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Sample records for motifs predict complexes

  1. Triangle network motifs predict complexes by complementing high-error interactomes with structural information.

    Science.gov (United States)

    Andreopoulos, Bill; Winter, Christof; Labudde, Dirk; Schroeder, Michael

    2009-06-27

    A lot of high-throughput studies produce protein-protein interaction networks (PPINs) with many errors and missing information. Even for genome-wide approaches, there is often a low overlap between PPINs produced by different studies. Second-level neighbors separated by two protein-protein interactions (PPIs) were previously used for predicting protein function and finding complexes in high-error PPINs. We retrieve second level neighbors in PPINs, and complement these with structural domain-domain interactions (SDDIs) representing binding evidence on proteins, forming PPI-SDDI-PPI triangles. We find low overlap between PPINs, SDDIs and known complexes, all well below 10%. We evaluate the overlap of PPI-SDDI-PPI triangles with known complexes from Munich Information center for Protein Sequences (MIPS). PPI-SDDI-PPI triangles have ~20 times higher overlap with MIPS complexes than using second-level neighbors in PPINs without SDDIs. The biological interpretation for triangles is that a SDDI causes two proteins to be observed with common interaction partners in high-throughput experiments. The relatively few SDDIs overlapping with PPINs are part of highly connected SDDI components, and are more likely to be detected in experimental studies. We demonstrate the utility of PPI-SDDI-PPI triangles by reconstructing myosin-actin processes in the nucleus, cytoplasm, and cytoskeleton, which were not obvious in the original PPIN. Using other complementary datatypes in place of SDDIs to form triangles, such as PubMed co-occurrences or threading information, results in a similar ability to find protein complexes. Given high-error PPINs with missing information, triangles of mixed datatypes are a promising direction for finding protein complexes. Integrating PPINs with SDDIs improves finding complexes. Structural SDDIs partially explain the high functional similarity of second-level neighbors in PPINs. We estimate that relatively little structural information would be sufficient

  2. Triangle network motifs predict complexes by complementing high-error interactomes with structural information

    Directory of Open Access Journals (Sweden)

    Labudde Dirk

    2009-06-01

    Full Text Available Abstract Background A lot of high-throughput studies produce protein-protein interaction networks (PPINs with many errors and missing information. Even for genome-wide approaches, there is often a low overlap between PPINs produced by different studies. Second-level neighbors separated by two protein-protein interactions (PPIs were previously used for predicting protein function and finding complexes in high-error PPINs. We retrieve second level neighbors in PPINs, and complement these with structural domain-domain interactions (SDDIs representing binding evidence on proteins, forming PPI-SDDI-PPI triangles. Results We find low overlap between PPINs, SDDIs and known complexes, all well below 10%. We evaluate the overlap of PPI-SDDI-PPI triangles with known complexes from Munich Information center for Protein Sequences (MIPS. PPI-SDDI-PPI triangles have ~20 times higher overlap with MIPS complexes than using second-level neighbors in PPINs without SDDIs. The biological interpretation for triangles is that a SDDI causes two proteins to be observed with common interaction partners in high-throughput experiments. The relatively few SDDIs overlapping with PPINs are part of highly connected SDDI components, and are more likely to be detected in experimental studies. We demonstrate the utility of PPI-SDDI-PPI triangles by reconstructing myosin-actin processes in the nucleus, cytoplasm, and cytoskeleton, which were not obvious in the original PPIN. Using other complementary datatypes in place of SDDIs to form triangles, such as PubMed co-occurrences or threading information, results in a similar ability to find protein complexes. Conclusion Given high-error PPINs with missing information, triangles of mixed datatypes are a promising direction for finding protein complexes. Integrating PPINs with SDDIs improves finding complexes. Structural SDDIs partially explain the high functional similarity of second-level neighbors in PPINs. We estimate that

  3. Discovery of candidate KEN-box motifs using cell cycle keyword enrichment combined with native disorder prediction and motif conservation.

    Science.gov (United States)

    Michael, Sushama; Travé, Gilles; Ramu, Chenna; Chica, Claudia; Gibson, Toby J

    2008-02-15

    KEN-box-mediated target selection is one of the mechanisms used in the proteasomal destruction of mitotic cell cycle proteins via the APC/C complex. While annotating the Eukaryotic Linear Motif resource (ELM, http://elm.eu.org/), we found that KEN motifs were significantly enriched in human protein entries with cell cycle keywords in the UniProt/Swiss-Prot database-implying that KEN-boxes might be more common than reported. Matches to short linear motifs in protein database searches are not, per se, significant. KEN-box enrichment with cell cycle Gene Ontology terms suggests that collectively these motifs are functional but does not prove that any given instance is so. Candidates were surveyed for native disorder prediction using GlobPlot and IUPred and for motif conservation in homologues. Among >25 strong new candidates, the most notable are human HIPK2, CHFR, CDC27, Dab2, Upf2, kinesin Eg5, DNA Topoisomerase 1 and yeast Cdc5 and Swi5. A similar number of weaker candidates were present. These proteins have yet to be tested for APC/C targeted destruction, providing potential new avenues of research.

  4. A novel k-mer set memory (KSM) motif representation improves regulatory variant prediction.

    Science.gov (United States)

    Guo, Yuchun; Tian, Kevin; Zeng, Haoyang; Guo, Xiaoyun; Gifford, David Kenneth

    2018-04-13

    The representation and discovery of transcription factor (TF) sequence binding specificities is critical for understanding gene regulatory networks and interpreting the impact of disease-associated noncoding genetic variants. We present a novel TF binding motif representation, the k -mer set memory (KSM), which consists of a set of aligned k -mers that are overrepresented at TF binding sites, and a new method called KMAC for de novo discovery of KSMs. We find that KSMs more accurately predict in vivo binding sites than position weight matrix (PWM) models and other more complex motif models across a large set of ChIP-seq experiments. Furthermore, KSMs outperform PWMs and more complex motif models in predicting in vitro binding sites. KMAC also identifies correct motifs in more experiments than five state-of-the-art motif discovery methods. In addition, KSM-derived features outperform both PWM and deep learning model derived sequence features in predicting differential regulatory activities of expression quantitative trait loci (eQTL) alleles. Finally, we have applied KMAC to 1600 ENCODE TF ChIP-seq data sets and created a public resource of KSM and PWM motifs. We expect that the KSM representation and KMAC method will be valuable in characterizing TF binding specificities and in interpreting the effects of noncoding genetic variations. © 2018 Guo et al.; Published by Cold Spring Harbor Laboratory Press.

  5. Distinct configurations of protein complexes and biochemical pathways revealed by epistatic interaction network motifs

    LENUS (Irish Health Repository)

    Casey, Fergal

    2011-08-22

    Abstract Background Gene and protein interactions are commonly represented as networks, with the genes or proteins comprising the nodes and the relationship between them as edges. Motifs, or small local configurations of edges and nodes that arise repeatedly, can be used to simplify the interpretation of networks. Results We examined triplet motifs in a network of quantitative epistatic genetic relationships, and found a non-random distribution of particular motif classes. Individual motif classes were found to be associated with different functional properties, suggestive of an underlying biological significance. These associations were apparent not only for motif classes, but for individual positions within the motifs. As expected, NNN (all negative) motifs were strongly associated with previously reported genetic (i.e. synthetic lethal) interactions, while PPP (all positive) motifs were associated with protein complexes. The two other motif classes (NNP: a positive interaction spanned by two negative interactions, and NPP: a negative spanned by two positives) showed very distinct functional associations, with physical interactions dominating for the former but alternative enrichments, typical of biochemical pathways, dominating for the latter. Conclusion We present a model showing how NNP motifs can be used to recognize supportive relationships between protein complexes, while NPP motifs often identify opposing or regulatory behaviour between a gene and an associated pathway. The ability to use motifs to point toward underlying biological organizational themes is likely to be increasingly important as more extensive epistasis mapping projects in higher organisms begin.

  6. Principal component analysis for predicting transcription-factor binding motifs from array-derived data

    Directory of Open Access Journals (Sweden)

    Vincenti Matthew P

    2005-11-01

    Full Text Available Abstract Background The responses to interleukin 1 (IL-1 in human chondrocytes constitute a complex regulatory mechanism, where multiple transcription factors interact combinatorially to transcription-factor binding motifs (TFBMs. In order to select a critical set of TFBMs from genomic DNA information and an array-derived data, an efficient algorithm to solve a combinatorial optimization problem is required. Although computational approaches based on evolutionary algorithms are commonly employed, an analytical algorithm would be useful to predict TFBMs at nearly no computational cost and evaluate varying modelling conditions. Singular value decomposition (SVD is a powerful method to derive primary components of a given matrix. Applying SVD to a promoter matrix defined from regulatory DNA sequences, we derived a novel method to predict the critical set of TFBMs. Results The promoter matrix was defined to establish a quantitative relationship between the IL-1-driven mRNA alteration and genomic DNA sequences of the IL-1 responsive genes. The matrix was decomposed with SVD, and the effects of 8 potential TFBMs (5'-CAGGC-3', 5'-CGCCC-3', 5'-CCGCC-3', 5'-ATGGG-3', 5'-GGGAA-3', 5'-CGTCC-3', 5'-AAAGG-3', and 5'-ACCCA-3' were predicted from a pool of 512 random DNA sequences. The prediction included matches to the core binding motifs of biologically known TFBMs such as AP2, SP1, EGR1, KROX, GC-BOX, ABI4, ETF, E2F, SRF, STAT, IK-1, PPARγ, STAF, ROAZ, and NFκB, and their significance was evaluated numerically using Monte Carlo simulation and genetic algorithm. Conclusion The described SVD-based prediction is an analytical method to provide a set of potential TFBMs involved in transcriptional regulation. The results would be useful to evaluate analytically a contribution of individual DNA sequences.

  7. Fast social-like learning of complex behaviors based on motor motifs

    Science.gov (United States)

    Calvo Tapia, Carlos; Tyukin, Ivan Y.; Makarov, Valeri A.

    2018-05-01

    Social learning is widely observed in many species. Less experienced agents copy successful behaviors exhibited by more experienced individuals. Nevertheless, the dynamical mechanisms behind this process remain largely unknown. Here we assume that a complex behavior can be decomposed into a sequence of n motor motifs. Then a neural network capable of activating motor motifs in a given sequence can drive an agent. To account for (n -1 )! possible sequences of motifs in a neural network, we employ the winnerless competition approach. We then consider a teacher-learner situation: one agent exhibits a complex movement, while another one aims at mimicking the teacher's behavior. Despite the huge variety of possible motif sequences we show that the learner, equipped with the provided learning model, can rewire "on the fly" its synaptic couplings in no more than (n -1 ) learning cycles and converge exponentially to the durations of the teacher's motifs. We validate the learning model on mobile robots. Experimental results show that the learner is indeed capable of copying the teacher's behavior composed of six motor motifs in a few learning cycles. The reported mechanism of learning is general and can be used for replicating different functions, including, for example, sound patterns or speech.

  8. Comparative analysis of evolutionarily conserved motifs of epidermal growth factor receptor 2 (HER2) predicts novel potential therapeutic epitopes

    DEFF Research Database (Denmark)

    Deng, Xiaohong; Zheng, Xuxu; Yang, Huanming

    2014-01-01

    druggable epitopes/targets. We employed the PROSITE Scan to detect structurally conserved motifs and PRINTS to search for linearly conserved motifs of ECD HER2. We found that the epitopes recognized by trastuzumab and pertuzumab are located in the predicted conserved motifs of ECD HER2, supporting our...

  9. Structural motifs of diiodine complexes with amides and thioamides.

    Science.gov (United States)

    Parigoridi, Ioanna-Efpraxia; Corban, Ghada J; Hadjikakou, Sotiris K; Hadjiliadis, Nick; Kourkoumelis, Nikolaos; Kostakis, George; Psycharis, Vassilis; Raptopoulou, Catherine P; Kubicki, Maciej

    2008-10-14

    The reaction of 2-pyrimidone hydrochloride ([C(4)H(5)N(2)O](+)[Cl](-) or [PMOH(2)](+)[Cl](-)) with diiodine in a dichloromethane-methanol solution resulted in the formation of ([C(4)H(5)N(2)O](+))(2)[I(2)Cl(2)](2-) (1) complex. The compound was characterized by elemental analysis, FT-IR, DTA-TG and conductivity titrations. The crystal structure of 1 was also determined by X-ray diffraction at 294(1) K. Compound 1 is monoclinic, space group P2(1)/n, consisting of two cationic [PMOH(2)](+) species and a [I(2)Cl(2)](2-) counter dianion. The cation is in its keto form. Direct reaction of thiazolidine-2-thione (tzdtH), with diiodine in dichloromethane solution, on the other hand, led to the formation of a crystalline solid which contained two complexes of formulae [(tzdtH)(2)I](+)[I(3)](-).2I(2) (2) and [(tzdtH)I(2)](2).I(2) (2a) in a ratio of 90 to 10%. Complex 2a was characterized by X-ray analysis at 180(2) K. Compound is monoclinic, space group C2/c and contains two units of [(tzdtH)I(2)] "spoke" structures. Compound 1, as well as the known species iodonium salt [(tzdtH)(2)I](+)[I(3)](-).2I(2) (2) and the charge transfer (CT) iodine complexes of formulae [(bztzdtH)I(2)] (3) and [(bztzdtH)I(2)].I(2) (4) (bztzdtH = 2-mercaptobenzothiazole) with "spoke" and extended "spoke" structures respectively, were tested for their oxidizing activity towards 3,5-di-tert-butylcatechol to 3,5-di-tert-butyl-o-benzoquinone.

  10. Core regulatory network motif underlies the ocellar complex patterning in Drosophila melanogaster

    Science.gov (United States)

    Aguilar-Hidalgo, D.; Lemos, M. C.; Córdoba, A.

    2015-03-01

    During organogenesis, developmental programs governed by Gene Regulatory Networks (GRN) define the functionality, size and shape of the different constituents of living organisms. Robustness, thus, is an essential characteristic that GRNs need to fulfill in order to maintain viability and reproducibility in a species. In the present work we analyze the robustness of the patterning for the ocellar complex formation in Drosophila melanogaster fly. We have systematically pruned the GRN that drives the development of this visual system to obtain the minimum pathway able to satisfy this pattern. We found that the mechanism underlying the patterning obeys to the dynamics of a 3-nodes network motif with a double negative feedback loop fed by a morphogenetic gradient that triggers the inhibition in a French flag problem fashion. A Boolean modeling of the GRN confirms robustness in the patterning mechanism showing the same result for different network complexity levels. Interestingly, the network provides a steady state solution in the interocellar part of the patterning and an oscillatory regime in the ocelli. This theoretical result predicts that the ocellar pattern may underlie oscillatory dynamics in its genetic regulation.

  11. Predictive Surface Complexation Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Sverjensky, Dimitri A. [Johns Hopkins Univ., Baltimore, MD (United States). Dept. of Earth and Planetary Sciences

    2016-11-29

    Surface complexation plays an important role in the equilibria and kinetics of processes controlling the compositions of soilwaters and groundwaters, the fate of contaminants in groundwaters, and the subsurface storage of CO2 and nuclear waste. Over the last several decades, many dozens of individual experimental studies have addressed aspects of surface complexation that have contributed to an increased understanding of its role in natural systems. However, there has been no previous attempt to develop a model of surface complexation that can be used to link all the experimental studies in order to place them on a predictive basis. Overall, my research has successfully integrated the results of the work of many experimentalists published over several decades. For the first time in studies of the geochemistry of the mineral-water interface, a practical predictive capability for modeling has become available. The predictive correlations developed in my research now enable extrapolations of experimental studies to provide estimates of surface chemistry for systems not yet studied experimentally and for natural and anthropogenically perturbed systems.

  12. Prediction of Biomolecular Complexes

    KAUST Repository

    Vangone, Anna

    2017-04-12

    Almost all processes in living organisms occur through specific interactions between biomolecules. Any dysfunction of those interactions can lead to pathological events. Understanding such interactions is therefore a crucial step in the investigation of biological systems and a starting point for drug design. In recent years, experimental studies have been devoted to unravel the principles of biomolecular interactions; however, due to experimental difficulties in solving the three-dimensional (3D) structure of biomolecular complexes, the number of available, high-resolution experimental 3D structures does not fulfill the current needs. Therefore, complementary computational approaches to model such interactions are necessary to assist experimentalists since a full understanding of how biomolecules interact (and consequently how they perform their function) only comes from 3D structures which provide crucial atomic details about binding and recognition processes. In this chapter we review approaches to predict biomolecular complexesBiomolecular complexes, introducing the concept of molecular dockingDocking, a technique which uses a combination of geometric, steric and energetics considerations to predict the 3D structure of a biological complex starting from the individual structures of its constituent parts. We provide a mini-guide about docking concepts, its potential and challenges, along with post-docking analysis and a list of related software.

  13. Prediction of Biomolecular Complexes

    KAUST Repository

    Vangone, Anna; Oliva, Romina; Cavallo, Luigi; Bonvin, Alexandre M. J. J.

    2017-01-01

    Almost all processes in living organisms occur through specific interactions between biomolecules. Any dysfunction of those interactions can lead to pathological events. Understanding such interactions is therefore a crucial step in the investigation of biological systems and a starting point for drug design. In recent years, experimental studies have been devoted to unravel the principles of biomolecular interactions; however, due to experimental difficulties in solving the three-dimensional (3D) structure of biomolecular complexes, the number of available, high-resolution experimental 3D structures does not fulfill the current needs. Therefore, complementary computational approaches to model such interactions are necessary to assist experimentalists since a full understanding of how biomolecules interact (and consequently how they perform their function) only comes from 3D structures which provide crucial atomic details about binding and recognition processes. In this chapter we review approaches to predict biomolecular complexesBiomolecular complexes, introducing the concept of molecular dockingDocking, a technique which uses a combination of geometric, steric and energetics considerations to predict the 3D structure of a biological complex starting from the individual structures of its constituent parts. We provide a mini-guide about docking concepts, its potential and challenges, along with post-docking analysis and a list of related software.

  14. Using hexamers to predict cis-regulatory motifs in Drosophila

    Directory of Open Access Journals (Sweden)

    Kibler Dennis

    2005-10-01

    Full Text Available Abstract Background Cis-regulatory modules (CRMs are short stretches of DNA that help regulate gene expression in higher eukaryotes. They have been found up to 1 megabase away from the genes they regulate and can be located upstream, downstream, and even within their target genes. Due to the difficulty of finding CRMs using biological and computational techniques, even well-studied regulatory systems may contain CRMs that have not yet been discovered. Results We present a simple, efficient method (HexDiff based only on hexamer frequencies of known CRMs and non-CRM sequence to predict novel CRMs in regulatory systems. On a data set of 16 gap and pair-rule genes containing 52 known CRMs, predictions made by HexDiff had a higher correlation with the known CRMs than several existing CRM prediction algorithms: Ahab, Cluster Buster, MSCAN, MCAST, and LWF. After combining the results of the different algorithms, 10 putative CRMs were identified and are strong candidates for future study. The hexamers used by HexDiff to distinguish between CRMs and non-CRM sequence were also analyzed and were shown to be enriched in regulatory elements. Conclusion HexDiff provides an efficient and effective means for finding new CRMs based on known CRMs, rather than known binding sites.

  15. Prediction of proteasome cleavage motifs by neural networks

    DEFF Research Database (Denmark)

    Kesimir, C.; Nussbaum, A.K.; Schild, H.

    2002-01-01

    physiological conditions. Our algorithm has been trained not only on in vitro data, but also on MHC Class I ligand data, which reflect a combination of immunoproteasome and constitutive proteasome specificity. This feature, together with the use of neural networks, a non-linear classification technique, make...... the prediction of MHC Class I ligand boundaries more accurate: 65% of the cleavage sites and 85% of the non-cleavage sites are correctly determined. Moreover, we show that the neural networks trained on the constitutive proteasome data learns a specificity that differs from that of the networks trained on MHC...

  16. Poly(A) motif prediction using spectral latent features from human DNA sequences

    KAUST Repository

    Xie, Bo; Jankovic, Boris R.; Bajic, Vladimir B.; Song, Le; Gao, Xin

    2013-01-01

    Motivation: Polyadenylation is the addition of a poly(A) tail to an RNA molecule. Identifying DNA sequence motifs that signal the addition of poly(A) tails is essential to improved genome annotation and better understanding of the regulatory mechanisms and stability of mRNA.Existing poly(A) motif predictors demonstrate that information extracted from the surrounding nucleotide sequences of candidate poly(A) motifs can differentiate true motifs from the false ones to a great extent. A variety of sophisticated features has been explored, including sequential, structural, statistical, thermodynamic and evolutionary properties. However, most of these methods involve extensive manual feature engineering, which can be time-consuming and can require in-depth domain knowledge.Results: We propose a novel machine-learning method for poly(A) motif prediction by marrying generative learning (hidden Markov models) and discriminative learning (support vector machines). Generative learning provides a rich palette on which the uncertainty and diversity of sequence information can be handled, while discriminative learning allows the performance of the classification task to be directly optimized. Here, we used hidden Markov models for fitting the DNA sequence dynamics, and developed an efficient spectral algorithm for extracting latent variable information from these models. These spectral latent features were then fed into support vector machines to fine-tune the classification performance.We evaluated our proposed method on a comprehensive human poly(A) dataset that consists of 14 740 samples from 12 of the most abundant variants of human poly(A) motifs. Compared with one of the previous state-of-the-art methods in the literature (the random forest model with expert-crafted features), our method reduces the average error rate, false-negative rate and false-positive rate by 26, 15 and 35%, respectively. Meanwhile, our method makes ?30% fewer error predictions relative to the other

  17. Poly(A) motif prediction using spectral latent features from human DNA sequences

    KAUST Repository

    Xie, Bo

    2013-06-21

    Motivation: Polyadenylation is the addition of a poly(A) tail to an RNA molecule. Identifying DNA sequence motifs that signal the addition of poly(A) tails is essential to improved genome annotation and better understanding of the regulatory mechanisms and stability of mRNA.Existing poly(A) motif predictors demonstrate that information extracted from the surrounding nucleotide sequences of candidate poly(A) motifs can differentiate true motifs from the false ones to a great extent. A variety of sophisticated features has been explored, including sequential, structural, statistical, thermodynamic and evolutionary properties. However, most of these methods involve extensive manual feature engineering, which can be time-consuming and can require in-depth domain knowledge.Results: We propose a novel machine-learning method for poly(A) motif prediction by marrying generative learning (hidden Markov models) and discriminative learning (support vector machines). Generative learning provides a rich palette on which the uncertainty and diversity of sequence information can be handled, while discriminative learning allows the performance of the classification task to be directly optimized. Here, we used hidden Markov models for fitting the DNA sequence dynamics, and developed an efficient spectral algorithm for extracting latent variable information from these models. These spectral latent features were then fed into support vector machines to fine-tune the classification performance.We evaluated our proposed method on a comprehensive human poly(A) dataset that consists of 14 740 samples from 12 of the most abundant variants of human poly(A) motifs. Compared with one of the previous state-of-the-art methods in the literature (the random forest model with expert-crafted features), our method reduces the average error rate, false-negative rate and false-positive rate by 26, 15 and 35%, respectively. Meanwhile, our method makes ?30% fewer error predictions relative to the other

  18. Dual hydrogen-bonding motifs in complexes formed between tropolone and formic acid

    Science.gov (United States)

    Nemchick, Deacon J.; Cohen, Michael K.; Vaccaro, Patrick H.

    2016-11-01

    The near-ultraviolet π*←π absorption system of weakly bound complexes formed between tropolone (TrOH) and formic acid (FA) under cryogenic free-jet expansion conditions has been interrogated by exploiting a variety of fluorescence-based laser-spectroscopic probes, with synergistic quantum-chemical calculations built upon diverse model chemistries being enlisted to unravel the structural and dynamical properties of the pertinent ground [X˜ 1A'] and excited [A˜ 1A'(" separators="π*π )] electronic states. For binary TrOH ṡ FA adducts, the presence of dual hydrogen-bond linkages gives rise to three low-lying isomers designated (in relative energy order) as INT, EXT1, and EXT2 depending on whether docking of the FA ligand to the TrOH substrate takes place internal or external to the five-membered reaction cleft of tropolone. While the symmetric double-minimum topography predicted for the INT potential surface mediates an intermolecular double proton-transfer event, the EXT1 and EXT2 structures are interconverted by an asymmetric single proton-transfer process that is TrOH-centric in nature. The A ˜ -X ˜ origin of TrOH ṡ FA at ν˜ 00=27 484 .45 cm-1 is displaced by δ ν˜ 00=+466 .76 cm-1 with respect to the analogous feature for bare tropolone and displays a hybrid type - a/b rotational contour that reflects the configuration of binding. A comprehensive analysis of vibrational landscapes supported by the optically connected X˜ 1A' and A˜ 1A'(" separators="π*π ) manifolds, including the characteristic isotopic shifts incurred by partial deuteration of the labile TrOH and FA protons, has been performed leading to the uniform assignment of numerous intermolecular (viz., modulating hydrogen-bond linkages) and intramolecular (viz., localized on monomer subunits) degrees of freedom. The holistic interpretation of all experimental and computational findings affords compelling evidence that an external-binding motif (attributed to EXT1), rather than the

  19. Prediction of host - pathogen protein interactions between Mycobacterium tuberculosis and Homo sapiens using sequence motifs.

    Science.gov (United States)

    Huo, Tong; Liu, Wei; Guo, Yu; Yang, Cheng; Lin, Jianping; Rao, Zihe

    2015-03-26

    Emergence of multiple drug resistant strains of M. tuberculosis (MDR-TB) threatens to derail global efforts aimed at reigning in the pathogen. Co-infections of M. tuberculosis with HIV are difficult to treat. To counter these new challenges, it is essential to study the interactions between M. tuberculosis and the host to learn how these bacteria cause disease. We report a systematic flow to predict the host pathogen interactions (HPIs) between M. tuberculosis and Homo sapiens based on sequence motifs. First, protein sequences were used as initial input for identifying the HPIs by 'interolog' method. HPIs were further filtered by prediction of domain-domain interactions (DDIs). Functional annotations of protein and publicly available experimental results were applied to filter the remaining HPIs. Using such a strategy, 118 pairs of HPIs were identified, which involve 43 proteins from M. tuberculosis and 48 proteins from Homo sapiens. A biological interaction network between M. tuberculosis and Homo sapiens was then constructed using the predicted inter- and intra-species interactions based on the 118 pairs of HPIs. Finally, a web accessible database named PATH (Protein interactions of M. tuberculosis and Human) was constructed to store these predicted interactions and proteins. This interaction network will facilitate the research on host-pathogen protein-protein interactions, and may throw light on how M. tuberculosis interacts with its host.

  20. Conserved Functional Motifs and Homology Modeling to Predict Hidden Moonlighting Functional Sites

    KAUST Repository

    Wong, Aloysius Tze; Gehring, Christoph A; Irving, Helen R.

    2015-01-01

    Moonlighting functional centers within proteins can provide them with hitherto unrecognized functions. Here, we review how hidden moonlighting functional centers, which we define as binding sites that have catalytic activity or regulate protein function in a novel manner, can be identified using targeted bioinformatic searches. Functional motifs used in such searches include amino acid residues that are conserved across species and many of which have been assigned functional roles based on experimental evidence. Molecules that were identified in this manner seeking cyclic mononucleotide cyclases in plants are used as examples. The strength of this computational approach is enhanced when good homology models can be developed to test the functionality of the predicted centers in silico, which, in turn, increases confidence in the ability of the identified candidates to perform the predicted functions. Computational characterization of moonlighting functional centers is not diagnostic for catalysis but serves as a rapid screening method, and highlights testable targets from a potentially large pool of candidates for subsequent in vitro and in vivo experiments required to confirm the functionality of the predicted moonlighting centers.

  1. Conserved Functional Motifs and Homology Modeling to Predict Hidden Moonlighting Functional Sites

    KAUST Repository

    Wong, Aloysius Tze

    2015-06-09

    Moonlighting functional centers within proteins can provide them with hitherto unrecognized functions. Here, we review how hidden moonlighting functional centers, which we define as binding sites that have catalytic activity or regulate protein function in a novel manner, can be identified using targeted bioinformatic searches. Functional motifs used in such searches include amino acid residues that are conserved across species and many of which have been assigned functional roles based on experimental evidence. Molecules that were identified in this manner seeking cyclic mononucleotide cyclases in plants are used as examples. The strength of this computational approach is enhanced when good homology models can be developed to test the functionality of the predicted centers in silico, which, in turn, increases confidence in the ability of the identified candidates to perform the predicted functions. Computational characterization of moonlighting functional centers is not diagnostic for catalysis but serves as a rapid screening method, and highlights testable targets from a potentially large pool of candidates for subsequent in vitro and in vivo experiments required to confirm the functionality of the predicted moonlighting centers.

  2. Structure-aided prediction of mammalian transcription factor complexes in conserved non-coding elements

    KAUST Repository

    Guturu, H.

    2013-11-11

    Mapping the DNA-binding preferences of transcription factor (TF) complexes is critical for deciphering the functions of cis-regulatory elements. Here, we developed a computational method that compares co-occurring motif spacings in conserved versus unconserved regions of the human genome to detect evolutionarily constrained binding sites of rigid TF complexes. Structural data were used to estimate TF complex physical plausibility, explore overlapping motif arrangements seldom tackled by non-structure-aware methods, and generate and analyse three-dimensional models of the predicted complexes bound to DNA. Using this approach, we predicted 422 physically realistic TF complex motifs at 18% false discovery rate, the majority of which (326, 77%) contain some sequence overlap between binding sites. The set of mostly novel complexes is enriched in known composite motifs, predictive of binding site configurations in TF-TF-DNA crystal structures, and supported by ChIP-seq datasets. Structural modelling revealed three cooperativity mechanisms: direct protein-protein interactions, potentially indirect interactions and \\'through-DNA\\' interactions. Indeed, 38% of the predicted complexes were found to contain four or more bases in which TF pairs appear to synergize through overlapping binding to the same DNA base pairs in opposite grooves or strands. Our TF complex and associated binding site predictions are available as a web resource at http://bejerano.stanford.edu/complex.

  3. Structure-aided prediction of mammalian transcription factor complexes in conserved non-coding elements

    KAUST Repository

    Guturu, H.; Doxey, A. C.; Wenger, A. M.; Bejerano, G.

    2013-01-01

    Mapping the DNA-binding preferences of transcription factor (TF) complexes is critical for deciphering the functions of cis-regulatory elements. Here, we developed a computational method that compares co-occurring motif spacings in conserved versus unconserved regions of the human genome to detect evolutionarily constrained binding sites of rigid TF complexes. Structural data were used to estimate TF complex physical plausibility, explore overlapping motif arrangements seldom tackled by non-structure-aware methods, and generate and analyse three-dimensional models of the predicted complexes bound to DNA. Using this approach, we predicted 422 physically realistic TF complex motifs at 18% false discovery rate, the majority of which (326, 77%) contain some sequence overlap between binding sites. The set of mostly novel complexes is enriched in known composite motifs, predictive of binding site configurations in TF-TF-DNA crystal structures, and supported by ChIP-seq datasets. Structural modelling revealed three cooperativity mechanisms: direct protein-protein interactions, potentially indirect interactions and 'through-DNA' interactions. Indeed, 38% of the predicted complexes were found to contain four or more bases in which TF pairs appear to synergize through overlapping binding to the same DNA base pairs in opposite grooves or strands. Our TF complex and associated binding site predictions are available as a web resource at http://bejerano.stanford.edu/complex.

  4. CompariMotif: quick and easy comparisons of sequence motifs.

    Science.gov (United States)

    Edwards, Richard J; Davey, Norman E; Shields, Denis C

    2008-05-15

    CompariMotif is a novel tool for making motif-motif comparisons, identifying and describing similarities between regular expression motifs. CompariMotif can identify a number of different relationships between motifs, including exact matches, variants of degenerate motifs and complex overlapping motifs. Motif relationships are scored using shared information content, allowing the best matches to be easily identified in large comparisons. Many input and search options are available, enabling a list of motifs to be compared to itself (to identify recurring motifs) or to datasets of known motifs. CompariMotif can be run online at http://bioware.ucd.ie/ and is freely available for academic use as a set of open source Python modules under a GNU General Public License from http://bioinformatics.ucd.ie/shields/software/comparimotif/

  5. Pol II promoter prediction using characteristic 4-mer motifs: a machine learning approach

    Directory of Open Access Journals (Sweden)

    Shoyaib Mohammad

    2008-10-01

    Full Text Available Abstract Background Eukaryotic promoter prediction using computational analysis techniques is one of the most difficult jobs in computational genomics that is essential for constructing and understanding genetic regulatory networks. The increased availability of sequence data for various eukaryotic organisms in recent years has necessitated for better tools and techniques for the prediction and analysis of promoters in eukaryotic sequences. Many promoter prediction methods and tools have been developed to date but they have yet to provide acceptable predictive performance. One obvious criteria to improve on current methods is to devise a better system for selecting appropriate features of promoters that distinguish them from non-promoters. Secondly improved performance can be achieved by enhancing the predictive ability of the machine learning algorithms used. Results In this paper, a novel approach is presented in which 128 4-mer motifs in conjunction with a non-linear machine-learning algorithm utilising a Support Vector Machine (SVM are used to distinguish between promoter and non-promoter DNA sequences. By applying this approach to plant, Drosophila, human, mouse and rat sequences, the classification model has showed 7-fold cross-validation percentage accuracies of 83.81%, 94.82%, 91.25%, 90.77% and 82.35% respectively. The high sensitivity and specificity value of 0.86 and 0.90 for plant; 0.96 and 0.92 for Drosophila; 0.88 and 0.92 for human; 0.78 and 0.84 for mouse and 0.82 and 0.80 for rat demonstrate that this technique is less prone to false positive results and exhibits better performance than many other tools. Moreover, this model successfully identifies location of promoter using TATA weight matrix. Conclusion The high sensitivity and specificity indicate that 4-mer frequencies in conjunction with supervised machine-learning methods can be beneficial in the identification of RNA pol II promoters comparative to other methods. This

  6. C-terminal motif prediction in eukaryotic proteomes using comparative genomics and statistical over-representation across protein families

    Directory of Open Access Journals (Sweden)

    Cutler Sean R

    2007-06-01

    Full Text Available Abstract Background The carboxy termini of proteins are a frequent site of activity for a variety of biologically important functions, ranging from post-translational modification to protein targeting. Several short peptide motifs involved in protein sorting roles and dependent upon their proximity to the C-terminus for proper function have already been characterized. As a limited number of such motifs have been identified, the potential exists for genome-wide statistical analysis and comparative genomics to reveal novel peptide signatures functioning in a C-terminal dependent manner. We have applied a novel methodology to the prediction of C-terminal-anchored peptide motifs involving a simple z-statistic and several techniques for improving the signal-to-noise ratio. Results We examined the statistical over-representation of position-specific C-terminal tripeptides in 7 eukaryotic proteomes. Sequence randomization models and simple-sequence masking were applied to the successful reduction of background noise. Similarly, as C-terminal homology among members of large protein families may artificially inflate tripeptide counts in an irrelevant and obfuscating manner, gene-family clustering was performed prior to the analysis in order to assess tripeptide over-representation across protein families as opposed to across all proteins. Finally, comparative genomics was used to identify tripeptides significantly occurring in multiple species. This approach has been able to predict, to our knowledge, all C-terminally anchored targeting motifs present in the literature. These include the PTS1 peroxisomal targeting signal (SKL*, the ER-retention signal (K/HDEL*, the ER-retrieval signal for membrane bound proteins (KKxx*, the prenylation signal (CC* and the CaaX box prenylation motif. In addition to a high statistical over-representation of these known motifs, a collection of significant tripeptides with a high propensity for biological function exists

  7. Flow Cytometry-Assisted Cloning of Specific Sequence Motifs from Complex 16S rRNA Gene Libraries

    DEFF Research Database (Denmark)

    Nielsen, Jeppe Lund; Schramm, Andreas; Bernhard, Anne E.

    2004-01-01

    for Systems Biology,3 Seattle, Washington, and Department of Ecological Microbiology, University of Bayreuth, Bayreuth, Germany2 A flow cytometry method was developed for rapid screening and recovery of cloned DNA containing common sequence motifs. This approach, termed fluorescence-activated cell sorting......  FLOW CYTOMETRY-ASSISTED CLONING OF SPECIFIC SEQUENCE MOTIFS FROM COMPLEX 16S RRNA GENE LIBRARIES Jeppe L. Nielsen,1 Andreas Schramm,1,2 Anne E. Bernhard,1 Gerrit J. van den Engh,3 and David A. Stahl1* Department of Civil and Environmental Engineering, University of Washington,1 and Institute......-assisted cloning, was used to recover sequences affiliated with a unique lineage within the Bacteroidetes not abundant in a clone library of environmental 16S rRNA genes.  ...

  8. Comparison of loline alkaloid gene clusters across fungal endophytes: predicting the co-regulatory sequence motifs and the evolutionary history.

    Science.gov (United States)

    Kutil, Brandi L; Greenwald, Charles; Liu, Gang; Spiering, Martin J; Schardl, Christopher L; Wilkinson, Heather H

    2007-10-01

    LOL, a fungal secondary metabolite gene cluster found in Epichloë and Neotyphodium species, is responsible for production of insecticidal loline alkaloids. To analyze the genetic architecture and to predict the evolutionary history of LOL, we compared five clusters from four fungal species (single clusters from Epichloë festucae, Neotyphodium sp. PauTG-1, Neotyphodium coenophialum, and two clusters we previously characterized in Neotyphodium uncinatum). Using PhyloCon to compare putative lol gene promoter regions, we have identified four motifs conserved across the lol genes in all five clusters. Each motif has significant similarity to known fungal transcription factor binding sites in the TRANSFAC database. Conservation of these motifs is further support for the hypothesis that the lol genes are co-regulated. Interestingly, the history of asexual Neotyphodium spp. includes multiple interspecific hybridization events. Comparing clusters from three Neotyphodium species and E. festucae allowed us to determine which Epichloë ancestors are the most likely contributors of LOL in these asexual species. For example, while no present day Epichloë typhina isolates are known to produce lolines, our data support the hypothesis that the E. typhina ancestor(s) of three asexual endophyte species contained a LOL gene cluster. Thus, these data support a model of evolution in which the polymorphism in loline alkaloid production phenotypes among endophyte species is likely due to the loss of the trait over time.

  9. GPS 2.1: enhanced prediction of kinase-specific phosphorylation sites with an algorithm of motif length selection.

    Science.gov (United States)

    Xue, Yu; Liu, Zexian; Cao, Jun; Ma, Qian; Gao, Xinjiao; Wang, Qingqi; Jin, Changjiang; Zhou, Yanhong; Wen, Longping; Ren, Jian

    2011-03-01

    As the most important post-translational modification of proteins, phosphorylation plays essential roles in all aspects of biological processes. Besides experimental approaches, computational prediction of phosphorylated proteins with their kinase-specific phosphorylation sites has also emerged as a popular strategy, for its low-cost, fast-speed and convenience. In this work, we developed a kinase-specific phosphorylation sites predictor of GPS 2.1 (Group-based Prediction System), with a novel but simple approach of motif length selection (MLS). By this approach, the robustness of the prediction system was greatly improved. All algorithms in GPS old versions were also reserved and integrated in GPS 2.1. The online service and local packages of GPS 2.1 were implemented in JAVA 1.5 (J2SE 5.0) and freely available for academic researches at: http://gps.biocuckoo.org.

  10. Markovian Model in High Order Sequence Prediction From Log-Motif Patterns in Agbada Paralic Section, Niger Delta, Nigeria

    International Nuclear Information System (INIS)

    Olabode, S. O.; Adekoya, J. A.

    2002-01-01

    Markovian model in the elucidation of high order sequence was applied to repetitive events of regressive and transgressive phases in the Agbada paralic section Niger Delta. The repetitive events are made up of delta front, delta topset and fluvio-deltaic sediments. The sediments consist of sands, sandstones, siltstones and shales in various proportions. Five wells: MN1, AA1, NP2, NP6 and NP8 were studied.Summary of biostratigraphic report and well log-motif patterns was used to delineate the third order depositional sequences in the wells.Various Markovian properties - observed transition frequency matrix, observed transition probability matrix, fixed probability vector, expected random matrix (randomised transition matrix) and difference matrix were determined for stacked high order sequence (high frequency cyclic events) nested within the third-order sequences using the log-motif patterns for the various sand bodies and shales. Flow diagrams were constructed for each of the depositional sequences to know the likely occurrence of number of cycles.Upward transition matrix between the log-motif patterns and flow diagram to elucidate cyclicity show that the overall regressive sequence of the Niger Delta has been modified by deltaic depositional elements and fluctuations in sea level. The predictions of higher order sequence within third order sequences from Markovian Properties provide good basis for correlation within the depositional sequences. The model has also been used to decipher the dominant depositional processes during the formation of the sequences. Discrete reservoir intervals and seal potentials within the sequences were also predicted from the flow diagrams constructed

  11. Space-related pharma-motifs for fast search of protein binding motifs and polypharmacological targets.

    Science.gov (United States)

    Chiu, Yi-Yuan; Lin, Chun-Yu; Lin, Chih-Ta; Hsu, Kai-Cheng; Chang, Li-Zen; Yang, Jinn-Moon

    2012-01-01

    To discover a compound inhibiting multiple proteins (i.e. polypharmacological targets) is a new paradigm for the complex diseases (e.g. cancers and diabetes). In general, the polypharmacological proteins often share similar local binding environments and motifs. As the exponential growth of the number of protein structures, to find the similar structural binding motifs (pharma-motifs) is an emergency task for drug discovery (e.g. side effects and new uses for old drugs) and protein functions. We have developed a Space-Related Pharmamotifs (called SRPmotif) method to recognize the binding motifs by searching against protein structure database. SRPmotif is able to recognize conserved binding environments containing spatially discontinuous pharma-motifs which are often short conserved peptides with specific physico-chemical properties for protein functions. Among 356 pharma-motifs, 56.5% interacting residues are highly conserved. Experimental results indicate that 81.1% and 92.7% polypharmacological targets of each protein-ligand complex are annotated with same biological process (BP) and molecular function (MF) terms, respectively, based on Gene Ontology (GO). Our experimental results show that the identified pharma-motifs often consist of key residues in functional (active) sites and play the key roles for protein functions. The SRPmotif is available at http://gemdock.life.nctu.edu.tw/SRP/. SRPmotif is able to identify similar pharma-interfaces and pharma-motifs sharing similar binding environments for polypharmacological targets by rapidly searching against the protein structure database. Pharma-motifs describe the conservations of binding environments for drug discovery and protein functions. Additionally, these pharma-motifs provide the clues for discovering new sequence-based motifs to predict protein functions from protein sequence databases. We believe that SRPmotif is useful for elucidating protein functions and drug discovery.

  12. Model complexity control for hydrologic prediction

    NARCIS (Netherlands)

    Schoups, G.; Van de Giesen, N.C.; Savenije, H.H.G.

    2008-01-01

    A common concern in hydrologic modeling is overparameterization of complex models given limited and noisy data. This leads to problems of parameter nonuniqueness and equifinality, which may negatively affect prediction uncertainties. A systematic way of controlling model complexity is therefore

  13. Rhythmic complexity and predictive coding

    DEFF Research Database (Denmark)

    Vuust, Peter; Witek, Maria A G

    2014-01-01

    Musical rhythm, consisting of apparently abstract intervals of accented temporal events,has a remarkable capacity to move our minds and bodies. How does the cognitive systemenable our experiences of rhythmically complex music? In this paper, we describe somecommon forms of rhythmic complexity...

  14. Contribution of Sequence Motif, Chromatin State, and DNA Structure Features to Predictive Models of Transcription Factor Binding in Yeast.

    Science.gov (United States)

    Tsai, Zing Tsung-Yeh; Shiu, Shin-Han; Tsai, Huai-Kuang

    2015-08-01

    Transcription factor (TF) binding is determined by the presence of specific sequence motifs (SM) and chromatin accessibility, where the latter is influenced by both chromatin state (CS) and DNA structure (DS) properties. Although SM, CS, and DS have been used to predict TF binding sites, a predictive model that jointly considers CS and DS has not been developed to predict either TF-specific binding or general binding properties of TFs. Using budding yeast as model, we found that machine learning classifiers trained with either CS or DS features alone perform better in predicting TF-specific binding compared to SM-based classifiers. In addition, simultaneously considering CS and DS further improves the accuracy of the TF binding predictions, indicating the highly complementary nature of these two properties. The contributions of SM, CS, and DS features to binding site predictions differ greatly between TFs, allowing TF-specific predictions and potentially reflecting different TF binding mechanisms. In addition, a "TF-agnostic" predictive model based on three DNA "intrinsic properties" (in silico predicted nucleosome occupancy, major groove geometry, and dinucleotide free energy) that can be calculated from genomic sequences alone has performance that rivals the model incorporating experiment-derived data. This intrinsic property model allows prediction of binding regions not only across TFs, but also across DNA-binding domain families with distinct structural folds. Furthermore, these predicted binding regions can help identify TF binding sites that have a significant impact on target gene expression. Because the intrinsic property model allows prediction of binding regions across DNA-binding domain families, it is TF agnostic and likely describes general binding potential of TFs. Thus, our findings suggest that it is feasible to establish a TF agnostic model for identifying functional regulatory regions in potentially any sequenced genome.

  15. Contribution of Sequence Motif, Chromatin State, and DNA Structure Features to Predictive Models of Transcription Factor Binding in Yeast.

    Directory of Open Access Journals (Sweden)

    Zing Tsung-Yeh Tsai

    2015-08-01

    Full Text Available Transcription factor (TF binding is determined by the presence of specific sequence motifs (SM and chromatin accessibility, where the latter is influenced by both chromatin state (CS and DNA structure (DS properties. Although SM, CS, and DS have been used to predict TF binding sites, a predictive model that jointly considers CS and DS has not been developed to predict either TF-specific binding or general binding properties of TFs. Using budding yeast as model, we found that machine learning classifiers trained with either CS or DS features alone perform better in predicting TF-specific binding compared to SM-based classifiers. In addition, simultaneously considering CS and DS further improves the accuracy of the TF binding predictions, indicating the highly complementary nature of these two properties. The contributions of SM, CS, and DS features to binding site predictions differ greatly between TFs, allowing TF-specific predictions and potentially reflecting different TF binding mechanisms. In addition, a "TF-agnostic" predictive model based on three DNA "intrinsic properties" (in silico predicted nucleosome occupancy, major groove geometry, and dinucleotide free energy that can be calculated from genomic sequences alone has performance that rivals the model incorporating experiment-derived data. This intrinsic property model allows prediction of binding regions not only across TFs, but also across DNA-binding domain families with distinct structural folds. Furthermore, these predicted binding regions can help identify TF binding sites that have a significant impact on target gene expression. Because the intrinsic property model allows prediction of binding regions across DNA-binding domain families, it is TF agnostic and likely describes general binding potential of TFs. Thus, our findings suggest that it is feasible to establish a TF agnostic model for identifying functional regulatory regions in potentially any sequenced genome.

  16. Computational analysis and prediction of the binding motif and protein interacting partners of the Abl SH3 domain.

    Directory of Open Access Journals (Sweden)

    Tingjun Hou

    2006-01-01

    Full Text Available Protein-protein interactions, particularly weak and transient ones, are often mediated by peptide recognition domains, such as Src Homology 2 and 3 (SH2 and SH3 domains, which bind to specific sequence and structural motifs. It is important but challenging to determine the binding specificity of these domains accurately and to predict their physiological interacting partners. In this study, the interactions between 35 peptide ligands (15 binders and 20 non-binders and the Abl SH3 domain were analyzed using molecular dynamics simulation and the Molecular Mechanics/Poisson-Boltzmann Solvent Area method. The calculated binding free energies correlated well with the rank order of the binding peptides and clearly distinguished binders from non-binders. Free energy component analysis revealed that the van der Waals interactions dictate the binding strength of peptides, whereas the binding specificity is determined by the electrostatic interaction and the polar contribution of desolvation. The binding motif of the Abl SH3 domain was then determined by a virtual mutagenesis method, which mutates the residue at each position of the template peptide relative to all other 19 amino acids and calculates the binding free energy difference between the template and the mutated peptides using the Molecular Mechanics/Poisson-Boltzmann Solvent Area method. A single position mutation free energy profile was thus established and used as a scoring matrix to search peptides recognized by the Abl SH3 domain in the human genome. Our approach successfully picked ten out of 13 experimentally determined binding partners of the Abl SH3 domain among the top 600 candidates from the 218,540 decapeptides with the PXXP motif in the SWISS-PROT database. We expect that this physical-principle based method can be applied to other protein domains as well.

  17. Identification of Ubiquinol Binding Motifs at the Qo-Site of the Cytochrome bc1 Complex

    DEFF Research Database (Denmark)

    Barragan, Angela M.; Crofts, Antony R.; Schulten, Klaus

    2015-01-01

    for the function of the bc1 complex is the initial redox process that involves a bifurcated electron transfer in which the two electrons from a quinol substrate are passed to different electron acceptors in the bc1 complex. The electron transfer is coupled to proton transfer. The overall mechanism of quinol...... all atom molecular dynamics and quantum chemical calculations to reveal the binding modes of quinol at the Qo-site of the bc1 complex from Rhodobacter capsulatus. The calculations suggest a novel configuration of amino acid residues responsible for quinol binding and support a mechanism for proton...

  18. The Crc and Hfq proteins of Pseudomonas putida cooperate in catabolite repression and formation of ribonucleic acid complexes with specific target motifs.

    Science.gov (United States)

    Moreno, Renata; Hernández-Arranz, Sofía; La Rosa, Ruggero; Yuste, Luis; Madhushani, Anjana; Shingler, Victoria; Rojo, Fernando

    2015-01-01

    The Crc protein is a global regulator that has a key role in catabolite repression and optimization of metabolism in Pseudomonads. Crc inhibits gene expression post-transcriptionally, preventing translation of mRNAs bearing an AAnAAnAA motif [the catabolite activity (CA) motif] close to the translation start site. Although Crc was initially believed to bind RNA by itself, this idea was recently challenged by results suggesting that a protein co-purifying with Crc, presumably the Hfq protein, could account for the detected RNA-binding activity. Hfq is an abundant protein that has a central role in post-transcriptional gene regulation. Herein, we show that the Pseudomonas putida Hfq protein can recognize the CA motifs of RNAs through its distal face and that Crc facilitates formation of a more stable complex at these targets. Crc was unable to bind RNA in the absence of Hfq. However, pull-down assays showed that Crc and Hfq can form a co-complex with RNA containing a CA motif in vitro. Inactivation of the hfq or the crc gene impaired catabolite repression to a similar extent. We propose that Crc and Hfq cooperate in catabolite repression, probably through forming a stable co-complex with RNAs containing CA motifs to result in inhibition of translation initiation. © 2014 Society for Applied Microbiology and John Wiley & Sons Ltd.

  19. Genome-wide targeted prediction of ABA responsive genes in rice based on over-represented cis-motif in co-expressed genes.

    Science.gov (United States)

    Lenka, Sangram K; Lohia, Bikash; Kumar, Abhay; Chinnusamy, Viswanathan; Bansal, Kailash C

    2009-02-01

    Abscisic acid (ABA), the popular plant stress hormone, plays a key role in regulation of sub-set of stress responsive genes. These genes respond to ABA through specific transcription factors which bind to cis-regulatory elements present in their promoters. We discovered the ABA Responsive Element (ABRE) core (ACGT) containing CGMCACGTGB motif as over-represented motif among the promoters of ABA responsive co-expressed genes in rice. Targeted gene prediction strategy using this motif led to the identification of 402 protein coding genes potentially regulated by ABA-dependent molecular genetic network. RT-PCR analysis of arbitrarily chosen 45 genes from the predicted 402 genes confirmed 80% accuracy of our prediction. Plant Gene Ontology (GO) analysis of ABA responsive genes showed enrichment of signal transduction and stress related genes among diverse functional categories.

  20. Design and evaluation of antimalarial peptides derived from prediction of short linear motifs in proteins related to erythrocyte invasion.

    Directory of Open Access Journals (Sweden)

    Alessandra Bianchin

    Full Text Available The purpose of this study was to investigate the blood stage of the malaria causing parasite, Plasmodium falciparum, to predict potential protein interactions between the parasite merozoite and the host erythrocyte and design peptides that could interrupt these predicted interactions. We screened the P. falciparum and human proteomes for computationally predicted short linear motifs (SLiMs in cytoplasmic portions of transmembrane proteins that could play roles in the invasion of the erythrocyte by the merozoite, an essential step in malarial pathogenesis. We tested thirteen peptides predicted to contain SLiMs, twelve of them palmitoylated to enhance membrane targeting, and found three that blocked parasite growth in culture by inhibiting the initiation of new infections in erythrocytes. Scrambled peptides for two of the most promising peptides suggested that their activity may be reflective of amino acid properties, in particular, positive charge. However, one peptide showed effects which were stronger than those of scrambled peptides. This was derived from human red blood cell glycophorin-B. We concluded that proteome-wide computational screening of the intracellular regions of both host and pathogen adhesion proteins provides potential lead peptides for the development of anti-malarial compounds.

  1. Complexity factors and prediction of performance

    International Nuclear Information System (INIS)

    Braarud, Per Oeyvind

    1998-03-01

    Understanding of what makes a control room situation difficult to handle is important when studying operator performance, both with respect to prediction as well as improvement of the human performance. A factor analytic approach identified eight factors from operators' answers to an 39 item questionnaire about complexity of the operator's task in the control room. A Complexity Profiling Questionnaire was developed, based on the factor analytic results from the operators' conception of complexity. The validity of the identified complexity factors was studied by prediction of crew performance and prediction of plant performance from ratings of the complexity of scenarios. The scenarios were rated by both process experts and the operators participating in the scenarios, using the Complexity Profiling Questionnaire. The process experts' complexity ratings predicted both crew performance and plant performance, while the operators' rating predicted plant performance only. The results reported are from initial studies of complexity, and imply a promising potential for further studies of the concept. The approach used in the study as well as the reported results are discussed. A chapter about the structure of the conception of complexity, and a chapter about further research conclude the report. (author)

  2. The KYxxL motif in Rad17 protein is essential for the interaction with the 9–1–1 complex

    Energy Technology Data Exchange (ETDEWEB)

    Fukumoto, Yasunori, E-mail: fukumoto@faculty.chiba-u.jp [Laboratory of Molecular Cell Biology, Graduate School of Pharmaceutical Sciences, Chiba University, Chiba 260-8675 (Japan); Ikeuchi, Masayoshi; Nakayama, Yuji [Department of Biochemistry & Molecular Biology, Kyoto Pharmaceutical University, Kyoto 607-8414 (Japan); Yamaguchi, Naoto, E-mail: nyama@faculty.chiba-u.jp [Laboratory of Molecular Cell Biology, Graduate School of Pharmaceutical Sciences, Chiba University, Chiba 260-8675 (Japan)

    2016-09-02

    ATR-dependent DNA damage checkpoint is the major DNA damage checkpoint against UV irradiation and DNA replication stress. The Rad17–RFC and Rad9–Rad1–Hus1 (9–1–1) complexes interact with each other to contribute to ATR signaling, however, the precise regulatory mechanism of the interaction has not been established. Here, we identified a conserved sequence motif, KYxxL, in the AAA+ domain of Rad17 protein, and demonstrated that this motif is essential for the interaction with the 9–1–1 complex. We also show that UV-induced Rad17 phosphorylation is increased in the Rad17 KYxxL mutants. These data indicate that the interaction with the 9–1–1 complex is not required for Rad17 protein to be an efficient substrate for the UV-induced phosphorylation. Our data also raise the possibility that the 9–1–1 complex plays a negative regulatory role in the Rad17 phosphorylation. We also show that the nucleotide-binding activity of Rad17 is required for its nuclear localization. - Highlights: • We have identified a conserved KYxxL motif in Rad17 protein. • The KYxxL motif is crucial for the interaction with the 9–1–1 complex. • The KYxxL motif is dispensable or inhibitory for UV-induced Rad17 phosphorylation. • Nucleotide binding of Rad17 is required for its nuclear localization.

  3. A nucleobase-centered coarse-grained representation for structure prediction of RNA motifs.

    Science.gov (United States)

    Poblete, Simón; Bottaro, Sandro; Bussi, Giovanni

    2018-02-28

    We introduce the SPlit-and-conQueR (SPQR) model, a coarse-grained (CG) representation of RNA designed for structure prediction and refinement. In our approach, the representation of a nucleotide consists of a point particle for the phosphate group and an anisotropic particle for the nucleoside. The interactions are, in principle, knowledge-based potentials inspired by the $\\mathcal {E}$SCORE function, a base-centered scoring function. However, a special treatment is given to base-pairing interactions and certain geometrical conformations which are lost in a raw knowledge-based model. This results in a representation able to describe planar canonical and non-canonical base pairs and base-phosphate interactions and to distinguish sugar puckers and glycosidic torsion conformations. The model is applied to the folding of several structures, including duplexes with internal loops of non-canonical base pairs, tetraloops, junctions and a pseudoknot. For the majority of these systems, experimental structures are correctly predicted at the level of individual contacts. We also propose a method for efficiently reintroducing atomistic detail from the CG representation.

  4. Quantitative characterisation of complexity and predictability

    International Nuclear Information System (INIS)

    Badii, R.

    1990-04-01

    A measure of complexity for sequentially created symbolic patterns is introduced. The underlying grammatical rules are systematically detected in terms of variable-length prefix-free codewords and arranged on a 'logic' tree. Predictions on the scaling structure of the system are then formulated and compared with the observation. The discrepancy between the two, evaluated through a generalisation of the information gain, characterises the complexity of the system, relative to the unfolding scheme. (author) 1 fig., 20 refs

  5. Organization of feed-forward loop motifs reveals architectural principles in natural and engineered networks.

    Science.gov (United States)

    Gorochowski, Thomas E; Grierson, Claire S; di Bernardo, Mario

    2018-03-01

    Network motifs are significantly overrepresented subgraphs that have been proposed as building blocks for natural and engineered networks. Detailed functional analysis has been performed for many types of motif in isolation, but less is known about how motifs work together to perform complex tasks. To address this issue, we measure the aggregation of network motifs via methods that extract precisely how these structures are connected. Applying this approach to a broad spectrum of networked systems and focusing on the widespread feed-forward loop motif, we uncover striking differences in motif organization. The types of connection are often highly constrained, differ between domains, and clearly capture architectural principles. We show how this information can be used to effectively predict functionally important nodes in the metabolic network of Escherichia coli . Our findings have implications for understanding how networked systems are constructed from motif parts and elucidate constraints that guide their evolution.

  6. Crystal structure of the G3BP2 NTF2-like domain in complex with a canonical FGDF motif peptide

    DEFF Research Database (Denmark)

    Kristensen, Ole

    2015-01-01

    -terminal domains of the G3BP1 and Rasputin proteins. Recently, a subset of G3BP interacting proteins was recognized to share a common sequence motif, FGDF. The most studied binding partners, USP10 and viral nsP3, interfere with essential G3BP functions related to assembly of cellular stress granules. Reported...

  7. Identification of sequence motifs significantly associated with antisense activity

    Directory of Open Access Journals (Sweden)

    Peek Andrew S

    2007-06-01

    mediators to speed the process along like the RNA Induced Silencing Complex (RISC in RNAi. The independence of motif position and antisense activity also allows us to bypass consideration of this feature in the modelling process, promoting model efficiency and reducing the chance of overfitting when predicting antisense activity. The increase in SVR correlation with significant features compared to nearest-neighbour features indicates that thermodynamics alone is likely not the only factor in determining antisense efficiency.

  8. NNAlign: A Web-Based Prediction Method Allowing Non-Expert End-User Discovery of Sequence Motifs in Quantitative Peptide Data

    DEFF Research Database (Denmark)

    Andreatta, Massimo; Schafer-Nielsen, Claus; Lund, Ole

    2011-01-01

    Recent advances in high-throughput technologies have made it possible to generate both gene and protein sequence data at an unprecedented rate and scale thereby enabling entirely new "omics"-based approaches towards the analysis of complex biological processes. However, the amount and complexity...... to interpret large data sets. We have recently developed a method, NNAlign, which is generally applicable to any biological problem where quantitative peptide data is available. This method efficiently identifies underlying sequence patterns by simultaneously aligning peptide sequences and identifying motifs...... associated with quantitative readouts. Here, we provide a web-based implementation of NNAlign allowing non-expert end-users to submit their data (optionally adjusting method parameters), and in return receive a trained method (including a visual representation of the identified motif) that subsequently can...

  9. Ménage à trois: the complex relationships between mitogen-activated protein kinases, WRKY transcription factors, and VQ-motif-containing proteins.

    Science.gov (United States)

    Weyhe, Martin; Eschen-Lippold, Lennart; Pecher, Pascal; Scheel, Dierk; Lee, Justin

    2014-01-01

    Out of the 34 members of the VQ-motif-containing protein (VQP) family, 10 are phosphorylated by the mitogen-activated protein kinases (MAPKs), MPK3 and MPK6. Most of these MPK3/6-targeted VQPs (MVQs) interacted with specific sub-groups of WRKY transcription factors in a VQ-motif-dependent manner. In some cases, the MAPK appears to phosphorylate either the MVQ or the WRKY, while in other cases, both proteins have been reported to act as MAPK substrates. We propose a network of dynamic interactions between members from the MAPK, MVQ and WRKY families - either as binary or as tripartite interactions. The compositions of the WRKY-MVQ transcriptional protein complexes may change - for instance, through MPK3/6-mediated modulation of protein stability - and therefore control defense gene transcription.

  10. MHC motif viewer

    DEFF Research Database (Denmark)

    Rapin, Nicolas Philippe Jean-Pierre; Hoof, Ilka; Lund, Ole

    2008-01-01

    . Algorithms that predict which peptides MHC molecules bind have recently been developed and cover many different alleles, but the utility of these algorithms is hampered by the lack of tools for browsing and comparing the specificity of these molecules. We have, therefore, developed a web server, MHC motif....... A special viewing feature, MHC fight, allows for display of the specificity of two different MHC molecules side by side. We show how the web server can be used to discover and display surprising similarities as well as differences between MHC molecules within and between different species. The MHC motif...

  11. Predicting tissue specific cis-regulatory modules in the human genome using pairs of co-occurring motifs

    Directory of Open Access Journals (Sweden)

    Girgis Hani Z

    2012-02-01

    Full Text Available Abstract Background Researchers seeking to unlock the genetic basis of human physiology and diseases have been studying gene transcription regulation. The temporal and spatial patterns of gene expression are controlled by mainly non-coding elements known as cis-regulatory modules (CRMs and epigenetic factors. CRMs modulating related genes share the regulatory signature which consists of transcription factor (TF binding sites (TFBSs. Identifying such CRMs is a challenging problem due to the prohibitive number of sequence sets that need to be analyzed. Results We formulated the challenge as a supervised classification problem even though experimentally validated CRMs were not required. Our efforts resulted in a software system named CrmMiner. The system mines for CRMs in the vicinity of related genes. CrmMiner requires two sets of sequences: a mixed set and a control set. Sequences in the vicinity of the related genes comprise the mixed set, whereas the control set includes random genomic sequences. CrmMiner assumes that a large percentage of the mixed set is made of background sequences that do not include CRMs. The system identifies pairs of closely located motifs representing vertebrate TFBSs that are enriched in the training mixed set consisting of 50% of the gene loci. In addition, CrmMiner selects a group of the enriched pairs to represent the tissue-specific regulatory signature. The mixed and the control sets are searched for candidate sequences that include any of the selected pairs. Next, an optimal Bayesian classifier is used to distinguish candidates found in the mixed set from their control counterparts. Our study proposes 62 tissue-specific regulatory signatures and putative CRMs for different human tissues and cell types. These signatures consist of assortments of ubiquitously expressed TFs and tissue-specific TFs. Under controlled settings, CrmMiner identified known CRMs in noisy sets up to 1:25 signal-to-noise ratio. CrmMiner was

  12. Alpha complexes in protein structure prediction

    DEFF Research Database (Denmark)

    Winter, Pawel; Fonseca, Rasmus

    2015-01-01

    Reducing the computational effort and increasing the accuracy of potential energy functions is of utmost importance in modeling biological systems, for instance in protein structure prediction, docking or design. Evaluating interactions between nonbonded atoms is the bottleneck of such computations......-complexes from scratch for every configuration encountered during the search for the native structure would make this approach hopelessly slow. However, it is argued that kinetic a-complexes can be used to reduce the computational effort of determining the potential energy when "moving" from one configuration...... to a neighboring one. As a consequence, relatively expensive (initial) construction of an a-complex is expected to be compensated by subsequent fast kinetic updates during the search process. Computational results presented in this paper are limited. However, they suggest that the applicability of a...

  13. Crystal structure of the G3BP2 NTF2-like domain in complex with a canonical FGDF motif peptide.

    Science.gov (United States)

    Kristensen, Ole

    2015-11-06

    The crystal structure of the NTF2-like domain of the human Ras GTPase SH3 Binding Protein (G3BP), isoform 2, was determined at a resolution of 2.75 Å in complex with a peptide containing a FGDF sequence motif. The overall structure of the protein is highly similar to the homodimeric N-terminal domains of the G3BP1 and Rasputin proteins. Recently, a subset of G3BP interacting proteins was recognized to share a common sequence motif, FGDF. The most studied binding partners, USP10 and viral nsP3, interfere with essential G3BP functions related to assembly of cellular stress granules. Reported molecular modeling suggested that FGDF-motif containing peptides bind in an extended conformation into a hydrophobic groove on the surface of the G3BP NTF2-like domain in a manner similar to the known binding of FxFG nucleoporin repeats. The results in this paper provide evidence for a different binding mode. The FGDF peptide binds and changes conformation of the protruding N-terminal residues by providing hydrophobic interactions to a symmetry related molecule that facilitated crystallization of the G3BP2 isoform. Copyright © 2015 Elsevier Inc. All rights reserved.

  14. Motif statistics and spike correlations in neuronal networks

    International Nuclear Information System (INIS)

    Hu, Yu; Shea-Brown, Eric; Trousdale, James; Josić, Krešimir

    2013-01-01

    Motifs are patterns of subgraphs of complex networks. We studied the impact of such patterns of connectivity on the level of correlated, or synchronized, spiking activity among pairs of cells in a recurrent network of integrate and fire neurons. For a range of network architectures, we find that the pairwise correlation coefficients, averaged across the network, can be closely approximated using only three statistics of network connectivity. These are the overall network connection probability and the frequencies of two second order motifs: diverging motifs, in which one cell provides input to two others, and chain motifs, in which two cells are connected via a third intermediary cell. Specifically, the prevalence of diverging and chain motifs tends to increase correlation. Our method is based on linear response theory, which enables us to express spiking statistics using linear algebra, and a resumming technique, which extrapolates from second order motifs to predict the overall effect of coupling on network correlation. Our motif-based results seek to isolate the effect of network architecture perturbatively from a known network state. (paper)

  15. Direct AUC optimization of regulatory motifs.

    Science.gov (United States)

    Zhu, Lin; Zhang, Hong-Bo; Huang, De-Shuang

    2017-07-15

    The discovery of transcription factor binding site (TFBS) motifs is essential for untangling the complex mechanism of genetic variation under different developmental and environmental conditions. Among the huge amount of computational approaches for de novo identification of TFBS motifs, discriminative motif learning (DML) methods have been proven to be promising for harnessing the discovery power of accumulated huge amount of high-throughput binding data. However, they have to sacrifice accuracy for speed and could fail to fully utilize the information of the input sequences. We propose a novel algorithm called CDAUC for optimizing DML-learned motifs based on the area under the receiver-operating characteristic curve (AUC) criterion, which has been widely used in the literature to evaluate the significance of extracted motifs. We show that when the considered AUC loss function is optimized in a coordinate-wise manner, the cost function of each resultant sub-problem is a piece-wise constant function, whose optimal value can be found exactly and efficiently. Further, a key step of each iteration of CDAUC can be efficiently solved as a computational geometry problem. Experimental results on real world high-throughput datasets illustrate that CDAUC outperforms competing methods for refining DML motifs, while being one order of magnitude faster. Meanwhile, preliminary results also show that CDAUC may also be useful for improving the interpretability of convolutional kernels generated by the emerging deep learning approaches for predicting TF sequences specificities. CDAUC is available at: https://drive.google.com/drive/folders/0BxOW5MtIZbJjNFpCeHlBVWJHeW8 . dshuang@tongji.edu.cn. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

  16. Mutations in the putative zinc-binding motif of UL52 demonstrate a complex interdependence between the UL5 and UL52 subunits of the human herpes simplex virus type 1 helicase/primase complex.

    Science.gov (United States)

    Chen, Yan; Carrington-Lawrence, Stacy D; Bai, Ping; Weller, Sandra K

    2005-07-01

    Herpes simplex virus type 1 (HSV-1) encodes a heterotrimeric helicase-primase (UL5/8/52) complex. UL5 contains seven motifs found in helicase superfamily 1, and UL52 contains conserved motifs found in primases. The contributions of each subunit to the biochemical activities of the complex, however, remain unclear. We have previously demonstrated that a mutation in the putative zinc finger at UL52 C terminus abrogates not only primase but also ATPase, helicase, and DNA-binding activities of a UL5/UL52 subcomplex, indicating a complex interdependence between the two subunits. To test this hypothesis and to further investigate the role of the zinc finger in the enzymatic activities of the helicase-primase, a series of mutations were constructed in this motif. They differed in their ability to complement a UL52 null virus: totally defective, partial complementation, and potentiating. In this study, four of these mutants were studied biochemically after expression and purification from insect cells infected with recombinant baculoviruses. All mutants show greatly reduced primase activity. Complementation-defective mutants exhibited severe defects in ATPase, helicase, and DNA-binding activities. Partially complementing mutants displayed intermediate levels of these activities, except that one showed a wild-type level of helicase activity. These data suggest that the UL52 zinc finger motif plays an important role in the activities of the helicase-primase complex. The observation that mutations in UL52 affected helicase, ATPase, and DNA-binding activities indicates that UL52 binding to DNA via the zinc finger may be necessary for loading UL5. Alternatively, UL5 and UL52 may share a DNA-binding interface.

  17. Expression, refolding and crystallizations of the Grb2-like (GADS) C-terminal SH3 domain complexed with a SLP-76 motif peptide

    International Nuclear Information System (INIS)

    Faravelli, Alessandro; Dimasi, Nazzareno

    2005-01-01

    Several crystals of the Grb2-like C-terminal SH3 domain in complex with a motif peptide from the SLP-76 protein were obtained and characterized. The Grb2-like adaptor protein GADS is composed of an N-terminal SH3 domain, an SH2 domain, a proline-rich region and a C-terminal SH3 domain. GADS interacts through its C-terminal SH3 domain with the adaptor protein SLP-76, thus recruiting this protein and other associated molecules to the linker for activation of T-cell (LAT) protein. The DNA encoding the C-terminal SH3 domain of GADS (GADS-cSH3) was assembled synthetically using a recursive PCR technique and the protein was overexpressed in Escherichia coli, refolded and purified. Several crystals of this domain in complex with the SLP-76 peptide were obtained and characterized

  18. The Arabidopsis GAGA-Binding Factor BASIC PENTACYSTEINE6 Recruits the POLYCOMB-REPRESSIVE COMPLEX1 Component LIKE HETEROCHROMATIN PROTEIN1 to GAGA DNA Motifs.

    Science.gov (United States)

    Hecker, Andreas; Brand, Luise H; Peter, Sébastien; Simoncello, Nathalie; Kilian, Joachim; Harter, Klaus; Gaudin, Valérie; Wanke, Dierk

    2015-07-01

    Polycomb-repressive complexes (PRCs) play key roles in development by repressing a large number of genes involved in various functions. Much, however, remains to be discovered about PRC-silencing mechanisms as well as their targeting to specific genomic regions. Besides other mechanisms, GAGA-binding factors in animals can guide PRC members in a sequence-specific manner to Polycomb-responsive DNA elements. Here, we show that the Arabidopsis (Arabidopsis thaliana) GAGA-motif binding factor protein basic pentacysteine6 (BPC6) interacts with like heterochromatin protein1 (LHP1), a PRC1 component, and associates with vernalization2 (VRN2), a PRC2 component, in vivo. By using a modified DNA-protein interaction enzyme-linked immunosorbant assay, we could show that BPC6 was required and sufficient to recruit LHP1 to GAGA motif-containing DNA probes in vitro. We also found that LHP1 interacts with VRN2 and, therefore, can function as a possible scaffold between BPC6 and VRN2. The lhp1-4 bpc4 bpc6 triple mutant displayed a pleiotropic phenotype, extreme dwarfism and early flowering, which disclosed synergistic functions of LHP1 and group II plant BPC members. Transcriptome analyses supported this synergy and suggested a possible function in the concerted repression of homeotic genes, probably through histone H3 lysine-27 trimethylation. Hence, our findings suggest striking similarities between animal and plant GAGA-binding factors in the recruitment of PRC1 and PRC2 components to Polycomb-responsive DNA element-like GAGA motifs, which must have evolved through convergent evolution. © 2015 American Society of Plant Biologists. All Rights Reserved.

  19. PREDICTION OF THERMODYNAMIC PROPERTIES OF COMPLEX FLUIDS

    International Nuclear Information System (INIS)

    Marc Donohue

    2006-01-01

    The goal of this research has been to generalize Density Functional Theory (DFT) for complex molecules, i.e. molecules whose size, shape, and interaction energies cause them to show significant deviations from mean-field behavior. We considered free energy functionals and minimized them for systems with different geometries and dimensionalities including confined fluids (such as molecular layers on surfaces and molecules in nano-scale pores), systems with directional interactions and order-disorder transitions, amphiphilic dimers, block copolymers, and self-assembled nano-structures. The results of this procedure include equations of equilibrium for these systems and the development of computational tools for predicting phase transitions and self-assembly in complex fluids. DFT was developed for confined fluids. A new phenomenon, surface compression of confined fluids, was predicted theoretically and confirmed by existing experimental data and by simulations. The strong attraction to a surface causes adsorbate molecules to attain much higher densities than that of a normal liquid. Under these conditions, adsorbate molecules are so compressed that they repel each other. This phenomenon is discussed in terms of experimental data, results of Monte Carlo simulations, and theoretical models. Lattice version of DFT was developed for modeling phase transitions in adsorbed phase including wetting, capillary condensation, and ordering. Phase behavior of amphiphilic dimers on surfaces and in solutions was modeled using lattice DFT and Monte Carlo simulations. This study resulted in predictive models for adsorption isotherms and for local density distributions in solutions. We have observed a wide variety of phase behavior for amphiphilic dimers, including formation of lamellae and micelles. Block copolymers were modeled in terms of configurational probabilities and in the approximation of random mixing entropy. Probabilities of different orientations for the segments were

  20. Predicting skin permeability from complex chemical mixtures

    International Nuclear Information System (INIS)

    Riviere, Jim E.; Brooks, James D.

    2005-01-01

    Occupational and environmental exposure to topical chemicals is usually in the form of complex chemical mixtures, yet risk assessment is based on experimentally derived data from individual chemical exposures from a single, usually aqueous vehicle, or from computed physiochemical properties. We present an approach using hybrid quantitative structure permeation relationships (QSPeR) models where absorption through porcine skin flow-through diffusion cells is well predicted using a QSPeR model describing the individual penetrants, coupled with a mixture factor (MF) that accounts for physicochemical properties of the vehicle/mixture components. The baseline equation is log k p = c + mMF + aΣα 2 H + bΣβ 2 H + sπ 2 H + rR 2 + vV x where Σα 2 H is the hydrogen-bond donor acidity, Σβ 2 H is the hydrogen-bond acceptor basicity, π 2 H is the dipolarity/polarizability, R 2 represents the excess molar refractivity, and V x is the McGowan volume of the penetrants of interest; c, m, a, b, s, r, and v are strength coefficients coupling these descriptors to skin permeability (k p ) of 12 penetrants (atrazine, chlorpyrifos, ethylparathion, fenthion, methylparathion, nonylphenol, ρ-nitrophenol, pentachlorophenol, phenol, propazine, simazine, and triazine) in 24 mixtures. Mixtures consisted of full factorial combinations of vehicles (water, ethanol, propylene glycol) and additives (sodium lauryl sulfate, methyl nicotinate). An additional set of 4 penetrants (DEET, SDS, permethrin, ricinoleic acid) in different mixtures were included to assess applicability of this approach. This resulted in a dataset of 16 compounds administered in 344 treatment combinations. Across all exposures with no MF, R 2 for absorption was 0.62. With the MF, correlations increased up to 0.78. Parameters correlated to the MF include refractive index, polarizability and log (1/Henry's Law Constant) of the mixture components. These factors should not be considered final as the focus of these studies

  1. Genome-wide prediction and functional validation of promoter motifs regulating gene expression in spore and infection stages of Phytophthora infestans.

    Directory of Open Access Journals (Sweden)

    Sourav Roy

    2013-03-01

    Full Text Available Most eukaryotic pathogens have complex life cycles in which gene expression networks orchestrate the formation of cells specialized for dissemination or host colonization. In the oomycete Phytophthora infestans, the potato late blight pathogen, major shifts in mRNA profiles during developmental transitions were identified using microarrays. We used those data with search algorithms to discover about 100 motifs that are over-represented in promoters of genes up-regulated in hyphae, sporangia, sporangia undergoing zoosporogenesis, swimming zoospores, or germinated cysts forming appressoria (infection structures. Most of the putative stage-specific transcription factor binding sites (TFBSs thus identified had features typical of TFBSs such as position or orientation bias, palindromy, and conservation in related species. Each of six motifs tested in P. infestans transformants using the GUS reporter gene conferred the expected stage-specific expression pattern, and several were shown to bind nuclear proteins in gel-shift assays. Motifs linked to the appressoria-forming stage, including a functionally validated TFBS, were over-represented in promoters of genes encoding effectors and other pathogenesis-related proteins. To understand how promoter and genome architecture influence expression, we also mapped transcription patterns to the P. infestans genome assembly. Adjacent genes were not typically induced in the same stage, including genes transcribed in opposite directions from small intergenic regions, but co-regulated gene pairs occurred more than expected by random chance. These data help illuminate the processes regulating development and pathogenesis, and will enable future attempts to purify the cognate transcription factors.

  2. Genome-wide conserved consensus transcription factor binding motifs are hyper-methylated

    Directory of Open Access Journals (Sweden)

    Down Thomas A

    2010-09-01

    Full Text Available Abstract Background DNA methylation can regulate gene expression by modulating the interaction between DNA and proteins or protein complexes. Conserved consensus motifs exist across the human genome ("predicted transcription factor binding sites": "predicted TFBS" but the large majority of these are proven by chromatin immunoprecipitation and high throughput sequencing (ChIP-seq not to be biological transcription factor binding sites ("empirical TFBS". We hypothesize that DNA methylation at conserved consensus motifs prevents promiscuous or disorderly transcription factor binding. Results Using genome-wide methylation maps of the human heart and sperm, we found that all conserved consensus motifs as well as the subset of those that reside outside CpG islands have an aggregate profile of hyper-methylation. In contrast, empirical TFBS with conserved consensus motifs have a profile of hypo-methylation. 40% of empirical TFBS with conserved consensus motifs resided in CpG islands whereas only 7% of all conserved consensus motifs were in CpG islands. Finally we further identified a minority subset of TF whose profiles are either hypo-methylated or neutral at their respective conserved consensus motifs implicating that these TF may be responsible for establishing or maintaining an un-methylated DNA state, or whose binding is not regulated by DNA methylation. Conclusions Our analysis supports the hypothesis that at least for a subset of TF, empirical binding to conserved consensus motifs genome-wide may be controlled by DNA methylation.

  3. MotifMark: Finding regulatory motifs in DNA sequences.

    Science.gov (United States)

    Hassanzadeh, Hamid Reza; Kolhe, Pushkar; Isbell, Charles L; Wang, May D

    2017-07-01

    The interaction between proteins and DNA is a key driving force in a significant number of biological processes such as transcriptional regulation, repair, recombination, splicing, and DNA modification. The identification of DNA-binding sites and the specificity of target proteins in binding to these regions are two important steps in understanding the mechanisms of these biological activities. A number of high-throughput technologies have recently emerged that try to quantify the affinity between proteins and DNA motifs. Despite their success, these technologies have their own limitations and fall short in precise characterization of motifs, and as a result, require further downstream analysis to extract useful and interpretable information from a haystack of noisy and inaccurate data. Here we propose MotifMark, a new algorithm based on graph theory and machine learning, that can find binding sites on candidate probes and rank their specificity in regard to the underlying transcription factor. We developed a pipeline to analyze experimental data derived from compact universal protein binding microarrays and benchmarked it against two of the most accurate motif search methods. Our results indicate that MotifMark can be a viable alternative technique for prediction of motif from protein binding microarrays and possibly other related high-throughput techniques.

  4. Peptide-binding motif prediction by using phage display library for SasaUBA*0301, a resistance haplotype of MHC class I molecule from Atlantic Salmon (Salmo salar)

    DEFF Research Database (Denmark)

    Zhao, Heng; Hermsen, Trudi; Stet, Rene J M

    2008-01-01

    The structure of the peptide-binding specificity of major histocompatibility complex (MHC) class I has been analyzed extensively in human and mouse. For fish, there are no crystallographic models of MHC molecules, neither are there data on the peptide-binding specificity. In this study, we descri...... and there is a significant association between MHC polymorphism and the disease resistance. Therefore, our study might contribute to designing a peptide vaccine against this viral disease....... class I molecule might have a very similar binding motif at the C-terminus compared with a known mouse class I molecule H2-Kb which has L, or I, V, M at p8. Previous work showed that Atlantic Salmon carrying the allele SasaUBA*0301 are resistant to infectious Salmon aneamia virus...

  5. Synthesis and characterization of dinuclear complexes containing the Fe(III)-F...(H2O)M(II) motif

    DEFF Research Database (Denmark)

    Ghiladi, M; Jensen, K.B.; Jiang, Jianzhong

    1999-01-01

    .818(2), 1.902(2) Å) and one of them is strongly hydrogen bonded to the water molecule on the adjacent Cu atom (F-H...O 2.653(4) Å). The metal ions in the aquafluoride complexes [(bpbp)Fe(F)2M(H2O)2][BF4]2, M=Fe or Co, are weakly antiferromagnetically coupled (J=-8 and -10 cm-1 respectively) and in [(bpbp...

  6. Fitness for synchronization of network motifs

    DEFF Research Database (Denmark)

    Vega, Y.M.; Vázquez-Prada, M.; Pacheco, A.F.

    2004-01-01

    We study the synchronization of Kuramoto's oscillators in small parts of networks known as motifs. We first report on the system dynamics for the case of a scale-free network and show the existence of a non-trivial critical point. We compute the probability that network motifs synchronize, and fi...... that the fitness for synchronization correlates well with motifs interconnectedness and structural complexity. Possible implications for present debates about network evolution in biological and other systems are discussed....

  7. Novel binding motif and new flexibility revealed by structural analyses of a pyruvate dehydrogenase-dihydrolipoyl acetyltransferase subcomplex from the Escherichia coli pyruvate dehydrogenase multienzyme complex.

    Science.gov (United States)

    Arjunan, Palaniappa; Wang, Junjie; Nemeria, Natalia S; Reynolds, Shelley; Brown, Ian; Chandrasekhar, Krishnamoorthy; Calero, Guillermo; Jordan, Frank; Furey, William

    2014-10-24

    The Escherichia coli pyruvate dehydrogenase multienzyme complex contains multiple copies of three enzymatic components, E1p, E2p, and E3, that sequentially carry out distinct steps in the overall reaction converting pyruvate to acetyl-CoA. Efficient functioning requires the enzymatic components to assemble into a large complex, the integrity of which is maintained by tethering of the displaced, peripheral E1p and E3 components to the E2p core through non-covalent binding. We here report the crystal structure of a subcomplex between E1p and an E2p didomain containing a hybrid lipoyl domain along with the peripheral subunit-binding domain responsible for tethering to the core. In the structure, a region at the N terminus of each subunit in the E1p homodimer previously unseen due to crystallographic disorder was observed, revealing a new folding motif involved in E1p-E2p didomain interactions, and an additional, unexpected, flexibility was discovered in the E1p-E2p didomain subcomplex, both of which probably have consequences in the overall multienzyme complex assembly. This represents the first structure of an E1p-E2p didomain subcomplex involving a homodimeric E1p, and the results may be applicable to a large range of complexes with homodimeric E1 components. Results of HD exchange mass spectrometric experiments using the intact, wild type 3-lipoyl E2p and E1p are consistent with the crystallographic data obtained from the E1p-E2p didomain subcomplex as well as with other biochemical and NMR data reported from our groups, confirming that our findings are applicable to the entire E1p-E2p assembly. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

  8. Novel Binding Motif and New Flexibility Revealed by Structural Analyses of a Pyruvate Dehydrogenase-Dihydrolipoyl Acetyltransferase Subcomplex from the Escherichia coli Pyruvate Dehydrogenase Multienzyme Complex*

    Science.gov (United States)

    Arjunan, Palaniappa; Wang, Junjie; Nemeria, Natalia S.; Reynolds, Shelley; Brown, Ian; Chandrasekhar, Krishnamoorthy; Calero, Guillermo; Jordan, Frank; Furey, William

    2014-01-01

    The Escherichia coli pyruvate dehydrogenase multienzyme complex contains multiple copies of three enzymatic components, E1p, E2p, and E3, that sequentially carry out distinct steps in the overall reaction converting pyruvate to acetyl-CoA. Efficient functioning requires the enzymatic components to assemble into a large complex, the integrity of which is maintained by tethering of the displaced, peripheral E1p and E3 components to the E2p core through non-covalent binding. We here report the crystal structure of a subcomplex between E1p and an E2p didomain containing a hybrid lipoyl domain along with the peripheral subunit-binding domain responsible for tethering to the core. In the structure, a region at the N terminus of each subunit in the E1p homodimer previously unseen due to crystallographic disorder was observed, revealing a new folding motif involved in E1p-E2p didomain interactions, and an additional, unexpected, flexibility was discovered in the E1p-E2p didomain subcomplex, both of which probably have consequences in the overall multienzyme complex assembly. This represents the first structure of an E1p-E2p didomain subcomplex involving a homodimeric E1p, and the results may be applicable to a large range of complexes with homodimeric E1 components. Results of HD exchange mass spectrometric experiments using the intact, wild type 3-lipoyl E2p and E1p are consistent with the crystallographic data obtained from the E1p-E2p didomain subcomplex as well as with other biochemical and NMR data reported from our groups, confirming that our findings are applicable to the entire E1p-E2p assembly. PMID:25210042

  9. The Complexity of Developmental Predictions from Dual Process Models

    Science.gov (United States)

    Stanovich, Keith E.; West, Richard F.; Toplak, Maggie E.

    2011-01-01

    Drawing developmental predictions from dual-process theories is more complex than is commonly realized. Overly simplified predictions drawn from such models may lead to premature rejection of the dual process approach as one of many tools for understanding cognitive development. Misleading predictions can be avoided by paying attention to several…

  10. Nonlinear absorbing cationic iridium(III) complexes bearing benzothiazolylfluorene motif on the bipyridine (N∧N) ligand: synthesis, photophysics and reverse saturable absorption.

    Science.gov (United States)

    Li, Yuhao; Dandu, Naveen; Liu, Rui; Hu, Lei; Kilina, Svetlana; Sun, Wenfang

    2013-07-24

    Four new heteroleptic cationic Ir(III) complexes bearing benzothiazolylfluorene motif on the bipyridine (N∧N) (1 and 2) and phenylpyridine (C∧N) (3 and 4) ligands are synthesized and characterized. The influence of the position of the substituent and the extent of π-conjugation on the photophysics of these complexes is systematically investigated by spectroscopic methods and simulated by time-dependent density functional theory (TDDFT). The complexes exhibit ligand-centered (1)π,π* transitions with admixtures of (1)ILCT (π(benzothiazolylfluorene) → π*(bpy)) and (1)MLCT (metal-to-ligand charge transfer) characters below 475 nm, and very weak (1,3)MLCT and (1,3)LLCT (ligand-to-ligand charge transfer) transitions above 475 nm. The emission of these complexes at room temperature in CH2Cl2 solutions is ascribed to be predominantly from the (3)MLCT/(3)LLCT states for 1 and from the (3)π,π* state for 2, while the emitting state of 3 and 4 are assigned to be an admixture of (3)MLCT, (3)LLCT, and (3)π,π* characters. The variations of the photophysical properties of 1-4 are attributed to different degrees of π-conjugation in the bipyridine and phenylpyridine ligands induced by different positions of the benzothiazolylfluorenyl substituents on the bipyridine ligand and different extents of π-conjugation in the phenylpyridine ligands, which alters the energy and lifetime of the lowest singlet and triplet excited states. 1-4 all possess broadband transient absorption (TA) upon nanosecond laser excitation, which extends from the visible to the NIR region. Therefore, 1-4 all exhibit strong reverse saturable absorption (RSA) at 532 nm for ns laser pulses. However, the TA of complexes 1, 2, and 3 are much stronger than that of 4. This feature, combined with the difference in ground-state absorption and triplet excited-state quantum yield, result in the difference in RSA strength, which follows this trend: 1 ≈ 2 ≈ 3 > 4. Therefore, complexes 1-3 are strong

  11. RelB and RelE of Escherichia coli Form a Tight Complex That Represses Transcription via The Ribbon-Helix-Helix Motif in RelB

    DEFF Research Database (Denmark)

    Overgaard, Martin; Borch, Jonas; Gerdes, Kenn

    2009-01-01

    RelB, the Ribbon-Helix-Helix (RHH) repressor encoded by the relBE toxin-antitoxin locus of Escherichia coli, forms a tight complex with RelE and thereby counteracts the mRNA cleavage activity of RelE. In addition, RelB dimers repress the strong relBE promoter and this repression by RelB is enhanced...... by RelE - that is - RelE functions as a transcriptional co-repressor. RelB is a Lon protease substrate and Lon is required both for activation of relBE transcription and for activation of the mRNA cleavage activity of RelE. Here we characterize the molecular interactions important for transcriptional...... motif recognizes four 6 bp repeats within the bipartite binding site. The spacing between each half-site was found to be essential for cooperative interactions between adjacently bound RelB dimers stabilized by the co-repressor RelE. Kinetic and stoichiometric measurements of the interaction between Rel...

  12. The crystal structure of the Split End protein SHARP adds a new layer of complexity to proteins containing RNA recognition motifs.

    Science.gov (United States)

    Arieti, Fabiana; Gabus, Caroline; Tambalo, Margherita; Huet, Tiphaine; Round, Adam; Thore, Stéphane

    2014-06-01

    The Split Ends (SPEN) protein was originally discovered in Drosophila in the late 1990s. Since then, homologous proteins have been identified in eukaryotic species ranging from plants to humans. Every family member contains three predicted RNA recognition motifs (RRMs) in the N-terminal region of the protein. We have determined the crystal structure of the region of the human SPEN homolog that contains these RRMs-the SMRT/HDAC1 Associated Repressor Protein (SHARP), at 2.0 Å resolution. SHARP is a co-regulator of the nuclear receptors. We demonstrate that two of the three RRMs, namely RRM3 and RRM4, interact via a highly conserved interface. Furthermore, we show that the RRM3-RRM4 block is the main platform mediating the stable association with the H12-H13 substructure found in the steroid receptor RNA activator (SRA), a long, non-coding RNA previously shown to play a crucial role in nuclear receptor transcriptional regulation. We determine that SHARP association with SRA relies on both single- and double-stranded RNA sequences. The crystal structure of the SHARP-RRM fragment, together with the associated RNA-binding studies, extend the repertoire of nucleic acid binding properties of RRM domains suggesting a new hypothesis for a better understanding of SPEN protein functions. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  13. Predicting facial characteristics from complex polygenic variations

    DEFF Research Database (Denmark)

    Fagertun, Jens; Wolffhechel, Karin Marie Brandt; Pers, Tune

    2015-01-01

    Research into the importance of the human genome in the context of facial appearance is receiving increasing attention and has led to the detection of several Single Nucleotide Polymorphisms (SNPs) of importance. In this work we attempt a holistic approach predicting facial characteristics from...... genetic principal components across a population of 1,266 individuals. For this we perform a genome-wide association analysis to select a large number of SNPs linked to specific facial traits, recode these to genetic principal components and then use these principal components as predictors for facial...

  14. MotifNet: a web-server for network motif analysis.

    Science.gov (United States)

    Smoly, Ilan Y; Lerman, Eugene; Ziv-Ukelson, Michal; Yeger-Lotem, Esti

    2017-06-15

    Network motifs are small topological patterns that recur in a network significantly more often than expected by chance. Their identification emerged as a powerful approach for uncovering the design principles underlying complex networks. However, available tools for network motif analysis typically require download and execution of computationally intensive software on a local computer. We present MotifNet, the first open-access web-server for network motif analysis. MotifNet allows researchers to analyze integrated networks, where nodes and edges may be labeled, and to search for motifs of up to eight nodes. The output motifs are presented graphically and the user can interactively filter them by their significance, number of instances, node and edge labels, and node identities, and view their instances. MotifNet also allows the user to distinguish between motifs that are centered on specific nodes and motifs that recur in distinct parts of the network. MotifNet is freely available at http://netbio.bgu.ac.il/motifnet . The website was implemented using ReactJs and supports all major browsers. The server interface was implemented in Python with data stored on a MySQL database. estiyl@bgu.ac.il or michaluz@cs.bgu.ac.il. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

  15. Modeling of Complex Life Cycle Prediction Based on Cell Division

    Directory of Open Access Journals (Sweden)

    Fucheng Zhang

    2017-01-01

    Full Text Available Effective fault diagnosis and reasonable life expectancy are of great significance and practical engineering value for the safety, reliability, and maintenance cost of equipment and working environment. At present, the life prediction methods of the equipment are equipment life prediction based on condition monitoring, combined forecasting model, and driven data. Most of them need to be based on a large amount of data to achieve the problem. For this issue, we propose learning from the mechanism of cell division in the organism. We have established a moderate complexity of life prediction model across studying the complex multifactor correlation life model. In this paper, we model the life prediction of cell division. Experiments show that our model can effectively simulate the state of cell division. Through the model of reference, we will use it for the equipment of the complex life prediction.

  16. Motif-independent prediction of a secondary metabolism gene cluster using comparative genomics: application to sequenced genomes of Aspergillus and ten other filamentous fungal species.

    Science.gov (United States)

    Takeda, Itaru; Umemura, Myco; Koike, Hideaki; Asai, Kiyoshi; Machida, Masayuki

    2014-08-01

    Despite their biological importance, a significant number of genes for secondary metabolite biosynthesis (SMB) remain undetected due largely to the fact that they are highly diverse and are not expressed under a variety of cultivation conditions. Several software tools including SMURF and antiSMASH have been developed to predict fungal SMB gene clusters by finding core genes encoding polyketide synthase, nonribosomal peptide synthetase and dimethylallyltryptophan synthase as well as several others typically present in the cluster. In this work, we have devised a novel comparative genomics method to identify SMB gene clusters that is independent of motif information of the known SMB genes. The method detects SMB gene clusters by searching for a similar order of genes and their presence in nonsyntenic blocks. With this method, we were able to identify many known SMB gene clusters with the core genes in the genomic sequences of 10 filamentous fungi. Furthermore, we have also detected SMB gene clusters without core genes, including the kojic acid biosynthesis gene cluster of Aspergillus oryzae. By varying the detection parameters of the method, a significant difference in the sequence characteristics was detected between the genes residing inside the clusters and those outside the clusters. © The Author 2014. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

  17. A Method to Predict the Structure and Stability of RNA/RNA Complexes.

    Science.gov (United States)

    Xu, Xiaojun; Chen, Shi-Jie

    2016-01-01

    RNA/RNA interactions are essential for genomic RNA dimerization and regulation of gene expression. Intermolecular loop-loop base pairing is a widespread and functionally important tertiary structure motif in RNA machinery. However, computational prediction of intermolecular loop-loop base pairing is challenged by the entropy and free energy calculation due to the conformational constraint and the intermolecular interactions. In this chapter, we describe a recently developed statistical mechanics-based method for the prediction of RNA/RNA complex structures and stabilities. The method is based on the virtual bond RNA folding model (Vfold). The main emphasis in the method is placed on the evaluation of the entropy and free energy for the loops, especially tertiary kissing loops. The method also uses recursive partition function calculations and two-step screening algorithm for large, complicated structures of RNA/RNA complexes. As case studies, we use the HIV-1 Mal dimer and the siRNA/HIV-1 mutant (T4) to illustrate the method.

  18. Gradation of complexity and predictability of hydrological processes

    Science.gov (United States)

    Sang, Yan-Fang; Singh, Vijay P.; Wen, Jun; Liu, Changming

    2015-06-01

    Quantification of the complexity and predictability of hydrological systems is important for evaluating the impact of climate change on hydrological processes, and for guiding water activities. In the literature, the focus seems to have been on describing the complexity of spatiotemporal distribution of hydrological variables, but little attention has been paid to the study of complexity gradation, because the degree of absolute complexity of hydrological systems cannot be objectively evaluated. Here we show that complexity and predictability of hydrological processes can be graded into three ranks (low, middle, and high). The gradation is based on the difference in the energy distribution of hydrological series and that of white noise under multitemporal scales. It reflects different energy concentration levels and contents of deterministic components of the hydrological series in the three ranks. Higher energy concentration level reflects lower complexity and higher predictability, but scattered energy distribution being similar to white noise has the highest complexity and is almost unpredictable. We conclude that the three ranks (low, middle, and high) approximately correspond to deterministic, stochastic, and random hydrological systems, respectively. The result of complexity gradation can guide hydrological observations and modeling, and identification of similarity patterns among different hydrological systems.

  19. MSDmotif: exploring protein sites and motifs

    Directory of Open Access Journals (Sweden)

    Henrick Kim

    2008-07-01

    Full Text Available Abstract Background Protein structures have conserved features – motifs, which have a sufficient influence on the protein function. These motifs can be found in sequence as well as in 3D space. Understanding of these fragments is essential for 3D structure prediction, modelling and drug-design. The Protein Data Bank (PDB is the source of this information however present search tools have limited 3D options to integrate protein sequence with its 3D structure. Results We describe here a web application for querying the PDB for ligands, binding sites, small 3D structural and sequence motifs and the underlying database. Novel algorithms for chemical fragments, 3D motifs, ϕ/ψ sequences, super-secondary structure motifs and for small 3D structural motif associations searches are incorporated. The interface provides functionality for visualization, search criteria creation, sequence and 3D multiple alignment options. MSDmotif is an integrated system where a results page is also a search form. A set of motif statistics is available for analysis. This set includes molecule and motif binding statistics, distribution of motif sequences, occurrence of an amino-acid within a motif, correlation of amino-acids side-chain charges within a motif and Ramachandran plots for each residue. The binding statistics are presented in association with properties that include a ligand fragment library. Access is also provided through the distributed Annotation System (DAS protocol. An additional entry point facilitates XML requests with XML responses. Conclusion MSDmotif is unique by combining chemical, sequence and 3D data in a single search engine with a range of search and visualisation options. It provides multiple views of data found in the PDB archive for exploring protein structures.

  20. Motif signatures of transcribed enhancers

    KAUST Repository

    Kleftogiannis, Dimitrios

    2017-09-14

    In mammalian cells, transcribed enhancers (TrEn) play important roles in the initiation of gene expression and maintenance of gene expression levels in spatiotemporal manner. One of the most challenging questions in biology today is how the genomic characteristics of enhancers relate to enhancer activities. This is particularly critical, as several recent studies have linked enhancer sequence motifs to specific functional roles. To date, only a limited number of enhancer sequence characteristics have been investigated, leaving space for exploring the enhancers genomic code in a more systematic way. To address this problem, we developed a novel computational method, TELS, aimed at identifying predictive cell type/tissue specific motif signatures. We used TELS to compile a comprehensive catalog of motif signatures for all known TrEn identified by the FANTOM5 consortium across 112 human primary cells and tissues. Our results confirm that distinct cell type/tissue specific motif signatures characterize TrEn. These signatures allow discriminating successfully a) TrEn from random controls, proxy of non-enhancer activity, and b) cell type/tissue specific TrEn from enhancers expressed and transcribed in different cell types/tissues. TELS codes and datasets are publicly available at http://www.cbrc.kaust.edu.sa/TELS.

  1. Automated classification of RNA 3D motifs and the RNA 3D Motif Atlas

    Science.gov (United States)

    Petrov, Anton I.; Zirbel, Craig L.; Leontis, Neocles B.

    2013-01-01

    The analysis of atomic-resolution RNA three-dimensional (3D) structures reveals that many internal and hairpin loops are modular, recurrent, and structured by conserved non-Watson–Crick base pairs. Structurally similar loops define RNA 3D motifs that are conserved in homologous RNA molecules, but can also occur at nonhomologous sites in diverse RNAs, and which often vary in sequence. To further our understanding of RNA motif structure and sequence variability and to provide a useful resource for structure modeling and prediction, we present a new method for automated classification of internal and hairpin loop RNA 3D motifs and a new online database called the RNA 3D Motif Atlas. To classify the motif instances, a representative set of internal and hairpin loops is automatically extracted from a nonredundant list of RNA-containing PDB files. Their structures are compared geometrically, all-against-all, using the FR3D program suite. The loops are clustered into motif groups, taking into account geometric similarity and structural annotations and making allowance for a variable number of bulged bases. The automated procedure that we have implemented identifies all hairpin and internal loop motifs previously described in the literature. All motif instances and motif groups are assigned unique and stable identifiers and are made available in the RNA 3D Motif Atlas (http://rna.bgsu.edu/motifs), which is automatically updated every four weeks. The RNA 3D Motif Atlas provides an interactive user interface for exploring motif diversity and tools for programmatic data access. PMID:23970545

  2. Predictive hypotheses are ineffectual in resolving complex biochemical systems.

    Science.gov (United States)

    Fry, Michael

    2018-03-20

    Scientific hypotheses may either predict particular unknown facts or accommodate previously-known data. Although affirmed predictions are intuitively more rewarding than accommodations of established facts, opinions divide whether predictive hypotheses are also epistemically superior to accommodation hypotheses. This paper examines the contribution of predictive hypotheses to discoveries of several bio-molecular systems. Having all the necessary elements of the system known beforehand, an abstract predictive hypothesis of semiconservative mode of DNA replication was successfully affirmed. However, in defining the genetic code whose biochemical basis was unclear, hypotheses were only partially effective and supplementary experimentation was required for its conclusive definition. Markedly, hypotheses were entirely inept in predicting workings of complex systems that included unknown elements. Thus, hypotheses did not predict the existence and function of mRNA, the multiple unidentified components of the protein biosynthesis machinery, or the manifold unknown constituents of the ubiquitin-proteasome system of protein breakdown. Consequently, because of their inability to envision unknown entities, predictive hypotheses did not contribute to the elucidation of cation theories remained the sole instrument to explain complex bio-molecular systems, the philosophical question of alleged advantage of predictive over accommodative hypotheses became inconsequential.

  3. Regulation of synaptic inhibition by phospho-dependent binding of the AP2 complex to a YECL motif in the GABAA receptor γ2 subunit

    Science.gov (United States)

    Kittler, Josef T.; Chen, Guojun; Kukhtina, Viktoria; Vahedi-Faridi, Ardeschir; Gu, Zhenglin; Tretter, Verena; Smith, Katharine R.; McAinsh, Kristina; Arancibia-Carcamo, I. Lorena; Saenger, Wolfram; Haucke, Volker; Yan, Zhen; Moss, Stephen J.

    2008-01-01

    The regulation of the number of γ2-subunit-containing GABAA receptors (GABAARs) present at synapses is critical for correct synaptic inhibition and animal behavior. This regulation occurs, in part, by the controlled removal of receptors from the membrane in clathrin-coated vesicles, but it remains unclear how clathrin recruitment to surface γ2-subunit-containing GABAARs is regulated. Here, we identify a γ2-subunit-specific Yxxφ-type-binding motif for the clathrin adaptor protein, AP2, which is located within a site for γ2-subunit tyrosine phosphorylation. Blocking GABAAR-AP2 interactions via this motif increases synaptic responses within minutes. Crystallographic and biochemical studies reveal that phosphorylation of the Yxxφ motif inhibits AP2 binding, leading to increased surface receptor number. In addition, the crystal structure provides an explanation for the high affinity of this motif for AP2 and suggests that γ2-subunit-containing heteromeric GABAARs may be internalized as dimers or multimers. These data define a mechanism for tyrosine kinase regulation of GABAAR surface levels and synaptic inhibition. PMID:18305175

  4. Regulation of synaptic inhibition by phospho-dependent binding of the AP2 complex to a YECL motif in the GABAA receptor gamma2 subunit.

    Science.gov (United States)

    Kittler, Josef T; Chen, Guojun; Kukhtina, Viktoria; Vahedi-Faridi, Ardeschir; Gu, Zhenglin; Tretter, Verena; Smith, Katharine R; McAinsh, Kristina; Arancibia-Carcamo, I Lorena; Saenger, Wolfram; Haucke, Volker; Yan, Zhen; Moss, Stephen J

    2008-03-04

    The regulation of the number of gamma2-subunit-containing GABA(A) receptors (GABA(A)Rs) present at synapses is critical for correct synaptic inhibition and animal behavior. This regulation occurs, in part, by the controlled removal of receptors from the membrane in clathrin-coated vesicles, but it remains unclear how clathrin recruitment to surface gamma2-subunit-containing GABA(A)Rs is regulated. Here, we identify a gamma2-subunit-specific Yxxvarphi-type-binding motif for the clathrin adaptor protein, AP2, which is located within a site for gamma2-subunit tyrosine phosphorylation. Blocking GABA(A)R-AP2 interactions via this motif increases synaptic responses within minutes. Crystallographic and biochemical studies reveal that phosphorylation of the Yxxvarphi motif inhibits AP2 binding, leading to increased surface receptor number. In addition, the crystal structure provides an explanation for the high affinity of this motif for AP2 and suggests that gamma2-subunit-containing heteromeric GABA(A)Rs may be internalized as dimers or multimers. These data define a mechanism for tyrosine kinase regulation of GABA(A)R surface levels and synaptic inhibition.

  5. Interaction of Cu+ with cytosine and formation of i-motif-like C-M+-C complexes: alkali versus coinage metals

    NARCIS (Netherlands)

    Gao, J.; Berden, G.; Rodgers, M.T.; Oomens, J.

    2016-01-01

    The Watson-Crick structure of DNA is among the most well-known molecular structures of our time. However, alternative base-pairing motifs are also known to occur, often depending on base sequence, pH, or the presence of cations. Pairing of cytosine (C) bases induced by the sharing of a single proton

  6. Protein complex prediction via dense subgraphs and false positive analysis.

    Directory of Open Access Journals (Sweden)

    Cecilia Hernandez

    Full Text Available Many proteins work together with others in groups called complexes in order to achieve a specific function. Discovering protein complexes is important for understanding biological processes and predict protein functions in living organisms. Large-scale and throughput techniques have made possible to compile protein-protein interaction networks (PPI networks, which have been used in several computational approaches for detecting protein complexes. Those predictions might guide future biologic experimental research. Some approaches are topology-based, where highly connected proteins are predicted to be complexes; some propose different clustering algorithms using partitioning, overlaps among clusters for networks modeled with unweighted or weighted graphs; and others use density of clusters and information based on protein functionality. However, some schemes still require much processing time or the quality of their results can be improved. Furthermore, most of the results obtained with computational tools are not accompanied by an analysis of false positives. We propose an effective and efficient mining algorithm for discovering highly connected subgraphs, which is our base for defining protein complexes. Our representation is based on transforming the PPI network into a directed acyclic graph that reduces the number of represented edges and the search space for discovering subgraphs. Our approach considers weighted and unweighted PPI networks. We compare our best alternative using PPI networks from Saccharomyces cerevisiae (yeast and Homo sapiens (human with state-of-the-art approaches in terms of clustering, biological metrics and execution times, as well as three gold standards for yeast and two for human. Furthermore, we analyze false positive predicted complexes searching the PDBe (Protein Data Bank in Europe database in order to identify matching protein complexes that have been purified and structurally characterized. Our analysis shows

  7. Construction of ontology augmented networks for protein complex prediction.

    Science.gov (United States)

    Zhang, Yijia; Lin, Hongfei; Yang, Zhihao; Wang, Jian

    2013-01-01

    Protein complexes are of great importance in understanding the principles of cellular organization and function. The increase in available protein-protein interaction data, gene ontology and other resources make it possible to develop computational methods for protein complex prediction. Most existing methods focus mainly on the topological structure of protein-protein interaction networks, and largely ignore the gene ontology annotation information. In this article, we constructed ontology augmented networks with protein-protein interaction data and gene ontology, which effectively unified the topological structure of protein-protein interaction networks and the similarity of gene ontology annotations into unified distance measures. After constructing ontology augmented networks, a novel method (clustering based on ontology augmented networks) was proposed to predict protein complexes, which was capable of taking into account the topological structure of the protein-protein interaction network, as well as the similarity of gene ontology annotations. Our method was applied to two different yeast protein-protein interaction datasets and predicted many well-known complexes. The experimental results showed that (i) ontology augmented networks and the unified distance measure can effectively combine the structure closeness and gene ontology annotation similarity; (ii) our method is valuable in predicting protein complexes and has higher F1 and accuracy compared to other competing methods.

  8. Predicting beauty: fractal dimension and visual complexity in art.

    Science.gov (United States)

    Forsythe, A; Nadal, M; Sheehy, N; Cela-Conde, C J; Sawey, M

    2011-02-01

    Visual complexity has been known to be a significant predictor of preference for artistic works for some time. The first study reported here examines the extent to which perceived visual complexity in art can be successfully predicted using automated measures of complexity. Contrary to previous findings the most successful predictor of visual complexity was Gif compression. The second study examined the extent to which fractal dimension could account for judgments of perceived beauty. The fractal dimension measure accounts for more of the variance in judgments of perceived beauty in visual art than measures of visual complexity alone, particularly for abstract and natural images. Results also suggest that when colour is removed from an artistic image observers are unable to make meaningful judgments as to its beauty. ©2010 The British Psychological Society.

  9. Quantum chemical prediction of antennae structures in lanthanide complexes

    International Nuclear Information System (INIS)

    Ottonelli, M.; Musso, G.F.; Rizzo, F.; Dellepiane, G.; Porzio, W.; Destri, S.

    2008-01-01

    In this paper the quantum chemical semiempirical procedure recently proposed by us to predict ground- and excited-state geometries of lanthanide complexes, the pseudo coordination centre method (PCC), is preliminarily compared with the semiempirical sparkle model for the calculation of lanthanide complexes (SMLC). Contrary to the SMLC method, where the rare-earth ion is replaced by a reparameterized sparkle atom, in our approach we replace it with a metal ion which is already present in the chosen semiempirical parameterization. This implies that in the optimization of the geometry of the complexes a different weight is implicitly given to the complex region including the rare-earth ion and its neighbour atoms with respect to the region of the ligands aggregate. As a consequence our approach is expected to reproduce better than the SMLC one the geometry of the ligands aggregate embedded in the complex, while the contrary happens for the coordination distances

  10. Multiple TPR motifs characterize the Fanconi anemia FANCG protein.

    Science.gov (United States)

    Blom, Eric; van de Vrugt, Henri J; de Vries, Yne; de Winter, Johan P; Arwert, Fré; Joenje, Hans

    2004-01-05

    The genome protection pathway that is defective in patients with Fanconi anemia (FA) is controlled by at least eight genes, including BRCA2. A key step in the pathway involves the monoubiquitylation of FANCD2, which critically depends on a multi-subunit nuclear 'core complex' of at least six FANC proteins (FANCA, -C, -E, -F, -G, and -L). Except for FANCL, which has WD40 repeats and a RING finger domain, no significant domain structure has so far been recognized in any of the core complex proteins. By using a homology search strategy comparing the human FANCG protein sequence with its ortholog sequences in Oryzias latipes (Japanese rice fish) and Danio rerio (zebrafish) we identified at least seven tetratricopeptide repeat motifs (TPRs) covering a major part of this protein. TPRs are degenerate 34-amino acid repeat motifs which function as scaffolds mediating protein-protein interactions, often found in multiprotein complexes. In four out of five TPR motifs tested (TPR1, -2, -5, and -6), targeted missense mutagenesis disrupting the motifs at the critical position 8 of each TPR caused complete or partial loss of FANCG function. Loss of function was evident from failure of the mutant proteins to complement the cellular FA phenotype in FA-G lymphoblasts, which was correlated with loss of binding to FANCA. Although the TPR4 mutant fully complemented the cells, it showed a reduced interaction with FANCA, suggesting that this TPR may also be of functional importance. The recognition of FANCG as a typical TPR protein predicts this protein to play a key role in the assembly and/or stabilization of the nuclear FA protein core complex.

  11. Complex versus simple models: ion-channel cardiac toxicity prediction.

    Science.gov (United States)

    Mistry, Hitesh B

    2018-01-01

    There is growing interest in applying detailed mathematical models of the heart for ion-channel related cardiac toxicity prediction. However, a debate as to whether such complex models are required exists. Here an assessment in the predictive performance between two established large-scale biophysical cardiac models and a simple linear model B net was conducted. Three ion-channel data-sets were extracted from literature. Each compound was designated a cardiac risk category using two different classification schemes based on information within CredibleMeds. The predictive performance of each model within each data-set for each classification scheme was assessed via a leave-one-out cross validation. Overall the B net model performed equally as well as the leading cardiac models in two of the data-sets and outperformed both cardiac models on the latest. These results highlight the importance of benchmarking complex versus simple models but also encourage the development of simple models.

  12. Complex versus simple models: ion-channel cardiac toxicity prediction

    Directory of Open Access Journals (Sweden)

    Hitesh B. Mistry

    2018-02-01

    Full Text Available There is growing interest in applying detailed mathematical models of the heart for ion-channel related cardiac toxicity prediction. However, a debate as to whether such complex models are required exists. Here an assessment in the predictive performance between two established large-scale biophysical cardiac models and a simple linear model Bnet was conducted. Three ion-channel data-sets were extracted from literature. Each compound was designated a cardiac risk category using two different classification schemes based on information within CredibleMeds. The predictive performance of each model within each data-set for each classification scheme was assessed via a leave-one-out cross validation. Overall the Bnet model performed equally as well as the leading cardiac models in two of the data-sets and outperformed both cardiac models on the latest. These results highlight the importance of benchmarking complex versus simple models but also encourage the development of simple models.

  13. Complex behaviour and predictability of the European dry spell regimes

    Directory of Open Access Journals (Sweden)

    X. Lana

    2010-09-01

    Full Text Available The complex spatial and temporal characteristics of European dry spell lengths, DSL, (sequences of consecutive days with rainfall amount below a certain threshold and their randomness and predictive instability are analysed from daily pluviometric series recorded at 267 rain gauges along the second half of the 20th century. DSL are obtained by considering four thresholds, R0, of 0.1, 1.0, 5.0 and 10.0 mm/day. A proper quantification of the complexity, randomness and predictive instability of the different DSL regimes in Europe is achieved on the basis of fractal analyses and dynamic system theory, including the reconstruction theorem. First, the concept of lacunarity is applied to the series of daily rainfall, and the lacunarity curves are well fitted to Cantor and random Cantor sets. Second, the rescaled analysis reveals that randomness, persistence and anti-persistence are present on the European DSL series. Third, the complexity of the physical process governing the DSL series is quantified by the minimum number of nonlinear equations determined by the correlation dimension. And fourth, the loss of memory of the physical process, which is one of the reasons for the complex predictability, is characterized by the values of the Kolmogorov entropy, and the predictive instability is directly associated with positive Lyapunov exponents. In this way, new bases for a better prediction of DSLs in Europe, sometimes leading to drought episodes, are established. Concretely, three predictive strategies are proposed in Sect. 5. It is worth mentioning that the spatial distribution of all fractal parameters does not solely depend on latitude and longitude but also reflects the effects of orography, continental climate or vicinity to the Atlantic and Arctic Oceans and Mediterranean Sea.

  14. Large-scale discovery of promoter motifs in Drosophila melanogaster.

    Directory of Open Access Journals (Sweden)

    Thomas A Down

    2007-01-01

    Full Text Available A key step in understanding gene regulation is to identify the repertoire of transcription factor binding motifs (TFBMs that form the building blocks of promoters and other regulatory elements. Identifying these experimentally is very laborious, and the number of TFBMs discovered remains relatively small, especially when compared with the hundreds of transcription factor genes predicted in metazoan genomes. We have used a recently developed statistical motif discovery approach, NestedMICA, to detect candidate TFBMs from a large set of Drosophila melanogaster promoter regions. Of the 120 motifs inferred in our initial analysis, 25 were statistically significant matches to previously reported motifs, while 87 appeared to be novel. Analysis of sequence conservation and motif positioning suggested that the great majority of these discovered motifs are predictive of functional elements in the genome. Many motifs showed associations with specific patterns of gene expression in the D. melanogaster embryo, and we were able to obtain confident annotation of expression patterns for 25 of our motifs, including eight of the novel motifs. The motifs are available through Tiffin, a new database of DNA sequence motifs. We have discovered many new motifs that are overrepresented in D. melanogaster promoter regions, and offer several independent lines of evidence that these are novel TFBMs. Our motif dictionary provides a solid foundation for further investigation of regulatory elements in Drosophila, and demonstrates techniques that should be applicable in other species. We suggest that further improvements in computational motif discovery should narrow the gap between the set of known motifs and the total number of transcription factors in metazoan genomes.

  15. Predicting extreme rainfall over eastern Asia by using complex networks

    International Nuclear Information System (INIS)

    He Su-Hong; Gong Yan-Chun; Huang Yan-Hua; Wu Cheng-Guo; Feng Tai-Chen; Gong Zhi-Qiang

    2014-01-01

    A climate network of extreme rainfall over eastern Asia is constructed for the period of 1971–2000, employing the tools of complex networks and a measure of nonlinear correlation called event synchronization (ES). Using this network, we predict the extreme rainfall for several cases without delay and with n-day delay (1 ≤ n ≤ 10). The prediction accuracy can reach 58% without delay, 21% with 1-day delay, and 12% with n-day delay (2 ≤ n ≤ 10). The results reveal that the prediction accuracy is low in years of a weak east Asia summer monsoon (EASM) or 1 year later and high in years of a strong EASM or 1 year later. Furthermore, the prediction accuracy is higher due to the many more links that represent correlations between different grid points and a higher extreme rainfall rate during strong EASM years. (geophysics, astronomy, and astrophysics)

  16. Discovery and validation of information theory-based transcription factor and cofactor binding site motifs.

    Science.gov (United States)

    Lu, Ruipeng; Mucaki, Eliseos J; Rogan, Peter K

    2017-03-17

    Data from ChIP-seq experiments can derive the genome-wide binding specificities of transcription factors (TFs) and other regulatory proteins. We analyzed 765 ENCODE ChIP-seq peak datasets of 207 human TFs with a novel motif discovery pipeline based on recursive, thresholded entropy minimization. This approach, while obviating the need to compensate for skewed nucleotide composition, distinguishes true binding motifs from noise, quantifies the strengths of individual binding sites based on computed affinity and detects adjacent cofactor binding sites that coordinate with the targets of primary, immunoprecipitated TFs. We obtained contiguous and bipartite information theory-based position weight matrices (iPWMs) for 93 sequence-specific TFs, discovered 23 cofactor motifs for 127 TFs and revealed six high-confidence novel motifs. The reliability and accuracy of these iPWMs were determined via four independent validation methods, including the detection of experimentally proven binding sites, explanation of effects of characterized SNPs, comparison with previously published motifs and statistical analyses. We also predict previously unreported TF coregulatory interactions (e.g. TF complexes). These iPWMs constitute a powerful tool for predicting the effects of sequence variants in known binding sites, performing mutation analysis on regulatory SNPs and predicting previously unrecognized binding sites and target genes. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  17. Which clustering algorithm is better for predicting protein complexes?

    Directory of Open Access Journals (Sweden)

    Moschopoulos Charalampos N

    2011-12-01

    Full Text Available Abstract Background Protein-Protein interactions (PPI play a key role in determining the outcome of most cellular processes. The correct identification and characterization of protein interactions and the networks, which they comprise, is critical for understanding the molecular mechanisms within the cell. Large-scale techniques such as pull down assays and tandem affinity purification are used in order to detect protein interactions in an organism. Today, relatively new high-throughput methods like yeast two hybrid, mass spectrometry, microarrays, and phage display are also used to reveal protein interaction networks. Results In this paper we evaluated four different clustering algorithms using six different interaction datasets. We parameterized the MCL, Spectral, RNSC and Affinity Propagation algorithms and applied them to six PPI datasets produced experimentally by Yeast 2 Hybrid (Y2H and Tandem Affinity Purification (TAP methods. The predicted clusters, so called protein complexes, were then compared and benchmarked with already known complexes stored in published databases. Conclusions While results may differ upon parameterization, the MCL and RNSC algorithms seem to be more promising and more accurate at predicting PPI complexes. Moreover, they predict more complexes than other reviewed algorithms in absolute numbers. On the other hand the spectral clustering algorithm achieves the highest valid prediction rate in our experiments. However, it is nearly always outperformed by both RNSC and MCL in terms of the geometrical accuracy while it generates the fewest valid clusters than any other reviewed algorithm. This article demonstrates various metrics to evaluate the accuracy of such predictions as they are presented in the text below. Supplementary material can be found at: http://www.bioacademy.gr/bioinformatics/projects/ppireview.htm

  18. An efficient link prediction index for complex military organization

    Science.gov (United States)

    Fan, Changjun; Liu, Zhong; Lu, Xin; Xiu, Baoxin; Chen, Qing

    2017-03-01

    Quality of information is crucial for decision-makers to judge the battlefield situations and design the best operation plans, however, real intelligence data are often incomplete and noisy, where missing links prediction methods and spurious links identification algorithms can be applied, if modeling the complex military organization as the complex network where nodes represent functional units and edges denote communication links. Traditional link prediction methods usually work well on homogeneous networks, but few for the heterogeneous ones. And the military network is a typical heterogeneous network, where there are different types of nodes and edges. In this paper, we proposed a combined link prediction index considering both the nodes' types effects and nodes' structural similarities, and demonstrated that it is remarkably superior to all the 25 existing similarity-based methods both in predicting missing links and identifying spurious links in a real military network data; we also investigated the algorithms' robustness under noisy environment, and found the mistaken information is more misleading than incomplete information in military areas, which is different from that in recommendation systems, and our method maintained the best performance under the condition of small noise. Since the real military network intelligence must be carefully checked at first due to its significance, and link prediction methods are just adopted to purify the network with the left latent noise, the method proposed here is applicable in real situations. In the end, as the FINC-E model, here used to describe the complex military organizations, is also suitable to many other social organizations, such as criminal networks, business organizations, etc., thus our method has its prospects in these areas for many tasks, like detecting the underground relationships between terrorists, predicting the potential business markets for decision-makers, and so on.

  19. Centrality Robustness and Link Prediction in Complex Social Networks

    DEFF Research Database (Denmark)

    Davidsen, Søren Atmakuri; Ortiz-Arroyo, Daniel

    2012-01-01

    . Secondly, we present a method to predict edges in dynamic social networks. Our experimental results indicate that the robustness of the centrality measures applied to more realistic social networks follows a predictable pattern and that the use of temporal statistics could improve the accuracy achieved......This chapter addresses two important issues in social network analysis that involve uncertainty. Firstly, we present am analysis on the robustness of centrality measures that extend the work presented in Borgati et al. using three types of complex network structures and one real social network...

  20. Interaction of Cu(+) with cytosine and formation of i-motif-like C-M(+)-C complexes: alkali versus coinage metals.

    Science.gov (United States)

    Gao, Juehan; Berden, Giel; Rodgers, M T; Oomens, Jos

    2016-03-14

    The Watson-Crick structure of DNA is among the most well-known molecular structures of our time. However, alternative base-pairing motifs are also known to occur, often depending on base sequence, pH, or the presence of cations. Pairing of cytosine (C) bases induced by the sharing of a single proton (C-H(+)-C) may give rise to the so-called i-motif, which occurs primarily in expanded trinucleotide repeats and the telomeric region of DNA, particularly at low pH. At physiological pH, silver cations were recently found to stabilize C dimers in a C-Ag(+)-C structure analogous to the hemiprotonated C-dimer. Here we use infrared ion spectroscopy in combination with density functional theory calculations at the B3LYP/6-311G+(2df,2p) level to show that copper in the 1+ oxidation state induces an analogous formation of C-Cu(+)-C structures. In contrast to protons and these transition metal ions, alkali metal ions induce a different dimer structure, where each ligand coordinates the alkali metal ion in a bidentate fashion in which the N3 and O2 atoms of both cytosine ligands coordinate to the metal ion, sacrificing hydrogen-bonding interactions between the ligands for improved chelation of the metal cation.

  1. Nostradamus 2014 prediction, modeling and analysis of complex systems

    CERN Document Server

    Suganthan, Ponnuthurai; Chen, Guanrong; Snasel, Vaclav; Abraham, Ajith; Rössler, Otto

    2014-01-01

    The prediction of behavior of complex systems, analysis and modeling of its structure is a vitally important problem in engineering, economy and generally in science today. Examples of such systems can be seen in the world around us (including our bodies) and of course in almost every scientific discipline including such “exotic” domains as the earth’s atmosphere, turbulent fluids, economics (exchange rate and stock markets), population growth, physics (control of plasma), information flow in social networks and its dynamics, chemistry and complex networks. To understand such complex dynamics, which often exhibit strange behavior, and to use it in research or industrial applications, it is paramount to create its models. For this purpose there exists a rich spectrum of methods, from classical such as ARMA models or Box Jenkins method to modern ones like evolutionary computation, neural networks, fuzzy logic, geometry, deterministic chaos amongst others. This proceedings book is a collection of accepted ...

  2. Predictability, Force and (Anti-)Resonance in Complex Object Control.

    Science.gov (United States)

    Maurice, Pauline; Hogan, Neville; Sternad, Dagmar

    2018-04-18

    Manipulation of complex objects as in tool use is ubiquitous and has given humans an evolutionary advantage. This study examined the strategies humans choose when manipulating an object with underactuated internal dynamics, such as a cup of coffee. The object's dynamics renders the temporal evolution complex, possibly even chaotic, and difficult to predict. A cart-and-pendulum model, loosely mimicking coffee sloshing in a cup, was implemented in a virtual environment with a haptic interface. Participants rhythmically manipulated the virtual cup containing a rolling ball; they could choose the oscillation frequency, while the amplitude was prescribed. Three hypotheses were tested: 1) humans decrease interaction forces between hand and object; 2) humans increase the predictability of the object dynamics; 3) humans exploit the resonances of the coupled object-hand system. Analysis revealed that humans chose either a high-frequency strategy with anti-phase cup-and-ball movements or a low-frequency strategy with in-phase cup-and-ball movements. Counter Hypothesis 1, they did not decrease interaction force; instead, they increased the predictability of the interaction dynamics, quantified by mutual information, supporting Hypothesis 2. To address Hypothesis 3, frequency analysis of the coupled hand-object system revealed two resonance frequencies separated by an anti-resonance frequency. The low-frequency strategy exploited one resonance, while the high-frequency strategy afforded more choice, consistent with the frequency response of the coupled system; both strategies avoided the anti-resonance. Hence, humans did not prioritize interaction force, but rather strategies that rendered interactions predictable. These findings highlight that physical interactions with complex objects pose control challenges not present in unconstrained movements.

  3. Mathematical approaches for complexity/predictivity trade-offs in complex system models : LDRD final report.

    Energy Technology Data Exchange (ETDEWEB)

    Goldsby, Michael E.; Mayo, Jackson R.; Bhattacharyya, Arnab (Massachusetts Institute of Technology, Cambridge, MA); Armstrong, Robert C.; Vanderveen, Keith

    2008-09-01

    The goal of this research was to examine foundational methods, both computational and theoretical, that can improve the veracity of entity-based complex system models and increase confidence in their predictions for emergent behavior. The strategy was to seek insight and guidance from simplified yet realistic models, such as cellular automata and Boolean networks, whose properties can be generalized to production entity-based simulations. We have explored the usefulness of renormalization-group methods for finding reduced models of such idealized complex systems. We have prototyped representative models that are both tractable and relevant to Sandia mission applications, and quantified the effect of computational renormalization on the predictive accuracy of these models, finding good predictivity from renormalized versions of cellular automata and Boolean networks. Furthermore, we have theoretically analyzed the robustness properties of certain Boolean networks, relevant for characterizing organic behavior, and obtained precise mathematical constraints on systems that are robust to failures. In combination, our results provide important guidance for more rigorous construction of entity-based models, which currently are often devised in an ad-hoc manner. Our results can also help in designing complex systems with the goal of predictable behavior, e.g., for cybersecurity.

  4. Several tetratricopeptide repeat (TPR) motifs of FANCG are required for assembly of the BRCA2/D1-D2-G-X3 complex, FANCD2 monoubiquitylation and phleomycin resistance

    International Nuclear Information System (INIS)

    Wilson, James B.; Blom, Eric; Cunningham, Ryan; Xiao, Yuxuan; Kupfer, Gary M.; Jones, Nigel J.

    2010-01-01

    The Fanconi anaemia (FA) FANCG protein is an integral component of the FA nuclear core complex that is required for monoubiquitylation of FANCD2. FANCG is also part of another protein complex termed D1-D2-G-X3 that contains FANCD2 and the homologous recombination repair proteins BRCA2 (FANCD1) and XRCC3. Formation of the D1-D2-G-X3 complex is mediated by serine-7 phosphorylation of FANCG and occurs independently of the FA core complex and FANCD2 monoubiquitylation. FANCG contains seven tetratricopeptide repeat (TPR) motifs that mediate protein-protein interactions and here we show that mutation of several of the TPR motifs at a conserved consensus residue ablates the in vivo binding activity of FANCG. Expression of mutated TPR1, TPR2, TPR5 and TPR6 in Chinese hamster fancg mutant NM3 fails to functionally complement its hypersensitivities to mitomycin C (MMC) and phleomycin and fails to restore FANCD2 monoubiquitylation. Using co-immunoprecipitation analysis, we demonstrate that these TPR-mutated FANCG proteins fail to interact with BRCA2, XRCC3, FANCA or FANCF. The interactions of other proteins in the D1-D2-G-X3 complex are also absent, including the interaction of BRCA2 with both the monoubiquitylated (FANCD2-L) and non-ubiquitylated (FANCD2-S) isoforms of FANCD2. Interestingly, a mutation of TPR7 (R563E), that complements the MMC and phleomycin hypersensitivity of human FA-G EUFA316 cells, fails to complement NM3, despite the mutated FANCG protein co-precipitating with FANCA, BRCA2 and XRCC3. Whilst interaction of TPR7-mutated FANCG with FANCF does appear to be reduced in NM3, FANCD2 is monoubiquitylated suggesting that sub-optimal interactions of FANCG in the core complex and the D1-D2-G-X3 complex are responsible for the observed MMC- and phleomycin-hypersensitivity, rather than a defect in FANCD2 monoubiquitylation. Our data demonstrate that FANCG functions as a mediator of protein-protein interactions and is vital for the assembly of multi-protein complexes

  5. Several tetratricopeptide repeat (TPR) motifs of FANCG are required for assembly of the BRCA2/D1-D2-G-X3 complex, FANCD2 monoubiquitylation and phleomycin resistance

    Energy Technology Data Exchange (ETDEWEB)

    Wilson, James B. [Molecular Oncology and Stem Cell Research Group, School of Biological Sciences, University of Liverpool, Biosciences Building, Crown Street, Liverpool L69 7ZB (United Kingdom); Blom, Eric [Department of Clinical Genetics and Human Genetics, VU University Medical Center, Van der Boechorststraat 7, NL-1081 BT Amsterdam (Netherlands); Cunningham, Ryan; Xiao, Yuxuan [Molecular Oncology and Stem Cell Research Group, School of Biological Sciences, University of Liverpool, Biosciences Building, Crown Street, Liverpool L69 7ZB (United Kingdom); Kupfer, Gary M. [Departments of Pediatrics and Pathology, Yale University School of Medicine, Section of Hematology/Oncology, 333 Cedar Street, New Haven, CT 0652 (United States); Jones, Nigel J., E-mail: njjones@liv.ac.uk [Molecular Oncology and Stem Cell Research Group, School of Biological Sciences, University of Liverpool, Biosciences Building, Crown Street, Liverpool L69 7ZB (United Kingdom)

    2010-07-07

    The Fanconi anaemia (FA) FANCG protein is an integral component of the FA nuclear core complex that is required for monoubiquitylation of FANCD2. FANCG is also part of another protein complex termed D1-D2-G-X3 that contains FANCD2 and the homologous recombination repair proteins BRCA2 (FANCD1) and XRCC3. Formation of the D1-D2-G-X3 complex is mediated by serine-7 phosphorylation of FANCG and occurs independently of the FA core complex and FANCD2 monoubiquitylation. FANCG contains seven tetratricopeptide repeat (TPR) motifs that mediate protein-protein interactions and here we show that mutation of several of the TPR motifs at a conserved consensus residue ablates the in vivo binding activity of FANCG. Expression of mutated TPR1, TPR2, TPR5 and TPR6 in Chinese hamster fancg mutant NM3 fails to functionally complement its hypersensitivities to mitomycin C (MMC) and phleomycin and fails to restore FANCD2 monoubiquitylation. Using co-immunoprecipitation analysis, we demonstrate that these TPR-mutated FANCG proteins fail to interact with BRCA2, XRCC3, FANCA or FANCF. The interactions of other proteins in the D1-D2-G-X3 complex are also absent, including the interaction of BRCA2 with both the monoubiquitylated (FANCD2-L) and non-ubiquitylated (FANCD2-S) isoforms of FANCD2. Interestingly, a mutation of TPR7 (R563E), that complements the MMC and phleomycin hypersensitivity of human FA-G EUFA316 cells, fails to complement NM3, despite the mutated FANCG protein co-precipitating with FANCA, BRCA2 and XRCC3. Whilst interaction of TPR7-mutated FANCG with FANCF does appear to be reduced in NM3, FANCD2 is monoubiquitylated suggesting that sub-optimal interactions of FANCG in the core complex and the D1-D2-G-X3 complex are responsible for the observed MMC- and phleomycin-hypersensitivity, rather than a defect in FANCD2 monoubiquitylation. Our data demonstrate that FANCG functions as a mediator of protein-protein interactions and is vital for the assembly of multi-protein complexes

  6. Predicting Eye Fixations on Complex Visual Stimuli Using Local Symmetry.

    Science.gov (United States)

    Kootstra, Gert; de Boer, Bart; Schomaker, Lambert R B

    2011-03-01

    Most bottom-up models that predict human eye fixations are based on contrast features. The saliency model of Itti, Koch and Niebur is an example of such contrast-saliency models. Although the model has been successfully compared to human eye fixations, we show that it lacks preciseness in the prediction of fixations on mirror-symmetrical forms. The contrast model gives high response at the borders, whereas human observers consistently look at the symmetrical center of these forms. We propose a saliency model that predicts eye fixations using local mirror symmetry. To test the model, we performed an eye-tracking experiment with participants viewing complex photographic images and compared the data with our symmetry model and the contrast model. The results show that our symmetry model predicts human eye fixations significantly better on a wide variety of images including many that are not selected for their symmetrical content. Moreover, our results show that especially early fixations are on highly symmetrical areas of the images. We conclude that symmetry is a strong predictor of human eye fixations and that it can be used as a predictor of the order of fixation.

  7. [Personal motif in art].

    Science.gov (United States)

    Gerevich, József

    2015-01-01

    One of the basic questions of the art psychology is whether a personal motif is to be found behind works of art and if so, how openly or indirectly it appears in the work itself. Analysis of examples and documents from the fine arts and literature allow us to conclude that the personal motif that can be identified by the viewer through symbols, at times easily at others with more difficulty, gives an emotional plus to the artistic product. The personal motif may be found in traumatic experiences, in communication to the model or with other emotionally important persons (mourning, disappointment, revenge, hatred, rivalry, revolt etc.), in self-searching, or self-analysis. The emotions are expressed in artistic activity either directly or indirectly. The intention nourished by the artist's identity (Kunstwollen) may stand in the way of spontaneous self-expression, channelling it into hidden paths. Under the influence of certain circumstances, the artist may arouse in the viewer, consciously or unconsciously, an illusionary, misleading image of himself. An examination of the personal motif is one of the important research areas of art therapy.

  8. Predicting EEG complexity from sleep macro and microstructure

    International Nuclear Information System (INIS)

    Chouvarda, I; Maglaveras, N; Mendez, M O; Rosso, V; Parrino, L; Grassi, A; Terzano, M; Bianchi, A M; Cerutti, S

    2011-01-01

    This work investigates the relation between the complexity of electroencephalography (EEG) signal, as measured by fractal dimension (FD), and normal sleep structure in terms of its macrostructure and microstructure. Sleep features are defined, encoding sleep stage and cyclic alternating pattern (CAP) related information, both in short and long term. The relevance of each sleep feature to the EEG FD is investigated, and the most informative ones are depicted. In order to quantitatively assess the relation between sleep characteristics and EEG dynamics, a modeling approach is proposed which employs subsets of the sleep macrostructure and microstructure features as input variables and predicts EEG FD based on these features of sleep micro/macrostructure. Different sleep feature sets are investigated along with linear and nonlinear models. Findings suggest that the EEG FD time series is best predicted by a nonlinear support vector machine (SVM) model, employing both sleep stage/transitions and CAP features at different time scales depending on the EEG activation subtype. This combination of features suggests that short-term and long-term history of macro and micro sleep events interact in a complex manner toward generating the dynamics of sleep

  9. RMOD: a tool for regulatory motif detection in signaling network.

    Directory of Open Access Journals (Sweden)

    Jinki Kim

    Full Text Available Regulatory motifs are patterns of activation and inhibition that appear repeatedly in various signaling networks and that show specific regulatory properties. However, the network structures of regulatory motifs are highly diverse and complex, rendering their identification difficult. Here, we present a RMOD, a web-based system for the identification of regulatory motifs and their properties in signaling networks. RMOD finds various network structures of regulatory motifs by compressing the signaling network and detecting the compressed forms of regulatory motifs. To apply it into a large-scale signaling network, it adopts a new subgraph search algorithm using a novel data structure called path-tree, which is a tree structure composed of isomorphic graphs of query regulatory motifs. This algorithm was evaluated using various sizes of signaling networks generated from the integration of various human signaling pathways and it showed that the speed and scalability of this algorithm outperforms those of other algorithms. RMOD includes interactive analysis and auxiliary tools that make it possible to manipulate the whole processes from building signaling network and query regulatory motifs to analyzing regulatory motifs with graphical illustration and summarized descriptions. As a result, RMOD provides an integrated view of the regulatory motifs and mechanism underlying their regulatory motif activities within the signaling network. RMOD is freely accessible online at the following URL: http://pks.kaist.ac.kr/rmod.

  10. Predictive modelling of complex agronomic and biological systems.

    Science.gov (United States)

    Keurentjes, Joost J B; Molenaar, Jaap; Zwaan, Bas J

    2013-09-01

    Biological systems are tremendously complex in their functioning and regulation. Studying the multifaceted behaviour and describing the performance of such complexity has challenged the scientific community for years. The reduction of real-world intricacy into simple descriptive models has therefore convinced many researchers of the usefulness of introducing mathematics into biological sciences. Predictive modelling takes such an approach another step further in that it takes advantage of existing knowledge to project the performance of a system in alternating scenarios. The ever growing amounts of available data generated by assessing biological systems at increasingly higher detail provide unique opportunities for future modelling and experiment design. Here we aim to provide an overview of the progress made in modelling over time and the currently prevalent approaches for iterative modelling cycles in modern biology. We will further argue for the importance of versatility in modelling approaches, including parameter estimation, model reduction and network reconstruction. Finally, we will discuss the difficulties in overcoming the mathematical interpretation of in vivo complexity and address some of the future challenges lying ahead. © 2013 John Wiley & Sons Ltd.

  11. The limits of de novo DNA motif discovery.

    Directory of Open Access Journals (Sweden)

    David Simcha

    Full Text Available A major challenge in molecular biology is reverse-engineering the cis-regulatory logic that plays a major role in the control of gene expression. This program includes searching through DNA sequences to identify "motifs" that serve as the binding sites for transcription factors or, more generally, are predictive of gene expression across cellular conditions. Several approaches have been proposed for de novo motif discovery-searching sequences without prior knowledge of binding sites or nucleotide patterns. However, unbiased validation is not straightforward. We consider two approaches to unbiased validation of discovered motifs: testing the statistical significance of a motif using a DNA "background" sequence model to represent the null hypothesis and measuring performance in predicting membership in gene clusters. We demonstrate that the background models typically used are "too null," resulting in overly optimistic assessments of significance, and argue that performance in predicting TF binding or expression patterns from DNA motifs should be assessed by held-out data, as in predictive learning. Applying this criterion to common motif discovery methods resulted in universally poor performance, although there is a marked improvement when motifs are statistically significant against real background sequences. Moreover, on synthetic data where "ground truth" is known, discriminative performance of all algorithms is far below the theoretical upper bound, with pronounced "over-fitting" in training. A key conclusion from this work is that the failure of de novo discovery approaches to accurately identify motifs is basically due to statistical intractability resulting from the fixed size of co-regulated gene clusters, and thus such failures do not necessarily provide evidence that unfound motifs are not active biologically. Consequently, the use of prior knowledge to enhance motif discovery is not just advantageous but necessary. An implementation of

  12. A Simple Decision Rule for Recognition of Poly(A) Tail Signal Motifs in Human Genome

    KAUST Repository

    AbouEisha, Hassan M.

    2015-05-12

    Background is the numerous attempts were made to predict motifs in genomic sequences that correspond to poly (A) tail signals. Vast portion of this effort has been directed to a plethora of nonlinear classification methods. Even when such approaches yield good discriminant results, identifying dominant features of regulatory mechanisms nevertheless remains a challenge. In this work, we look at decision rules that may help identifying such features. Findings are we present a simple decision rule for classification of candidate poly (A) tail signal motifs in human genomic sequence obtained by evaluating features during the construction of gradient boosted trees. We found that values of a single feature based on the frequency of adenine in the genomic sequence surrounding candidate signal and the number of consecutive adenine molecules in a well-defined region immediately following the motif displays good discriminative potential in classification of poly (A) tail motifs for samples covered by the rule. Conclusions is the resulting simple rule can be used as an efficient filter in construction of more complex poly(A) tail motifs classification algorithms.

  13. Genomic prediction of complex human traits: relatedness, trait architecture and predictive meta-models

    Science.gov (United States)

    Spiliopoulou, Athina; Nagy, Reka; Bermingham, Mairead L.; Huffman, Jennifer E.; Hayward, Caroline; Vitart, Veronique; Rudan, Igor; Campbell, Harry; Wright, Alan F.; Wilson, James F.; Pong-Wong, Ricardo; Agakov, Felix; Navarro, Pau; Haley, Chris S.

    2015-01-01

    We explore the prediction of individuals' phenotypes for complex traits using genomic data. We compare several widely used prediction models, including Ridge Regression, LASSO and Elastic Nets estimated from cohort data, and polygenic risk scores constructed using published summary statistics from genome-wide association meta-analyses (GWAMA). We evaluate the interplay between relatedness, trait architecture and optimal marker density, by predicting height, body mass index (BMI) and high-density lipoprotein level (HDL) in two data cohorts, originating from Croatia and Scotland. We empirically demonstrate that dense models are better when all genetic effects are small (height and BMI) and target individuals are related to the training samples, while sparse models predict better in unrelated individuals and when some effects have moderate size (HDL). For HDL sparse models achieved good across-cohort prediction, performing similarly to the GWAMA risk score and to models trained within the same cohort, which indicates that, for predicting traits with moderately sized effects, large sample sizes and familial structure become less important, though still potentially useful. Finally, we propose a novel ensemble of whole-genome predictors with GWAMA risk scores and demonstrate that the resulting meta-model achieves higher prediction accuracy than either model on its own. We conclude that although current genomic predictors are not accurate enough for diagnostic purposes, performance can be improved without requiring access to large-scale individual-level data. Our methodologically simple meta-model is a means of performing predictive meta-analysis for optimizing genomic predictions and can be easily extended to incorporate multiple population-level summary statistics or other domain knowledge. PMID:25918167

  14. Predicting the future completing models of observed complex systems

    CERN Document Server

    Abarbanel, Henry

    2013-01-01

    Predicting the Future: Completing Models of Observed Complex Systems provides a general framework for the discussion of model building and validation across a broad spectrum of disciplines. This is accomplished through the development of an exact path integral for use in transferring information from observations to a model of the observed system. Through many illustrative examples drawn from models in neuroscience, fluid dynamics, geosciences, and nonlinear electrical circuits, the concepts are exemplified in detail. Practical numerical methods for approximate evaluations of the path integral are explored, and their use in designing experiments and determining a model's consistency with observations is investigated. Using highly instructive examples, the problems of data assimilation and the means to treat them are clearly illustrated. This book will be useful for students and practitioners of physics, neuroscience, regulatory networks, meteorology and climate science, network dynamics, fluid dynamics, and o...

  15. Motif enrichment tool.

    Science.gov (United States)

    Blatti, Charles; Sinha, Saurabh

    2014-07-01

    The Motif Enrichment Tool (MET) provides an online interface that enables users to find major transcriptional regulators of their gene sets of interest. MET searches the appropriate regulatory region around each gene and identifies which transcription factor DNA-binding specificities (motifs) are statistically overrepresented. Motif enrichment analysis is currently available for many metazoan species including human, mouse, fruit fly, planaria and flowering plants. MET also leverages high-throughput experimental data such as ChIP-seq and DNase-seq from ENCODE and ModENCODE to identify the regulatory targets of a transcription factor with greater precision. The results from MET are produced in real time and are linked to a genome browser for easy follow-up analysis. Use of the web tool is free and open to all, and there is no login requirement. ADDRESS: http://veda.cs.uiuc.edu/MET/. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  16. Protein complex prediction based on k-connected subgraphs in protein interaction network

    OpenAIRE

    Habibi, Mahnaz; Eslahchi, Changiz; Wong, Limsoon

    2010-01-01

    Abstract Background Protein complexes play an important role in cellular mechanisms. Recently, several methods have been presented to predict protein complexes in a protein interaction network. In these methods, a protein complex is predicted as a dense subgraph of protein interactions. However, interactions data are incomplete and a protein complex does not have to be a complete or dense subgraph. Results We propose a more appropriate protein complex prediction method, CFA, that is based on ...

  17. Motif-role-fingerprints: the building-blocks of motifs, clustering-coefficients and transitivities in directed networks.

    Directory of Open Access Journals (Sweden)

    Mark D McDonnell

    Full Text Available Complex networks are frequently characterized by metrics for which particular subgraphs are counted. One statistic from this category, which we refer to as motif-role fingerprints, differs from global subgraph counts in that the number of subgraphs in which each node participates is counted. As with global subgraph counts, it can be important to distinguish between motif-role fingerprints that are 'structural' (induced subgraphs and 'functional' (partial subgraphs. Here we show mathematically that a vector of all functional motif-role fingerprints can readily be obtained from an arbitrary directed adjacency matrix, and then converted to structural motif-role fingerprints by multiplying that vector by a specific invertible conversion matrix. This result demonstrates that a unique structural motif-role fingerprint exists for any given functional motif-role fingerprint. We demonstrate a similar result for the cases of functional and structural motif-fingerprints without node roles, and global subgraph counts that form the basis of standard motif analysis. We also explicitly highlight that motif-role fingerprints are elemental to several popular metrics for quantifying the subgraph structure of directed complex networks, including motif distributions, directed clustering coefficient, and transitivity. The relationships between each of these metrics and motif-role fingerprints also suggest new subtypes of directed clustering coefficients and transitivities. Our results have potential utility in analyzing directed synaptic networks constructed from neuronal connectome data, such as in terms of centrality. Other potential applications include anomaly detection in networks, identification of similar networks and identification of similar nodes within networks. Matlab code for calculating all stated metrics following calculation of functional motif-role fingerprints is provided as S1 Matlab File.

  18. Supporting change processes in design: Complexity, prediction and reliability

    Energy Technology Data Exchange (ETDEWEB)

    Eckert, Claudia M. [Engineering Design Centre, University of Cambridge, Trumpington Street, Cambridge, CB2 1PZ (United Kingdom)]. E-mail: cme26@cam.ac.uk; Keller, Rene [Engineering Design Centre, University of Cambridge, Trumpington Street, Cambridge, CB2 1PZ (United Kingdom)]. E-mail: rk313@cam.ac.uk; Earl, Chris [Open University, Department of Design and Innovation, Walton Hall, Milton Keynes MK7 6AA (United Kingdom)]. E-mail: C.F.Earl@open.ac.uk; Clarkson, P. John [Engineering Design Centre, University of Cambridge, Trumpington Street, Cambridge, CB2 1PZ (United Kingdom)]. E-mail: pjc10@cam.ac.uk

    2006-12-15

    Change to existing products is fundamental to design processes. New products are often designed through change or modification to existing products. Specific parts or subsystems are changed to similar ones whilst others are directly reused. Design by modification applies particularly to safety critical products where the reuse of existing working parts and subsystems can reduce cost and risk. However change is rarely a matter of just reusing or modifying parts. Changing one part can propagate through the entire design leading to costly rework or jeopardising the integrity of the whole product. This paper characterises product change based on studies in the aerospace and automotive industry and introduces tools to aid designers in understanding the potential effects of change. Two ways of supporting designers are described: probabilistic prediction of the effects of change and visualisation of change propagation through product connectivities. Change propagation has uncertainties which are amplified by the choices designers make in practice as they implement change. Change prediction and visualisation is discussed with reference to complexity in three areas of product development: the structural backcloth of connectivities in the existing product (and its processes), the descriptions of the product used in design and the actions taken to carry out changes.

  19. The identification of functional motifs in temporal gene expression analysis

    Directory of Open Access Journals (Sweden)

    Michael G. Surette

    2005-01-01

    Full Text Available The identification of transcription factor binding sites is essential to the understanding of the regulation of gene expression and the reconstruction of genetic regulatory networks. The in silico identification of cis-regulatory motifs is challenging due to sequence variability and lack of sufficient data to generate consensus motifs that are of quantitative or even qualitative predictive value. To determine functional motifs in gene expression, we propose a strategy to adopt false discovery rate (FDR and estimate motif effects to evaluate combinatorial analysis of motif candidates and temporal gene expression data. The method decreases the number of predicted motifs, which can then be confirmed by genetic analysis. To assess the method we used simulated motif/expression data to evaluate parameters. We applied this approach to experimental data for a group of iron responsive genes in Salmonella typhimurium 14028S. The method identified known and potentially new ferric-uptake regulator (Fur binding sites. In addition, we identified uncharacterized functional motif candidates that correlated with specific patterns of expression. A SAS code for the simulation and analysis gene expression data is available from the first author upon request.

  20. Finding a Leucine in a Haystack: Searching the Proteome for ambigous Leucine-Aspartic Acid motifs

    KAUST Repository

    Arold, Stefan T.

    2016-01-01

    LDMF predicted 13 new LD motifs in humans. Using biophysical assays, we experimentally confirmed in vitro interactions for four novel LD motif proteins. Thus, LDMF allows proteome-wide discovery of LD motifs, despite a highly ambiguous sequence pattern. Functional implications will be discussed.

  1. Positional bias of general and tissue-specific regulatory motifs in mouse gene promoters

    Directory of Open Access Journals (Sweden)

    Farré Domènec

    2007-12-01

    Full Text Available Abstract Background The arrangement of regulatory motifs in gene promoters, or promoter architecture, is the result of mutation and selection processes that have operated over many millions of years. In mammals, tissue-specific transcriptional regulation is related to the presence of specific protein-interacting DNA motifs in gene promoters. However, little is known about the relative location and spacing of these motifs. To fill this gap, we have performed a systematic search for motifs that show significant bias at specific promoter locations in a large collection of housekeeping and tissue-specific genes. Results We observe that promoters driving housekeeping gene expression are enriched in particular motifs with strong positional bias, such as YY1, which are of little relevance in promoters driving tissue-specific expression. We also identify a large number of motifs that show positional bias in genes expressed in a highly tissue-specific manner. They include well-known tissue-specific motifs, such as HNF1 and HNF4 motifs in liver, kidney and small intestine, or RFX motifs in testis, as well as many potentially novel regulatory motifs. Based on this analysis, we provide predictions for 559 tissue-specific motifs in mouse gene promoters. Conclusion The study shows that motif positional bias is an important feature of mammalian proximal promoters and that it affects both general and tissue-specific motifs. Motif positional constraints define very distinct promoter architectures depending on breadth of expression and type of tissue.

  2. Automatic annotation of protein motif function with Gene Ontology terms

    Directory of Open Access Journals (Sweden)

    Gopalakrishnan Vanathi

    2004-09-01

    Full Text Available Abstract Background Conserved protein sequence motifs are short stretches of amino acid sequence patterns that potentially encode the function of proteins. Several sequence pattern searching algorithms and programs exist foridentifying candidate protein motifs at the whole genome level. However, amuch needed and importanttask is to determine the functions of the newly identified protein motifs. The Gene Ontology (GO project is an endeavor to annotate the function of genes or protein sequences with terms from a dynamic, controlled vocabulary and these annotations serve well as a knowledge base. Results This paperpresents methods to mine the GO knowledge base and use the association between the GO terms assigned to a sequence and the motifs matched by the same sequence as evidence for predicting the functions of novel protein motifs automatically. The task of assigning GO terms to protein motifsis viewed as both a binary classification and information retrieval problem, where PROSITE motifs are used as samples for mode training and functional prediction. The mutual information of a motif and aGO term association isfound to be a very useful feature. We take advantageof the known motifs to train a logistic regression classifier, which allows us to combine mutual information with other frequency-based features and obtain a probability of correctassociation. The trained logistic regression model has intuitively meaningful and logically plausible parameter values, and performs very well empirically according to our evaluation criteria. Conclusions In this research, different methods for automatic annotation of protein motifs have been investigated. Empirical result demonstrated that the methods have a great potential for detecting and augmenting information about thefunctions of newly discovered candidate protein motifs.

  3. Detection and characterization of 3D-signature phosphorylation site motifs and their contribution towards improved phosphorylation site prediction in proteins

    Directory of Open Access Journals (Sweden)

    Selbig Joachim

    2009-04-01

    Full Text Available Abstract Background Phosphorylation of proteins plays a crucial role in the regulation and activation of metabolic and signaling pathways and constitutes an important target for pharmaceutical intervention. Central to the phosphorylation process is the recognition of specific target sites by protein kinases followed by the covalent attachment of phosphate groups to the amino acids serine, threonine, or tyrosine. The experimental identification as well as computational prediction of phosphorylation sites (P-sites has proved to be a challenging problem. Computational methods have focused primarily on extracting predictive features from the local, one-dimensional sequence information surrounding phosphorylation sites. Results We characterized the spatial context of phosphorylation sites and assessed its usability for improved phosphorylation site predictions. We identified 750 non-redundant, experimentally verified sites with three-dimensional (3D structural information available in the protein data bank (PDB and grouped them according to their respective kinase family. We studied the spatial distribution of amino acids around phosphorserines, phosphothreonines, and phosphotyrosines to extract signature 3D-profiles. Characteristic spatial distributions of amino acid residue types around phosphorylation sites were indeed discernable, especially when kinase-family-specific target sites were analyzed. To test the added value of using spatial information for the computational prediction of phosphorylation sites, Support Vector Machines were applied using both sequence as well as structural information. When compared to sequence-only based prediction methods, a small but consistent performance improvement was obtained when the prediction was informed by 3D-context information. Conclusion While local one-dimensional amino acid sequence information was observed to harbor most of the discriminatory power, spatial context information was identified as

  4. iELM—a web server to explore short linear motif-mediated interactions

    Science.gov (United States)

    Weatheritt, Robert J.; Jehl, Peter; Dinkel, Holger; Gibson, Toby J.

    2012-01-01

    The recent expansion in our knowledge of protein–protein interactions (PPIs) has allowed the annotation and prediction of hundreds of thousands of interactions. However, the function of many of these interactions remains elusive. The interactions of Eukaryotic Linear Motif (iELM) web server provides a resource for predicting the function and positional interface for a subset of interactions mediated by short linear motifs (SLiMs). The iELM prediction algorithm is based on the annotated SLiM classes from the Eukaryotic Linear Motif (ELM) resource and allows users to explore both annotated and user-generated PPI networks for SLiM-mediated interactions. By incorporating the annotated information from the ELM resource, iELM provides functional details of PPIs. This can be used in proteomic analysis, for example, to infer whether an interaction promotes complex formation or degradation. Furthermore, details of the molecular interface of the SLiM-mediated interactions are also predicted. This information is displayed in a fully searchable table, as well as graphically with the modular architecture of the participating proteins extracted from the UniProt and Phospho.ELM resources. A network figure is also presented to aid the interpretation of results. The iELM server supports single protein queries as well as large-scale proteomic submissions and is freely available at http://i.elm.eu.org. PMID:22638578

  5. Structure of a SUMO-binding-motif mimic bound to Smt3p–Ubc9p: conservation of a noncovalent Ubiquitin-like protein–E2 complex as a platform for selective interactions within a SUMO pathway

    Science.gov (United States)

    Duda, David M.; van Waardenburg, Robert C. A. M.; Borg, Laura A.; McGarity, Sierra; Nourse, Amanda; Waddell, M. Brett; Bjornsti, Mary-Ann; Schulman, Brenda A.

    2007-01-01

    Summary The SUMO ubiquitin-like proteins play regulatory roles in cell division, transcription, DNA repair, and protein subcellular localization. Paralleling other ubiquitin-like proteins, SUMO proteins are proteolytically processed to maturity, conjugated to targets by E1-E2-E3 cascades, and subsequently recognized by specific downstream effectors containing a SUMO-binding motif (SBM). SUMO and its E2 from the budding yeast S. cerevisiae, Smt3p and Ubc9p, are encoded by essential genes. Here we describe the 1.9 Å resolution crystal structure of a noncovalent Smt3p–Ubc9p complex. Unexpectedly, a heterologous portion of the crystallized complex derived from the expression construct mimics an SBM, and binds Smt3p in a manner resembling SBM binding to human SUMO family members. In the complex, Smt3p binds a surface distal from Ubc9's catalytic cysteine. The structure implies that a single molecule of Smt3p cannot bind concurrently to both the noncovalent binding site and the catalytic cysteine of a single Ubc9p molecule. However, formation of higher-order complexes can occur, where a single Smt3p covalently linked to one Ubc9p's catalytic cysteine also binds noncovalently to another molecule of Ubc9p. Comparison with other structures from the SUMO pathway suggests that formation of the noncovalent Smt3p–Ubc9p complex occurs mutually exclusively with many other Smt3p and Ubc9p interactions in the conjugation cascade. By contrast, high-resolution insights into how Smt3p–Ubc9p can also interact with downstream recognition machineries come from contacts with the SBM mimic. Interestingly, the overall architecture of the Smt3p–Ubc9p complex is strikingly similar to recent structures from the ubiquitin pathway. The results imply that noncovalent ubiquitin-like protein–E2 complexes are conserved platforms, which function as parts of larger assemblies involved many protein post-translational regulatory pathways. PMID:17475278

  6. Computational analyses of synergism in small molecular network motifs.

    Directory of Open Access Journals (Sweden)

    Yili Zhang

    2014-03-01

    Full Text Available Cellular functions and responses to stimuli are controlled by complex regulatory networks that comprise a large diversity of molecular components and their interactions. However, achieving an intuitive understanding of the dynamical properties and responses to stimuli of these networks is hampered by their large scale and complexity. To address this issue, analyses of regulatory networks often focus on reduced models that depict distinct, reoccurring connectivity patterns referred to as motifs. Previous modeling studies have begun to characterize the dynamics of small motifs, and to describe ways in which variations in parameters affect their responses to stimuli. The present study investigates how variations in pairs of parameters affect responses in a series of ten common network motifs, identifying concurrent variations that act synergistically (or antagonistically to alter the responses of the motifs to stimuli. Synergism (or antagonism was quantified using degrees of nonlinear blending and additive synergism. Simulations identified concurrent variations that maximized synergism, and examined the ways in which it was affected by stimulus protocols and the architecture of a motif. Only a subset of architectures exhibited synergism following paired changes in parameters. The approach was then applied to a model describing interlocked feedback loops governing the synthesis of the CREB1 and CREB2 transcription factors. The effects of motifs on synergism for this biologically realistic model were consistent with those for the abstract models of single motifs. These results have implications for the rational design of combination drug therapies with the potential for synergistic interactions.

  7. RNA motif search with data-driven element ordering.

    Science.gov (United States)

    Rampášek, Ladislav; Jimenez, Randi M; Lupták, Andrej; Vinař, Tomáš; Brejová, Broňa

    2016-05-18

    In this paper, we study the problem of RNA motif search in long genomic sequences. This approach uses a combination of sequence and structure constraints to uncover new distant homologs of known functional RNAs. The problem is NP-hard and is traditionally solved by backtracking algorithms. We have designed a new algorithm for RNA motif search and implemented a new motif search tool RNArobo. The tool enhances the RNAbob descriptor language, allowing insertions in helices, which enables better characterization of ribozymes and aptamers. A typical RNA motif consists of multiple elements and the running time of the algorithm is highly dependent on their ordering. By approaching the element ordering problem in a principled way, we demonstrate more than 100-fold speedup of the search for complex motifs compared to previously published tools. We have developed a new method for RNA motif search that allows for a significant speedup of the search of complex motifs that include pseudoknots. Such speed improvements are crucial at a time when the rate of DNA sequencing outpaces growth in computing. RNArobo is available at http://compbio.fmph.uniba.sk/rnarobo .

  8. DMINDA: an integrated web server for DNA motif identification and analyses.

    Science.gov (United States)

    Ma, Qin; Zhang, Hanyuan; Mao, Xizeng; Zhou, Chuan; Liu, Bingqiang; Chen, Xin; Xu, Ying

    2014-07-01

    DMINDA (DNA motif identification and analyses) is an integrated web server for DNA motif identification and analyses, which is accessible at http://csbl.bmb.uga.edu/DMINDA/. This web site is freely available to all users and there is no login requirement. This server provides a suite of cis-regulatory motif analysis functions on DNA sequences, which are important to elucidation of the mechanisms of transcriptional regulation: (i) de novo motif finding for a given set of promoter sequences along with statistical scores for the predicted motifs derived based on information extracted from a control set, (ii) scanning motif instances of a query motif in provided genomic sequences, (iii) motif comparison and clustering of identified motifs, and (iv) co-occurrence analyses of query motifs in given promoter sequences. The server is powered by a backend computer cluster with over 150 computing nodes, and is particularly useful for motif prediction and analyses in prokaryotic genomes. We believe that DMINDA, as a new and comprehensive web server for cis-regulatory motif finding and analyses, will benefit the genomic research community in general and prokaryotic genome researchers in particular. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  9. ComplexContact: a web server for inter-protein contact prediction using deep learning

    KAUST Repository

    Zeng, Hong; Wang, Sheng; Zhou, Tianming; Zhao, Feifeng; Li, Xiufeng; Wu, Qing; Xu, Jinbo

    2018-01-01

    ComplexContact (http://raptorx2.uchicago.edu/ComplexContact/) is a web server for sequence-based interfacial residue-residue contact prediction of a putative protein complex. Interfacial residue-residue contacts are critical for understanding how proteins form complex and interact at residue level. When receiving a pair of protein sequences, ComplexContact first searches for their sequence homologs and builds two paired multiple sequence alignments (MSA), then it applies co-evolution analysis and a CASP-winning deep learning (DL) method to predict interfacial contacts from paired MSAs and visualizes the prediction as an image. The DL method was originally developed for intra-protein contact prediction and performed the best in CASP12. Our large-scale experimental test further shows that ComplexContact greatly outperforms pure co-evolution methods for inter-protein contact prediction, regardless of the species.

  10. ComplexContact: a web server for inter-protein contact prediction using deep learning

    KAUST Repository

    Zeng, Hong

    2018-05-20

    ComplexContact (http://raptorx2.uchicago.edu/ComplexContact/) is a web server for sequence-based interfacial residue-residue contact prediction of a putative protein complex. Interfacial residue-residue contacts are critical for understanding how proteins form complex and interact at residue level. When receiving a pair of protein sequences, ComplexContact first searches for their sequence homologs and builds two paired multiple sequence alignments (MSA), then it applies co-evolution analysis and a CASP-winning deep learning (DL) method to predict interfacial contacts from paired MSAs and visualizes the prediction as an image. The DL method was originally developed for intra-protein contact prediction and performed the best in CASP12. Our large-scale experimental test further shows that ComplexContact greatly outperforms pure co-evolution methods for inter-protein contact prediction, regardless of the species.

  11. ComplexContact: a web server for inter-protein contact prediction using deep learning.

    Science.gov (United States)

    Zeng, Hong; Wang, Sheng; Zhou, Tianming; Zhao, Feifeng; Li, Xiufeng; Wu, Qing; Xu, Jinbo

    2018-05-22

    ComplexContact (http://raptorx2.uchicago.edu/ComplexContact/) is a web server for sequence-based interfacial residue-residue contact prediction of a putative protein complex. Interfacial residue-residue contacts are critical for understanding how proteins form complex and interact at residue level. When receiving a pair of protein sequences, ComplexContact first searches for their sequence homologs and builds two paired multiple sequence alignments (MSA), then it applies co-evolution analysis and a CASP-winning deep learning (DL) method to predict interfacial contacts from paired MSAs and visualizes the prediction as an image. The DL method was originally developed for intra-protein contact prediction and performed the best in CASP12. Our large-scale experimental test further shows that ComplexContact greatly outperforms pure co-evolution methods for inter-protein contact prediction, regardless of the species.

  12. Foundations of Complex Systems Nonlinear Dynamics, Statistical Physics, and Prediction

    CERN Document Server

    Nicolis, Gregoire

    2007-01-01

    Complexity is emerging as a post-Newtonian paradigm for approaching a large body of phenomena of concern at the crossroads of physical, engineering, environmental, life and human sciences from a unifying point of view. This book outlines the foundations of modern complexity research as it arose from the cross-fertilization of ideas and tools from nonlinear science, statistical physics and numerical simulation. It is shown how these developments lead to an understanding, both qualitative and quantitative, of the complex systems encountered in nature and in everyday experience and, conversely, h

  13. Hypoxia-dependent sequestration of an oxygen sensor by a widespread structural motif can shape the hypoxic response - a predictive kinetic model

    Directory of Open Access Journals (Sweden)

    Novák Béla

    2010-10-01

    Full Text Available Abstract Background The activity of the heterodimeric transcription factor hypoxia inducible factor (HIF is regulated by the post-translational, oxygen-dependent hydroxylation of its α-subunit by members of the prolyl hydroxylase domain (PHD or EGLN-family and by factor inhibiting HIF (FIH. PHD-dependent hydroxylation targets HIFα for rapid proteasomal degradation; FIH-catalysed asparaginyl-hydroxylation of the C-terminal transactivation domain (CAD of HIFα suppresses the CAD-dependent subset of the extensive transcriptional responses induced by HIF. FIH can also hydroxylate ankyrin-repeat domain (ARD proteins, a large group of proteins which are functionally unrelated but share common structural features. Competition by ARD proteins for FIH is hypothesised to affect FIH activity towards HIFα; however the extent of this competition and its effect on the HIF-dependent hypoxic response are unknown. Results To analyse if and in which way the FIH/ARD protein interaction affects HIF-activity, we created a rate equation model. Our model predicts that an oxygen-regulated sequestration of FIH by ARD proteins significantly shapes the input/output characteristics of the HIF system. The FIH/ARD protein interaction is predicted to create an oxygen threshold for HIFα CAD-hydroxylation and to significantly sharpen the signal/response curves, which not only focuses HIFα CAD-hydroxylation into a defined range of oxygen tensions, but also makes the response ultrasensitive to varying oxygen tensions. Our model further suggests that the hydroxylation status of the ARD protein pool can encode the strength and the duration of a hypoxic episode, which may allow cells to memorise these features for a certain time period after reoxygenation. Conclusions The FIH/ARD protein interaction has the potential to contribute to oxygen-range finding, can sensitise the response to changes in oxygen levels, and can provide a memory of the strength and the duration of a

  14. Children's Verbal Working Memory: Role of Processing Complexity in Predicting Spoken Sentence Comprehension

    Science.gov (United States)

    Magimairaj, Beula M.; Montgomery, James W.

    2012-01-01

    Purpose: This study investigated the role of processing complexity of verbal working memory tasks in predicting spoken sentence comprehension in typically developing children. Of interest was whether simple and more complex working memory tasks have similar or different power in predicting sentence comprehension. Method: Sixty-five children (6- to…

  15. Prediction of Protein-Protein Interactions Related to Protein Complexes Based on Protein Interaction Networks

    Directory of Open Access Journals (Sweden)

    Peng Liu

    2015-01-01

    Full Text Available A method for predicting protein-protein interactions based on detected protein complexes is proposed to repair deficient interactions derived from high-throughput biological experiments. Protein complexes are pruned and decomposed into small parts based on the adaptive k-cores method to predict protein-protein interactions associated with the complexes. The proposed method is adaptive to protein complexes with different structure, number, and size of nodes in a protein-protein interaction network. Based on different complex sets detected by various algorithms, we can obtain different prediction sets of protein-protein interactions. The reliability of the predicted interaction sets is proved by using estimations with statistical tests and direct confirmation of the biological data. In comparison with the approaches which predict the interactions based on the cliques, the overlap of the predictions is small. Similarly, the overlaps among the predicted sets of interactions derived from various complex sets are also small. Thus, every predicted set of interactions may complement and improve the quality of the original network data. Meanwhile, the predictions from the proposed method replenish protein-protein interactions associated with protein complexes using only the network topology.

  16. Protein complex prediction based on k-connected subgraphs in protein interaction network

    Directory of Open Access Journals (Sweden)

    Habibi Mahnaz

    2010-09-01

    Full Text Available Abstract Background Protein complexes play an important role in cellular mechanisms. Recently, several methods have been presented to predict protein complexes in a protein interaction network. In these methods, a protein complex is predicted as a dense subgraph of protein interactions. However, interactions data are incomplete and a protein complex does not have to be a complete or dense subgraph. Results We propose a more appropriate protein complex prediction method, CFA, that is based on connectivity number on subgraphs. We evaluate CFA using several protein interaction networks on reference protein complexes in two benchmark data sets (MIPS and Aloy, containing 1142 and 61 known complexes respectively. We compare CFA to some existing protein complex prediction methods (CMC, MCL, PCP and RNSC in terms of recall and precision. We show that CFA predicts more complexes correctly at a competitive level of precision. Conclusions Many real complexes with different connectivity level in protein interaction network can be predicted based on connectivity number. Our CFA program and results are freely available from http://www.bioinf.cs.ipm.ir/softwares/cfa/CFA.rar.

  17. Political complexity predicts the spread of ethnolinguistic groups

    Science.gov (United States)

    Currie, Thomas E.; Mace, Ruth

    2009-01-01

    Human languages show a remarkable degree of variation in the area they cover. However, the factors governing the distribution of human cultural groups such as languages are not well understood. While previous studies have examined the role of a number of environmental variables the importance of cultural factors has not been systematically addressed. Here we use a geographical information system (GIS) to integrate information about languages with environmental, ecological, and ethnographic data to test a number of hypotheses that have been proposed to explain the global distribution of languages. We show that the degree of political complexity and type of subsistence strategy exhibited by societies are important predictors of the area covered by a language. Political complexity is also strongly associated with the latitudinal gradient in language area, whereas subsistence strategy is not. We argue that a process of cultural group selection favoring more complex societies may have been important in shaping the present-day global distribution of language diversity. PMID:19380740

  18. Prediction of wind energy distribution in complex terrain using CFD

    DEFF Research Database (Denmark)

    Xu, Chang; Li, Chenqi; Yang, Jianchuan

    2013-01-01

    Based on linear models, WAsP software predicts wind energy distribution, with a good accuracy for flat terrain, but with a large error under complicated topography. In this paper, numerical simulations are carried out using the FLUENT software on a mesh generated by the GAMBIT and ARGIS software ...

  19. Predicting Eye Fixations on Complex Visual Stimuli Using Local Symmetry

    NARCIS (Netherlands)

    Kootstra, Geert; de Boer, Bart; Schomaker, Lambertus

    Most bottom-up models that predict human eye fixations are based on contrast features. The saliency model of Itti, Koch and Niebur is an example of such contrast-saliency models. Although the model has been successfully compared to human eye fixations, we show that it lacks preciseness in the

  20. Predicting eye fixations on complex visual stimuli using local symmetry

    NARCIS (Netherlands)

    Kootstra, G.; de Boer, B.; Schomaker, L.R.B.

    2011-01-01

    Most bottom-up models that predict human eye fixations are based on contrast features. The saliency model of Itti, Koch and Niebur is an example of such contrast-saliency models. Although the model has been successfully compared to human eye fixations, we show that it lacks preciseness in the

  1. Neighboring phosphoSer-Pro motifs in the undefined domain of IRAK1 impart bivalent advantage for Pin1 binding.

    Science.gov (United States)

    Rogals, Monique J; Greenwood, Alexander I; Kwon, Jeahoo; Lu, Kun Ping; Nicholson, Linda K

    2016-12-01

    The peptidyl prolyl isomerase Pin1 has two domains that are considered to be its binding (WW) and catalytic (PPIase) domains, both of which interact with phosphorylated Ser/Thr-Pro motifs. This shared specificity might influence substrate selection, as many known Pin1 substrates have multiple sequentially close phosphoSer/Thr-Pro motifs, including the protein interleukin-1 receptor-associated kinase-1 (IRAK1). The IRAK1 undefined domain (UD) contains two sets of such neighboring motifs (Ser131/Ser144 and Ser163/Ser173), suggesting possible bivalent interactions with Pin1. Using a series of NMR titrations with 15N-labeled full-length Pin1 (Pin1-FL), PPIase, or WW domain and phosphopeptides representing the Ser131/Ser144 and Ser163/Ser173 regions of IRAK1-UD, bivalent interactions were investigated. Binding studies using singly phosphorylated peptides showed that individual motifs displayed weak affinities (> 100 μm) for Pin1-FL and each isolated domain. Analysis of dually phosphorylated peptides binding to Pin1-FL showed that inclusion of bivalent states was necessary to fit the data. The resulting complex model and fitted parameters were applied to predict the impact of bivalent states at low micromolar concentrations, demonstrating significant affinity enhancement for both dually phosphorylated peptides (3.5 and 24 μm for peptides based on the Ser131/Ser144 and Ser163/Ser173 regions, respectively). The complementary technique biolayer interferometry confirmed the predicted affinity enhancement for a representative set of singly and dually phosphorylated Ser131/Ser144 peptides at low micromolar concentrations, validating model predictions. These studies provide novel insights regarding the complexity of interactions between Pin1 and activated IRAK1, and more broadly suggest that phosphorylation of neighboring Ser/Thr-Pro motifs in proteins might provide competitive advantage at cellular concentrations for engaging with Pin1. © 2016 Federation of European

  2. Dissecting protein loops with a statistical scalpel suggests a functional implication of some structural motifs.

    Science.gov (United States)

    Regad, Leslie; Martin, Juliette; Camproux, Anne-Claude

    2011-06-20

    One of the strategies for protein function annotation is to search particular structural motifs that are known to be shared by proteins with a given function. Here, we present a systematic extraction of structural motifs of seven residues from protein loops and we explore their correspondence with functional sites. Our approach is based on the structural alphabet HMM-SA (Hidden Markov Model - Structural Alphabet), which allows simplification of protein structures into uni-dimensional sequences, and advanced pattern statistics adapted to short sequences. Structural motifs of interest are selected by looking for structural motifs significantly over-represented in SCOP superfamilies in protein loops. We discovered two types of structural motifs significantly over-represented in SCOP superfamilies: (i) ubiquitous motifs, shared by several superfamilies and (ii) superfamily-specific motifs, over-represented in few superfamilies. A comparison of ubiquitous words with known small structural motifs shows that they contain well-described motifs as turn, niche or nest motifs. A comparison between superfamily-specific motifs and biological annotations of Swiss-Prot reveals that some of them actually correspond to functional sites involved in the binding sites of small ligands, such as ATP/GTP, NAD(P) and SAH/SAM. Our findings show that statistical over-representation in SCOP superfamilies is linked to functional features. The detection of over-represented motifs within structures simplified by HMM-SA is therefore a promising approach for prediction of functional sites and annotation of uncharacterized proteins.

  3. Are more complex physiological models of forest ecosystems better choices for plot and regional predictions?

    Science.gov (United States)

    Wenchi Jin; Hong S. He; Frank R. Thompson

    2016-01-01

    Process-based forest ecosystem models vary from simple physiological, complex physiological, to hybrid empirical-physiological models. Previous studies indicate that complex models provide the best prediction at plot scale with a temporal extent of less than 10 years, however, it is largely untested as to whether complex models outperform the other two types of models...

  4. Identification, occurrence, and validation of DRE and ABRE Cis-regulatory motifs in the promoter regions of genes of Arabidopsis thaliana.

    Science.gov (United States)

    Mishra, Sonal; Shukla, Aparna; Upadhyay, Swati; Sanchita; Sharma, Pooja; Singh, Seema; Phukan, Ujjal J; Meena, Abha; Khan, Feroz; Tripathi, Vineeta; Shukla, Rakesh Kumar; Shrama, Ashok

    2014-04-01

    Plants posses a complex co-regulatory network which helps them to elicit a response under diverse adverse conditions. We used an in silico approach to identify the genes with both DRE and ABRE motifs in their promoter regions in Arabidopsis thaliana. Our results showed that Arabidopsis contains a set of 2,052 genes with ABRE and DRE motifs in their promoter regions. Approximately 72% or more of the total predicted 2,052 genes had a gap distance of less than 400 bp between DRE and ABRE motifs. For positional orientation of the DRE and ABRE motifs, we found that the DR form (one in direct and the other one in reverse orientation) was more prevalent than other forms. These predicted 2,052 genes include 155 transcription factors. Using microarray data from The Arabidopsis Information Resource (TAIR) database, we present 44 transcription factors out of 155 which are upregulated by more than twofold in response to osmotic stress and ABA treatment. Fifty-one transcripts from the one predicted above were validated using semiquantitative expression analysis to support the microarray data in TAIR. Taken together, we report a set of genes containing both DRE and ABRE motifs in their promoter regions in A. thaliana, which can be useful to understand the role of ABA under osmotic stress condition. © 2013 Institute of Botany, Chinese Academy of Sciences.

  5. Predicting DNA-binding proteins and binding residues by complex structure prediction and application to human proteome.

    Directory of Open Access Journals (Sweden)

    Huiying Zhao

    Full Text Available As more and more protein sequences are uncovered from increasingly inexpensive sequencing techniques, an urgent task is to find their functions. This work presents a highly reliable computational technique for predicting DNA-binding function at the level of protein-DNA complex structures, rather than low-resolution two-state prediction of DNA-binding as most existing techniques do. The method first predicts protein-DNA complex structure by utilizing the template-based structure prediction technique HHblits, followed by binding affinity prediction based on a knowledge-based energy function (Distance-scaled finite ideal-gas reference state for protein-DNA interactions. A leave-one-out cross validation of the method based on 179 DNA-binding and 3797 non-binding protein domains achieves a Matthews correlation coefficient (MCC of 0.77 with high precision (94% and high sensitivity (65%. We further found 51% sensitivity for 82 newly determined structures of DNA-binding proteins and 56% sensitivity for the human proteome. In addition, the method provides a reasonably accurate prediction of DNA-binding residues in proteins based on predicted DNA-binding complex structures. Its application to human proteome leads to more than 300 novel DNA-binding proteins; some of these predicted structures were validated by known structures of homologous proteins in APO forms. The method [SPOT-Seq (DNA] is available as an on-line server at http://sparks-lab.org.

  6. Predicting Complex Organic Molecule Emission from TW Hya

    Science.gov (United States)

    Vissapragada, Shreyas; Walsh, Catherine

    2017-01-01

    The Atacama Large Millimeter/submillimeter Array (ALMA) has significantly increased our ability to observe the rich chemical inventory of star and planet formation. ALMA has recently been used to detect CH3OH (methanol) and CH3CN (methyl cyanide) in protoplanetary disks; these molecules may be vital indicators of the complex organic ice reservoir in the comet-forming zone. We have constructed a physiochemical model of TW Hya, a well-studied protoplanetary disk, to explore the different formation mechanisms of complex ices. By running our model through a radiative transfer code and convolving with beam sizes appropriate for ALMA, we have obtained synthetic observations of methanol and methyl cyanide. Here, we compare and comment on these synthetic observations, and provide astrochemical justification for their spatial distributions.

  7. Supervised maximum-likelihood weighting of composite protein networks for complex prediction

    Directory of Open Access Journals (Sweden)

    Yong Chern Han

    2012-12-01

    Full Text Available Abstract Background Protein complexes participate in many important cellular functions, so finding the set of existent complexes is essential for understanding the organization and regulation of processes in the cell. With the availability of large amounts of high-throughput protein-protein interaction (PPI data, many algorithms have been proposed to discover protein complexes from PPI networks. However, such approaches are hindered by the high rate of noise in high-throughput PPI data, including spurious and missing interactions. Furthermore, many transient interactions are detected between proteins that are not from the same complex, while not all proteins from the same complex may actually interact. As a result, predicted complexes often do not match true complexes well, and many true complexes go undetected. Results We address these challenges by integrating PPI data with other heterogeneous data sources to construct a composite protein network, and using a supervised maximum-likelihood approach to weight each edge based on its posterior probability of belonging to a complex. We then use six different clustering algorithms, and an aggregative clustering strategy, to discover complexes in the weighted network. We test our method on Saccharomyces cerevisiae and Homo sapiens, and show that complex discovery is improved: compared to previously proposed supervised and unsupervised weighting approaches, our method recalls more known complexes, achieves higher precision at all recall levels, and generates novel complexes of greater functional similarity. Furthermore, our maximum-likelihood approach allows learned parameters to be used to visualize and evaluate the evidence of novel predictions, aiding human judgment of their credibility. Conclusions Our approach integrates multiple data sources with supervised learning to create a weighted composite protein network, and uses six clustering algorithms with an aggregative clustering strategy to

  8. Protein complex prediction in large ontology attributed protein-protein interaction networks.

    Science.gov (United States)

    Zhang, Yijia; Lin, Hongfei; Yang, Zhihao; Wang, Jian; Li, Yanpeng; Xu, Bo

    2013-01-01

    Protein complexes are important for unraveling the secrets of cellular organization and function. Many computational approaches have been developed to predict protein complexes in protein-protein interaction (PPI) networks. However, most existing approaches focus mainly on the topological structure of PPI networks, and largely ignore the gene ontology (GO) annotation information. In this paper, we constructed ontology attributed PPI networks with PPI data and GO resource. After constructing ontology attributed networks, we proposed a novel approach called CSO (clustering based on network structure and ontology attribute similarity). Structural information and GO attribute information are complementary in ontology attributed networks. CSO can effectively take advantage of the correlation between frequent GO annotation sets and the dense subgraph for protein complex prediction. Our proposed CSO approach was applied to four different yeast PPI data sets and predicted many well-known protein complexes. The experimental results showed that CSO was valuable in predicting protein complexes and achieved state-of-the-art performance.

  9. Sub-kilometer Numerical Weather Prediction in complex urban areas

    Science.gov (United States)

    Leroyer, S.; Bélair, S.; Husain, S.; Vionnet, V.

    2013-12-01

    A Sub-kilometer atmospheric modeling system with grid-spacings of 2.5 km, 1 km and 250 m and including urban processes is currently being developed at the Meteorological Service of Canada (MSC) in order to provide more accurate weather forecasts at the city scale. Atmospheric lateral boundary conditions are provided with the 15-km Canadian Regional Deterministic Prediction System (RDPS). Surface physical processes are represented with the Town Energy Balance (TEB) model for the built-up covers and with the Interactions between the Surface, Biosphere, and Atmosphere (ISBA) land surface model for the natural covers. In this study, several research experiments over large metropolitan areas and using observational networks at the urban scale are presented, with a special emphasis on the representation of local atmospheric circulations and their impact on extreme weather forecasting. First, numerical simulations are performed over the Vancouver metropolitan area during a summertime Intense Observing Period (IOP of 14-15 August 2008) of the Environmental Prediction in Canadian Cities (EPiCC) observational network. The influence of the horizontal resolution on the fine-scale representation of the sea-breeze development over the city is highlighted (Leroyer et al., 2013). Then severe storms cases occurring in summertime within the Greater Toronto Area (GTA) are simulated. In view of supporting the 2015 PanAmerican and Para-Pan games to be hold in GTA, a dense observational network has been recently deployed over this region to support model evaluations at the urban and meso scales. In particular, simulations are conducted for the case of 8 July 2013 when exceptional rainfalls were recorded. Leroyer, S., S. Bélair, J. Mailhot, S.Z. Husain, 2013: Sub-kilometer Numerical Weather Prediction in an Urban Coastal Area: A case study over the Vancouver Metropolitan Area, submitted to Journal of Applied Meteorology and Climatology.

  10. Simple neural substrate predicts complex rhythmic structure in duetting birds

    Science.gov (United States)

    Amador, Ana; Trevisan, M. A.; Mindlin, G. B.

    2005-09-01

    Horneros (Furnarius Rufus) are South American birds well known for their oven-looking nests and their ability to sing in couples. Previous work has analyzed the rhythmic organization of the duets, unveiling a mathematical structure behind the songs. In this work we analyze in detail an extended database of duets. The rhythms of the songs are compatible with the dynamics presented by a wide class of dynamical systems: forced excitable systems. Compatible with this nonlinear rule, we build a biologically inspired model for how the neural and the anatomical elements may interact to produce the observed rhythmic patterns. This model allows us to synthesize songs presenting the acoustic and rhythmic features observed in real songs. We also make testable predictions in order to support our hypothesis.

  11. A Commentary on Pitfalls of Predicting Complex Traits From SNP's

    DEFF Research Database (Denmark)

    de los Campos, Gustavo; Sorensen, Daniel

    2013-01-01

    As stated by Wray and co-authors1, knowing the proportion of variance of a trait that is explained by regression on markers in the population (h2M) is relevant because, in principle, h2M represents the maximum prediction accuracy (R2TST) that is achievable in testing (TST) data if marker effects...... of h2M (Ref. 5), conseqeuenty, it is not obvious that R2TST can achieve values equal to the finite sample estimate of h2G-BLUP. In a recent article5, we studied the R2TST of G-BLUP and its relationship with h2G-BLUP. We show analytically that mis-specification of the training–testing (TRN–TST) genomic...

  12. The effects of model and data complexity on predictions from species distributions models

    DEFF Research Database (Denmark)

    García-Callejas, David; Bastos, Miguel

    2016-01-01

    How complex does a model need to be to provide useful predictions is a matter of continuous debate across environmental sciences. In the species distributions modelling literature, studies have demonstrated that more complex models tend to provide better fits. However, studies have also shown...... that predictive performance does not always increase with complexity. Testing of species distributions models is challenging because independent data for testing are often lacking, but a more general problem is that model complexity has never been formally described in such studies. Here, we systematically...

  13. An integrative and applicable phylogenetic footprinting framework for cis-regulatory motifs identification in prokaryotic genomes.

    Science.gov (United States)

    Liu, Bingqiang; Zhang, Hanyuan; Zhou, Chuan; Li, Guojun; Fennell, Anne; Wang, Guanghui; Kang, Yu; Liu, Qi; Ma, Qin

    2016-08-09

    Phylogenetic footprinting is an important computational technique for identifying cis-regulatory motifs in orthologous regulatory regions from multiple genomes, as motifs tend to evolve slower than their surrounding non-functional sequences. Its application, however, has several difficulties for optimizing the selection of orthologous data and reducing the false positives in motif prediction. Here we present an integrative phylogenetic footprinting framework for accurate motif predictions in prokaryotic genomes (MP(3)). The framework includes a new orthologous data preparation procedure, an additional promoter scoring and pruning method and an integration of six existing motif finding algorithms as basic motif search engines. Specifically, we collected orthologous genes from available prokaryotic genomes and built the orthologous regulatory regions based on sequence similarity of promoter regions. This procedure made full use of the large-scale genomic data and taxonomy information and filtered out the promoters with limited contribution to produce a high quality orthologous promoter set. The promoter scoring and pruning is implemented through motif voting by a set of complementary predicting tools that mine as many motif candidates as possible and simultaneously eliminate the effect of random noise. We have applied the framework to Escherichia coli k12 genome and evaluated the prediction performance through comparison with seven existing programs. This evaluation was systematically carried out at the nucleotide and binding site level, and the results showed that MP(3) consistently outperformed other popular motif finding tools. We have integrated MP(3) into our motif identification and analysis server DMINDA, allowing users to efficiently identify and analyze motifs in 2,072 completely sequenced prokaryotic genomes. The performance evaluation indicated that MP(3) is effective for predicting regulatory motifs in prokaryotic genomes. Its application may enhance

  14. Prediction of Thermal Transport Properties of Materials with Microstructural Complexity

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Youping

    2017-10-10

    This project aims at overcoming the major obstacle standing in the way of progress in dynamic multiscale simulation, which is the lack of a concurrent atomistic-continuum method that allows phonons, heat and defects to pass through the atomistic-continuum interface. The research has led to the development of a concurrent atomistic-continuum (CAC) methodology for multiscale simulations of materials microstructural, mechanical and thermal transport behavior. Its efficacy has been tested and demonstrated through simulations of dislocation dynamics and phonon transport coupled with microstructural evolution in a variety of materials and through providing visual evidences of the nature of phonon transport, such as showing the propagation of heat pulses in single and polycrystalline solids is partially ballistic and partially diffusive. In addition to providing understanding on phonon scattering with phase interface and with grain boundaries, the research has contributed a multiscale simulation tool for understanding of the behavior of complex materials and has demonstrated the capability of the tool in simulating the dynamic, in situ experimental studies of nonequilibrium transient transport processes in material samples that are at length scales typically inaccessible by atomistically resolved methods.

  15. Exploitation of complex network topology for link prediction in biological interactomes

    KAUST Repository

    Alanis Lobato, Gregorio

    2014-01-01

    In this work, we propose three novel and powerful approaches for the prediction of interactions in biological networks and conclude that it is possible to mine the topology of these complex system representations and produce reliable

  16. Ganglion cell complex scan in the early prediction of glaucoma.

    Science.gov (United States)

    Ganekal, S

    2012-01-01

    To compare the macular ganglion cell complex (GCC) with peripapillary retinal fiber layer (RNFL) thickness map in glaucoma suspects and patients. Forty participants (20 glaucoma suspects and 20 glaucoma patients) were enrolled. Macular GCC and RNFL thickness maps were performed in both eyes of each participant in the same visit. The sensitivity and specificity of a color code less than 5% (red or yellow) for glaucoma diagnosis were calculated. Standard Automated Perimetry was performed with the Octopus 3.1.1 Dynamic 24-2 program. The statistical analysis was performed with the SPSS 10.1 (SPSS Inc. Chicago, IL, EUA). Results were expressed as mean +/- standard deviation and a p value of 0.05 or less was considered significant. Provide absolute numbers of these findings with their units of measurement. There was a statistically significant difference in average RNFL thickness (p=0.004), superior RNFL thickness (p=0.006), inferior RNFL thickness (p=0.0005) and average GCC (p=0.03) between the suspects and glaucoma patients. There was no difference in optic disc area (p=0.35) and vertical cup/disc ratio (p=0.234) in both groups. While 38% eyes had an abnormal GCC and 13% had an abnormal RNFL thickness in the glaucoma suspect group, 98% had an abnormal GCC and 90% had an abnormal RNFL thickness in the glaucoma group. The ability to diagnose glaucoma with macular GCC thickness is comparable to that with peripapillary RNFL thickness . Macular GCC thickness measurements may be a good alternative or a complementary measurement to RNFL thickness assessment in the clinical evaluation of glaucoma. © NEPjOPH.

  17. Efficient motif finding algorithms for large-alphabet inputs

    Directory of Open Access Journals (Sweden)

    Pavlovic Vladimir

    2010-10-01

    Full Text Available Abstract Background We consider the problem of identifying motifs, recurring or conserved patterns, in the biological sequence data sets. To solve this task, we present a new deterministic algorithm for finding patterns that are embedded as exact or inexact instances in all or most of the input strings. Results The proposed algorithm (1 improves search efficiency compared to existing algorithms, and (2 scales well with the size of alphabet. On a synthetic planted DNA motif finding problem our algorithm is over 10× more efficient than MITRA, PMSPrune, and RISOTTO for long motifs. Improvements are orders of magnitude higher in the same setting with large alphabets. On benchmark TF-binding site problems (FNP, CRP, LexA we observed reduction in running time of over 12×, with high detection accuracy. The algorithm was also successful in rapidly identifying protein motifs in Lipocalin, Zinc metallopeptidase, and supersecondary structure motifs for Cadherin and Immunoglobin families. Conclusions Our algorithm reduces computational complexity of the current motif finding algorithms and demonstrate strong running time improvements over existing exact algorithms, especially in important and difficult cases of large-alphabet sequences.

  18. An experimental test of a fundamental food web motif.

    Science.gov (United States)

    Rip, Jason M K; McCann, Kevin S; Lynn, Denis H; Fawcett, Sonia

    2010-06-07

    Large-scale changes to the world's ecosystem are resulting in the deterioration of biostructure-the complex web of species interactions that make up ecological communities. A difficult, yet crucial task is to identify food web structures, or food web motifs, that are the building blocks of this baroque network of interactions. Once identified, these food web motifs can then be examined through experiments and theory to provide mechanistic explanations for how structure governs ecosystem stability. Here, we synthesize recent ecological research to show that generalist consumers coupling resources with different interaction strengths, is one such motif. This motif amazingly occurs across an enormous range of spatial scales, and so acts to distribute coupled weak and strong interactions throughout food webs. We then perform an experiment that illustrates the importance of this motif to ecological stability. We find that weak interactions coupled to strong interactions by generalist consumers dampen strong interaction strengths and increase community stability. This study takes a critical step by isolating a common food web motif and through clear, experimental manipulation, identifies the fundamental stabilizing consequences of this structure for ecological communities.

  19. BEAM web server: a tool for structural RNA motif discovery.

    Science.gov (United States)

    Pietrosanto, Marco; Adinolfi, Marta; Casula, Riccardo; Ausiello, Gabriele; Ferrè, Fabrizio; Helmer-Citterich, Manuela

    2018-03-15

    RNA structural motif finding is a relevant problem that becomes computationally hard when working on high-throughput data (e.g. eCLIP, PAR-CLIP), often represented by thousands of RNA molecules. Currently, the BEAM server is the only web tool capable to handle tens of thousands of RNA in input with a motif discovery procedure that is only limited by the current secondary structure prediction accuracies. The recently developed method BEAM (BEAr Motifs finder) can analyze tens of thousands of RNA molecules and identify RNA secondary structure motifs associated to a measure of their statistical significance. BEAM is extremely fast thanks to the BEAR encoding that transforms each RNA secondary structure in a string of characters. BEAM also exploits the evolutionary knowledge contained in a substitution matrix of secondary structure elements, extracted from the RFAM database of families of homologous RNAs. The BEAM web server has been designed to streamline data pre-processing by automatically handling folding and encoding of RNA sequences, giving users a choice for the preferred folding program. The server provides an intuitive and informative results page with the list of secondary structure motifs identified, the logo of each motif, its significance, graphic representation and information about its position in the RNA molecules sharing it. The web server is freely available at http://beam.uniroma2.it/ and it is implemented in NodeJS and Python with all major browsers supported. marco.pietrosanto@uniroma2.it. Supplementary data are available at Bioinformatics online.

  20. Finding a Leucine in a Haystack: Searching the Proteome for ambigous Leucine-Aspartic Acid motifs

    KAUST Repository

    Arold, Stefan T.

    2016-01-25

    Leucine-aspartic acid (LD) motifs are short helical protein-protein interaction motifs involved in cell motility, survival and communication. LD motif interactions are also implicated in cancer metastasis and are targeted by several viruses. LD motifs are notoriously difficult to detect because sequence pattern searches lead to an excessively high number of false positives. Hence, despite 20 years of research, only six LD motif–containing proteins are known in humans, three of which are close homologues of the paxillin family. To enable the proteome-wide discovery of LD motifs, we developed LD Motif Finder (LDMF), a web tool based on machine learning that combines sequence information with structural predictions to detect LD motifs with high accuracy. LDMF predicted 13 new LD motifs in humans. Using biophysical assays, we experimentally confirmed in vitro interactions for four novel LD motif proteins. Thus, LDMF allows proteome-wide discovery of LD motifs, despite a highly ambiguous sequence pattern. Functional implications will be discussed.

  1. Pseudoracemic amino acid complexes: blind predictions for flexible two-component crystals.

    Science.gov (United States)

    Görbitz, Carl Henrik; Dalhus, Bjørn; Day, Graeme M

    2010-08-14

    Ab initio prediction of the crystal packing in complexes between two flexible molecules is a particularly challenging computational chemistry problem. In this work we present results of single crystal structure determinations as well as theoretical predictions for three 1 ratio 1 complexes between hydrophobic l- and d-amino acids (pseudoracemates), known from previous crystallographic work to form structures with one of two alternative hydrogen bonding arrangements. These are accurately reproduced in the theoretical predictions together with a series of patterns that have never been observed experimentally. In this bewildering forest of potential polymorphs, hydrogen bonding arrangements and molecular conformations, the theoretical predictions succeeded, for all three complexes, in finding the correct hydrogen bonding pattern. For two of the complexes, the calculations also reproduce the exact space group and side chain orientations in the best ranked predicted structure. This includes one complex for which the observed crystal packing clearly contradicted previous experience based on experimental data for a substantial number of related amino acid complexes. The results highlight the significant recent advances that have been made in computational methods for crystal structure prediction.

  2. Auditory Brainstem Response to Complex Sounds Predicts Self-Reported Speech-in-Noise Performance

    Science.gov (United States)

    Anderson, Samira; Parbery-Clark, Alexandra; White-Schwoch, Travis; Kraus, Nina

    2013-01-01

    Purpose: To compare the ability of the auditory brainstem response to complex sounds (cABR) to predict subjective ratings of speech understanding in noise on the Speech, Spatial, and Qualities of Hearing Scale (SSQ; Gatehouse & Noble, 2004) relative to the predictive ability of the Quick Speech-in-Noise test (QuickSIN; Killion, Niquette,…

  3. Evolutionarily conserved bias of amino-acid usage refines the definition of PDZ-binding motif

    Directory of Open Access Journals (Sweden)

    Launey Thomas

    2011-06-01

    Full Text Available Abstract Background The interactions between PDZ (PSD-95, Dlg, ZO-1 domains and PDZ-binding motifs play central roles in signal transductions within cells. Proteins with PDZ domains bind to PDZ-binding motifs almost exclusively when the motifs are located at the carboxyl (C- terminal ends of their binding partners. However, it remains little explored whether PDZ-binding motifs show any preferential location at the C-terminal ends of proteins, at genome-level. Results Here, we examined the distribution of the type-I (x-x-S/T-x-I/L/V or type-II (x-x-V-x-I/V PDZ-binding motifs in proteins encoded in the genomes of five different species (human, mouse, zebrafish, fruit fly and nematode. We first established that these PDZ-binding motifs are indeed preferentially present at their C-terminal ends. Moreover, we found specific amino acid (AA bias for the 'x' positions in the motifs at the C-terminal ends. In general, hydrophilic AAs were favored. Our genomics-based findings confirm and largely extend the results of previous interaction-based studies, allowing us to propose refined consensus sequences for all of the examined PDZ-binding motifs. An ontological analysis revealed that the refined motifs are functionally relevant since a large fraction of the proteins bearing the motif appear to be involved in signal transduction. Furthermore, co-precipitation experiments confirmed two new protein interactions predicted by our genomics-based approach. Finally, we show that influenza virus pathogenicity can be correlated with PDZ-binding motif, with high-virulence viral proteins bearing a refined PDZ-binding motif. Conclusions Our refined definition of PDZ-binding motifs should provide important clues for identifying functional PDZ-binding motifs and proteins involved in signal transduction.

  4. Improved prediction of MHC class I and class II epitopes using a novel Gibbs sampling approach

    DEFF Research Database (Denmark)

    Nielsen, Morten; Lundegaard, Claus; Worning, Peder

    2004-01-01

    Prediction of which peptides will bind a specific major histocompatibility complex (MHC) constitutes an important step in identifying potential T-cell epitopes suitable as vaccine candidates. MHC class II binding peptides have a broad length distribution complicating such predictions. Thus......, identifying the correct alignment is a crucial part of identifying the core of an MHC class II binding motif. In this context, we wish to describe a novel Gibbs motif sampler method ideally suited for recognizing such weak sequence motifs. The method is based on the Gibbs sampling method, and it incorporates...

  5. Low-dimensional morphospace of topological motifs in human fMRI brain networks

    Directory of Open Access Journals (Sweden)

    Sarah E. Morgan

    2018-06-01

    Full Text Available We present a low-dimensional morphospace of fMRI brain networks, where axes are defined in a data-driven manner based on the network motifs. The morphospace allows us to identify the key variations in healthy fMRI networks in terms of their underlying motifs, and we observe that two principal components (PCs can account for 97% of the motif variability. The first PC of the motif distribution is correlated with efficiency and inversely correlated with transitivity. Hence this axis approximately conforms to the well-known economical small-world trade-off between integration and segregation in brain networks. Finally, we show that the economical clustering generative model proposed by Vértes et al. (2012 can approximately reproduce the motif morphospace of the real fMRI brain networks, in contrast to other generative models. Overall, the motif morphospace provides a powerful way to visualize the relationships between network properties and to investigate generative or constraining factors in the formation of complex human brain functional networks. Motifs have been described as the building blocks of complex networks. Meanwhile, a morphospace allows networks to be placed in a common space and can reveal the relationships between different network properties and elucidate the driving forces behind network topology. We combine the concepts of motifs and morphospaces to create the first motif morphospace of fMRI brain networks. Crucially, the morphospace axes are defined by the motifs, in a data-driven manner. We observe strong correlations between the networks’ positions in morphospace and their global topological properties, suggesting that motif morphospaces are a powerful way to capture the topology of networks in a low-dimensional space and to compare generative models of brain networks. Motif morphospaces could also be used to study other complex networks’ topologies.

  6. Predicting co-complexed protein pairs using genomic and proteomic data integration

    Directory of Open Access Journals (Sweden)

    King Oliver D

    2004-04-01

    Full Text Available Abstract Background Identifying all protein-protein interactions in an organism is a major objective of proteomics. A related goal is to know which protein pairs are present in the same protein complex. High-throughput methods such as yeast two-hybrid (Y2H and affinity purification coupled with mass spectrometry (APMS have been used to detect interacting proteins on a genomic scale. However, both Y2H and APMS methods have substantial false-positive rates. Aside from high-throughput interaction screens, other gene- or protein-pair characteristics may also be informative of physical interaction. Therefore it is desirable to integrate multiple datasets and utilize their different predictive value for more accurate prediction of co-complexed relationship. Results Using a supervised machine learning approach – probabilistic decision tree, we integrated high-throughput protein interaction datasets and other gene- and protein-pair characteristics to predict co-complexed pairs (CCP of proteins. Our predictions proved more sensitive and specific than predictions based on Y2H or APMS methods alone or in combination. Among the top predictions not annotated as CCPs in our reference set (obtained from the MIPS complex catalogue, a significant fraction was found to physically interact according to a separate database (YPD, Yeast Proteome Database, and the remaining predictions may potentially represent unknown CCPs. Conclusions We demonstrated that the probabilistic decision tree approach can be successfully used to predict co-complexed protein (CCP pairs from other characteristics. Our top-scoring CCP predictions provide testable hypotheses for experimental validation.

  7. CMD: A Database to Store the Bonding States of Cysteine Motifs with Secondary Structures

    Directory of Open Access Journals (Sweden)

    Hamed Bostan

    2012-01-01

    Full Text Available Computational approaches to the disulphide bonding state and its connectivity pattern prediction are based on various descriptors. One descriptor is the amino acid sequence motifs flanking the cysteine residue motifs. Despite the existence of disulphide bonding information in many databases and applications, there is no complete reference and motif query available at the moment. Cysteine motif database (CMD is the first online resource that stores all cysteine residues, their flanking motifs with their secondary structure, and propensity values assignment derived from the laboratory data. We extracted more than 3 million cysteine motifs from PDB and UniProt data, annotated with secondary structure assignment, propensity value assignment, and frequency of occurrence and coefficiency of their bonding status. Removal of redundancies generated 15875 unique flanking motifs that are always bonded and 41577 unique patterns that are always nonbonded. Queries are based on the protein ID, FASTA sequence, sequence motif, and secondary structure individually or in batch format using the provided APIs that allow remote users to query our database via third party software and/or high throughput screening/querying. The CMD offers extensive information about the bonded, free cysteine residues, and their motifs that allows in-depth characterization of the sequence motif composition.

  8. Improving prediction of heterodimeric protein complexes using combination with pairwise kernel.

    Science.gov (United States)

    Ruan, Peiying; Hayashida, Morihiro; Akutsu, Tatsuya; Vert, Jean-Philippe

    2018-02-19

    Since many proteins become functional only after they interact with their partner proteins and form protein complexes, it is essential to identify the sets of proteins that form complexes. Therefore, several computational methods have been proposed to predict complexes from the topology and structure of experimental protein-protein interaction (PPI) network. These methods work well to predict complexes involving at least three proteins, but generally fail at identifying complexes involving only two different proteins, called heterodimeric complexes or heterodimers. There is however an urgent need for efficient methods to predict heterodimers, since the majority of known protein complexes are precisely heterodimers. In this paper, we use three promising kernel functions, Min kernel and two pairwise kernels, which are Metric Learning Pairwise Kernel (MLPK) and Tensor Product Pairwise Kernel (TPPK). We also consider the normalization forms of Min kernel. Then, we combine Min kernel or its normalization form and one of the pairwise kernels by plugging. We applied kernels based on PPI, domain, phylogenetic profile, and subcellular localization properties to predicting heterodimers. Then, we evaluate our method by employing C-Support Vector Classification (C-SVC), carrying out 10-fold cross-validation, and calculating the average F-measures. The results suggest that the combination of normalized-Min-kernel and MLPK leads to the best F-measure and improved the performance of our previous work, which had been the best existing method so far. We propose new methods to predict heterodimers, using a machine learning-based approach. We train a support vector machine (SVM) to discriminate interacting vs non-interacting protein pairs, based on informations extracted from PPI, domain, phylogenetic profiles and subcellular localization. We evaluate in detail new kernel functions to encode these data, and report prediction performance that outperforms the state-of-the-art.

  9. SSTRAP: A computational model for genomic motif discovery ...

    African Journals Online (AJOL)

    Computational methods can potentially provide high-quality prediction of biological molecules such as DNA binding sites and Transcription factors and therefore reduce the time needed for experimental verification and challenges associated with experimental methods. These biological molecules or motifs have significant ...

  10. Presence of a consensus DNA motif at nearby DNA sequence of the mutation susceptible CG nucleotides.

    Science.gov (United States)

    Chowdhury, Kaushik; Kumar, Suresh; Sharma, Tanu; Sharma, Ankit; Bhagat, Meenakshi; Kamai, Asangla; Ford, Bridget M; Asthana, Shailendra; Mandal, Chandi C

    2018-01-10

    Complexity in tissues affected by cancer arises from somatic mutations and epigenetic modifications in the genome. The mutation susceptible hotspots present within the genome indicate a non-random nature and/or a position specific selection of mutation. An association exists between the occurrence of mutations and epigenetic DNA methylation. This study is primarily aimed at determining mutation status, and identifying a signature for predicting mutation prone zones of tumor suppressor (TS) genes. Nearby sequences from the top five positions having a higher mutation frequency in each gene of 42 TS genes were selected from a cosmic database and were considered as mutation prone zones. The conserved motifs present in the mutation prone DNA fragments were identified. Molecular docking studies were done to determine putative interactions between the identified conserved motifs and enzyme methyltransferase DNMT1. Collective analysis of 42 TS genes found GC as the most commonly replaced and AT as the most commonly formed residues after mutation. Analysis of the top 5 mutated positions of each gene (210 DNA segments for 42 TS genes) identified that CG nucleotides of the amino acid codons (e.g., Arginine) are most susceptible to mutation, and found a consensus DNA "T/AGC/GAGGA/TG" sequence present in these mutation prone DNA segments. Similar to TS genes, analysis of 54 oncogenes not only found CG nucleotides of the amino acid Arg as the most susceptible to mutation, but also identified the presence of similar consensus DNA motifs in the mutation prone DNA fragments (270 DNA segments for 54 oncogenes) of oncogenes. Docking studies depicted that, upon binding of DNMT1 methylates to this consensus DNA motif (C residues of CpG islands), mutation was likely to occur. Thus, this study proposes that DNMT1 mediated methylation in chromosomal DNA may decrease if a foreign DNA segment containing this consensus sequence along with CG nucleotides is exogenously introduced to dividing

  11. Promoter Motifs in NCLDVs: An Evolutionary Perspective

    Science.gov (United States)

    Oliveira, Graziele Pereira; Andrade, Ana Cláudia dos Santos Pereira; Rodrigues, Rodrigo Araújo Lima; Arantes, Thalita Souza; Boratto, Paulo Victor Miranda; Silva, Ludmila Karen dos Santos; Dornas, Fábio Pio; Trindade, Giliane de Souza; Drumond, Betânia Paiva; La Scola, Bernard; Kroon, Erna Geessien; Abrahão, Jônatas Santos

    2017-01-01

    For many years, gene expression in the three cellular domains has been studied in an attempt to discover sequences associated with the regulation of the transcription process. Some specific transcriptional features were described in viruses, although few studies have been devoted to understanding the evolutionary aspects related to the spread of promoter motifs through related viral families. The discovery of giant viruses and the proposition of the new viral order Megavirales that comprise a monophyletic group, named nucleo-cytoplasmic large DNA viruses (NCLDV), raised new questions in the field. Some putative promoter sequences have already been described for some NCLDV members, bringing new insights into the evolutionary history of these complex microorganisms. In this review, we summarize the main aspects of the transcription regulation process in the three domains of life, followed by a systematic description of what is currently known about promoter regions in several NCLDVs. We also discuss how the analysis of the promoter sequences could bring new ideas about the giant viruses’ evolution. Finally, considering a possible common ancestor for the NCLDV group, we discussed possible promoters’ evolutionary scenarios and propose the term “MEGA-box” to designate an ancestor promoter motif (‘TATATAAAATTGA’) that could be evolved gradually by nucleotides’ gain and loss and point mutations. PMID:28117683

  12. Promoter Motifs in NCLDVs: An Evolutionary Perspective

    Directory of Open Access Journals (Sweden)

    Graziele Pereira Oliveira

    2017-01-01

    Full Text Available For many years, gene expression in the three cellular domains has been studied in an attempt to discover sequences associated with the regulation of the transcription process. Some specific transcriptional features were described in viruses, although few studies have been devoted to understanding the evolutionary aspects related to the spread of promoter motifs through related viral families. The discovery of giant viruses and the proposition of the new viral order Megavirales that comprise a monophyletic group, named nucleo-cytoplasmic large DNA viruses (NCLDV, raised new questions in the field. Some putative promoter sequences have already been described for some NCLDV members, bringing new insights into the evolutionary history of these complex microorganisms. In this review, we summarize the main aspects of the transcription regulation process in the three domains of life, followed by a systematic description of what is currently known about promoter regions in several NCLDVs. We also discuss how the analysis of the promoter sequences could bring new ideas about the giant viruses’ evolution. Finally, considering a possible common ancestor for the NCLDV group, we discussed possible promoters’ evolutionary scenarios and propose the term “MEGA-box” to designate an ancestor promoter motif (‘TATATAAAATTGA’ that could be evolved gradually by nucleotides’ gain and loss and point mutations.

  13. Link-Prediction Enhanced Consensus Clustering for Complex Networks (Open Access)

    Science.gov (United States)

    2016-05-20

    RESEARCH ARTICLE Link-Prediction Enhanced Consensus Clustering for Complex Networks Matthew Burgess1*, Eytan Adar1,2, Michael Cafarella1 1Computer...consensus clustering algorithm to enhance community detection on incomplete networks. Our framework utilizes existing community detection algorithms that...types of complex networks exhibit community structure: groups of highly connected nodes. Communities or clusters often reflect nodes that share similar

  14. Predicting complex acute wound healing in patients from a wound expertise centre registry: a prognostic study

    OpenAIRE

    Ubbink, Dirk T; Lindeboom, Robert; Eskes, Anne M; Brull, Huub; Legemate, Dink A; Vermeulen, Hester

    2015-01-01

    It is important for caregivers and patients to know which wounds are at risk of prolonged wound healing to enable timely communication and treatment. Available prognostic models predict wound healing in chronic ulcers, but not in acute wounds, that is, originating after trauma or surgery. We developed a model to detect which factors can predict (prolonged) healing of complex acute wounds in patients treated in a large wound expertise centre (WEC). Using Cox and linear regression analyses, we ...

  15. NetMHCcons: a consensus method for the major histocompatibility complex class I predictions

    DEFF Research Database (Denmark)

    Karosiene, Edita; Lundegaard, Claus; Lund, Ole

    2012-01-01

    A key role in cell-mediated immunity is dedicated to the major histocompatibility complex (MHC) molecules that bind peptides for presentation on the cell surface. Several in silico methods capable of predicting peptide binding to MHC class I have been developed. The accuracy of these methods depe...... at www.cbs.dtu.dk/services/NetMHCcons, and allows the user in an automatic manner to obtain the most accurate predictions for any given MHC molecule....

  16. Binding properties of SUMO-interacting motifs (SIMs) in yeast.

    Science.gov (United States)

    Jardin, Christophe; Horn, Anselm H C; Sticht, Heinrich

    2015-03-01

    Small ubiquitin-like modifier (SUMO) conjugation and interaction play an essential role in many cellular processes. A large number of yeast proteins is known to interact non-covalently with SUMO via short SUMO-interacting motifs (SIMs), but the structural details of this interaction are yet poorly characterized. In the present work, sequence analysis of a large dataset of 148 yeast SIMs revealed the existence of a hydrophobic core binding motif and a preference for acidic residues either within or adjacent to the core motif. Thus the sequence properties of yeast SIMs are highly similar to those described for human. Molecular dynamics simulations were performed to investigate the binding preferences for four representative SIM peptides differing in the number and distribution of acidic residues. Furthermore, the relative stability of two previously observed alternative binding orientations (parallel, antiparallel) was assessed. For all SIMs investigated, the antiparallel binding mode remained stable in the simulations and the SIMs were tightly bound via their hydrophobic core residues supplemented by polar interactions of the acidic residues. In contrary, the stability of the parallel binding mode is more dependent on the sequence features of the SIM motif like the number and position of acidic residues or the presence of additional adjacent interaction motifs. This information should be helpful to enhance the prediction of SIMs and their binding properties in different organisms to facilitate the reconstruction of the SUMO interactome.

  17. Design of experiments and springback prediction for AHSS automotive components with complex geometry

    International Nuclear Information System (INIS)

    Asgari, A.; Pereira, M.; Rolfe, B.; Dingle, M.; Hodgson, P.

    2005-01-01

    With the drive towards implementing Advanced High Strength Steels (AHSS) in the automotive industry; stamping engineers need to quickly answer questions about forming these strong materials into elaborate shapes. Commercially available codes have been successfully used to accurately predict formability, thickness and strains in complex parts. However, springback and twisting are still challenging subjects in numerical simulations of AHSS components. Design of Experiments (DOE) has been used in this paper to study the sensitivity of the implicit and explicit numerical results with respect to certain arrays of user input parameters in the forming of an AHSS component. Numerical results were compared to experimental measurements of the parts stamped in an industrial production line. The forming predictions of the implicit and explicit codes were in good agreement with the experimental measurements for the conventional steel grade, while lower accuracies were observed for the springback predictions. The forming predictions of the complex component with an AHSS material were also in good correlation with the respective experimental measurements. However, much lower accuracies were observed in its springback predictions. The number of integration points through the thickness and tool offset were found to be of significant importance, while coefficient of friction and Young's modulus (modeling input parameters) have no significant effect on the accuracy of the predictions for the complex geometry

  18. Pierced Lasso Bundles are a new class of knot-like motifs.

    Directory of Open Access Journals (Sweden)

    Ellinor Haglund

    2014-06-01

    Full Text Available A four-helix bundle is a well-characterized motif often used as a target for designed pharmaceutical therapeutics and nutritional supplements. Recently, we discovered a new structural complexity within this motif created by a disulphide bridge in the long-chain helical bundle cytokine leptin. When oxidized, leptin contains a disulphide bridge creating a covalent-loop through which part of the polypeptide chain is threaded (as seen in knotted proteins. We explored whether other proteins contain a similar intriguing knot-like structure as in leptin and discovered 11 structurally homologous proteins in the PDB. We call this new helical family class the Pierced Lasso Bundle (PLB and the knot-like threaded structural motif a Pierced Lasso (PL. In the current study, we use structure-based simulation to investigate the threading/folding mechanisms for all the PLBs along with three unthreaded homologs as the covalent loop (or lasso in leptin is important in folding dynamics and activity. We find that the presence of a small covalent loop leads to a mechanism where structural elements slipknot to thread through the covalent loop. Larger loops use a piercing mechanism where the free terminal plugs through the covalent loop. Remarkably, the position of the loop as well as its size influences the native state dynamics, which can impact receptor binding and biological activity. This previously unrecognized complexity of knot-like proteins within the helical bundle family comprises a completely new class within the knot family, and the hidden complexity we unraveled in the PLBs is expected to be found in other protein structures outside the four-helix bundles. The insights gained here provide critical new elements for future investigation of this emerging class of proteins, where function and the energetic landscape can be controlled by hidden topology, and should be take into account in ab initio predictions of newly identified protein targets.

  19. A sialoreceptor binding motif in the Mycoplasma synoviae adhesin VlhA.

    Directory of Open Access Journals (Sweden)

    Meghan May

    Full Text Available Mycoplasma synoviae depends on its adhesin VlhA to mediate cytadherence to sialylated host cell receptors. Allelic variants of VlhA arise through recombination between an assemblage of promoterless vlhA pseudogenes and a single transcription promoter site, creating lineages of M. synoviae that each express a different vlhA allele. The predicted full-length VlhA sequences adjacent to the promoter of nine lineages of M. synoviae varying in avidity of cytadherence were aligned with that of the reference strain MS53 and with a 60-a.a. hemagglutinating VlhA C-terminal fragment from a Tunisian lineage of strain WVU1853(T. Seven different sequence variants of an imperfectly conserved, single-copy, 12-a.a. candidate cytadherence motif were evident amid the flanking variable residues of the 11 total sequences examined. The motif was predicted to adopt a short hairpin structure in a low-complexity region near the C-terminus of VlhA. Biotinylated synthetic oligopeptides representing four selected variants of the 12-a.a. motif, with the whole synthesized 60-a.a. fragment as a positive control, differed (P<0.01 in the extent they bound to chicken erythrocyte membranes. All bound to a greater extent (P<0.01 than scrambled or irrelevant VlhA domain negative control peptides did. Experimentally introduced branched-chain amino acid (BCAA substitutions Val3Ile and Leu7Ile did not significantly alter binding, whereas fold-destabilizing substitutions Thr4Gly and Ala9Gly tended to reduce it (P<0.05. Binding was also reduced to background levels (P<0.01 when the peptides were exposed to desialylated membranes, or were pre-saturated with free sialic acid before exposure to untreated membranes. From this evidence we conclude that the motif P-X-(BCAA-X-F-X-(BCAA-X-A-K-X-G binds sialic acid and likely mediates VlhA-dependent M. synoviae attachment to host cells. This conserved mechanism retains the potential for fine-scale rheostasis in binding avidity, which could be a

  20. Host Genome Influence on Gut Microbial Composition and Microbial Prediction of Complex Traits in Pigs.

    Science.gov (United States)

    Camarinha-Silva, Amelia; Maushammer, Maria; Wellmann, Robin; Vital, Marius; Preuss, Siegfried; Bennewitz, Jörn

    2017-07-01

    The aim of the present study was to analyze the interplay between gastrointestinal tract (GIT) microbiota, host genetics, and complex traits in pigs using extended quantitative-genetic methods. The study design consisted of 207 pigs that were housed and slaughtered under standardized conditions, and phenotyped for daily gain, feed intake, and feed conversion rate. The pigs were genotyped with a standard 60 K SNP chip. The GIT microbiota composition was analyzed by 16S rRNA gene amplicon sequencing technology. Eight from 49 investigated bacteria genera showed a significant narrow sense host heritability, ranging from 0.32 to 0.57. Microbial mixed linear models were applied to estimate the microbiota variance for each complex trait. The fraction of phenotypic variance explained by the microbial variance was 0.28, 0.21, and 0.16 for daily gain, feed conversion, and feed intake, respectively. The SNP data and the microbiota composition were used to predict the complex traits using genomic best linear unbiased prediction (G-BLUP) and microbial best linear unbiased prediction (M-BLUP) methods, respectively. The prediction accuracies of G-BLUP were 0.35, 0.23, and 0.20 for daily gain, feed conversion, and feed intake, respectively. The corresponding prediction accuracies of M-BLUP were 0.41, 0.33, and 0.33. Thus, in addition to SNP data, microbiota abundances are an informative source of complex trait predictions. Since the pig is a well-suited animal for modeling the human digestive tract, M-BLUP, in addition to G-BLUP, might be beneficial for predicting human predispositions to some diseases, and, consequently, for preventative and personalized medicine. Copyright © 2017 by the Genetics Society of America.

  1. Kopi dan Kakao dalam Kreasi Motif Batik Khas Jember

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    Irfa'ina Rohana Salma

    2015-06-01

    Full Text Available ABSTRAK Batik Jember selama ini identik dengan motif daun tembakau. Visualisasi daun tembakau dalam motif Batik Jember cukup lemah, yaitu kurang berkarakter karena motif yang muncul adalah seperti gambar daun pada umumnya. Oleh karena itu perlu diciptakan desain motif batik khas Jember yang sumber inspirasinya digali dari kekayaan alam lainnya dari Jember yang mempunyai bentuk spesifik dan karakteristik sehingga identitas motif bisa didapatkan dengan lebih kuat. Hasil alam khas Jember tersebut adalah kopi dan kakao. Tujuan penciptaan seni ini adalah untuk menghasilkan motif batik  baru yang mempunyai ciri khas Jember. Metode yang digunakan yaitu pengumpulan data, pengamatan mendalam terhadap objek penciptaan, pengkajian sumber inspirasi, pembuatan desain motif, dan perwujudan menjadi batik. Dari penciptaan seni ini berhasil dikreasikan 6 (enam motif batik yaitu: (1 Motif Uwoh Kopi; (2 Motif Godong Kopi;  (3 Motif Ceplok Kakao; (4 Motif Kakao Raja; (5 Motif Kakao Biru; dan (6 Motif Wiji Mukti. Berdasarkan hasil penilaian “Selera Estetika” diketahui bahwa motif yang paling banyak disukai adalah Motif Uwoh Kopi dan Motif Kakao Raja. Kata kunci: Motif Woh Kopi, Motif Godong Kopi, Motif Ceplok Kakao, Motif Kakao Raja, Motif Kakao Biru, Motif Wiji Mukti ABSTRACTBatik Jember is synonymous with tobacco leaf motif. Tobacco leaf shape is quite weak in the visual appearance characterized as that motif emerges like a picture of leaves in general. Therefore, it is necessary to create a distinctive design motif extracted from other natural resources of Jember that have specific shapes and characteristics that can be obtained as the stronger motif identity. The typical natural resources from Jember are coffee and cocoa. The purpose of the creation of this art is to produce the unique, creative and innovative batik and have specific characteristics of Jember. The method used are data collection, observation of the object, reviewing inspiration sources

  2. Purification and functional motifs of the recombinant ATPase of orf virus.

    Science.gov (United States)

    Lin, Fong-Yuan; Chan, Kun-Wei; Wang, Chi-Young; Wong, Min-Liang; Hsu, Wei-Li

    2011-10-01

    Our previous study showed that the recombinant ATPase encoded by the A32L gene of orf virus displayed ATP hydrolysis activity as predicted from its amino acids sequence. This viral ATPase contains four known functional motifs (motifs I-IV) and a novel AYDG motif; they are essential for ATP hydrolysis reaction by binding ATP and magnesium ions. The motifs I and II correspond with the Walker A and B motifs of the typical ATPase, respectively. To examine the biochemical roles of these five conserved motifs, recombinant ATPases of five deletion mutants derived from the Taiping strain were expressed and purified. Their ATPase functions were assayed and compared with those of two wild type strains, Taiping and Nantou isolated in Taiwan. Our results showed that deletions at motifs I-III or IV exhibited lower activity than that of the wild type. Interestingly, deletion of AYDG motif decreased the ATPase activity more significantly than those of motifs I-IV deletions. Divalent ions such as magnesium and calcium were essential for ATPase activity. Moreover, our recombinant proteins of orf virus also demonstrated GTPase activity, though weaker than the original ATPase activity. Copyright © 2011 Elsevier Inc. All rights reserved.

  3. Dissecting protein loops with a statistical scalpel suggests a functional implication of some structural motifs

    Directory of Open Access Journals (Sweden)

    Martin Juliette

    2011-06-01

    Full Text Available Abstract Background One of the strategies for protein function annotation is to search particular structural motifs that are known to be shared by proteins with a given function. Results Here, we present a systematic extraction of structural motifs of seven residues from protein loops and we explore their correspondence with functional sites. Our approach is based on the structural alphabet HMM-SA (Hidden Markov Model - Structural Alphabet, which allows simplification of protein structures into uni-dimensional sequences, and advanced pattern statistics adapted to short sequences. Structural motifs of interest are selected by looking for structural motifs significantly over-represented in SCOP superfamilies in protein loops. We discovered two types of structural motifs significantly over-represented in SCOP superfamilies: (i ubiquitous motifs, shared by several superfamilies and (ii superfamily-specific motifs, over-represented in few superfamilies. A comparison of ubiquitous words with known small structural motifs shows that they contain well-described motifs as turn, niche or nest motifs. A comparison between superfamily-specific motifs and biological annotations of Swiss-Prot reveals that some of them actually correspond to functional sites involved in the binding sites of small ligands, such as ATP/GTP, NAD(P and SAH/SAM. Conclusions Our findings show that statistical over-representation in SCOP superfamilies is linked to functional features. The detection of over-represented motifs within structures simplified by HMM-SA is therefore a promising approach for prediction of functional sites and annotation of uncharacterized proteins.

  4. HKC: An Algorithm to Predict Protein Complexes in Protein-Protein Interaction Networks

    Directory of Open Access Journals (Sweden)

    Xiaomin Wang

    2011-01-01

    Full Text Available With the availability of more and more genome-scale protein-protein interaction (PPI networks, research interests gradually shift to Systematic Analysis on these large data sets. A key topic is to predict protein complexes in PPI networks by identifying clusters that are densely connected within themselves but sparsely connected with the rest of the network. In this paper, we present a new topology-based algorithm, HKC, to detect protein complexes in genome-scale PPI networks. HKC mainly uses the concepts of highest k-core and cohesion to predict protein complexes by identifying overlapping clusters. The experiments on two data sets and two benchmarks show that our algorithm has relatively high F-measure and exhibits better performance compared with some other methods.

  5. Finding low-conductance sets with dense interactions (FLCD) for better protein complex prediction.

    Science.gov (United States)

    Wang, Yijie; Qian, Xiaoning

    2017-03-14

    Intuitively, proteins in the same protein complexes should highly interact with each other but rarely interact with the other proteins in protein-protein interaction (PPI) networks. Surprisingly, many existing computational algorithms do not directly detect protein complexes based on both of these topological properties. Most of them, depending on mathematical definitions of either "modularity" or "conductance", have their own limitations: Modularity has the inherent resolution problem ignoring small protein complexes; and conductance characterizes the separability of complexes but fails to capture the interaction density within complexes. In this paper, we propose a two-step algorithm FLCD (Finding Low-Conductance sets with Dense interactions) to predict overlapping protein complexes with the desired topological structure, which is densely connected inside and well separated from the rest of the networks. First, FLCD detects well-separated subnetworks based on approximating a potential low-conductance set through a personalized PageRank vector from a protein and then solving a mixed integer programming (MIP) problem to find the minimum-conductance set within the identified low-conductance set. At the second step, the densely connected parts in those subnetworks are discovered as the protein complexes by solving another MIP problem that aims to find the dense subnetwork in the minimum-conductance set. Experiments on four large-scale yeast PPI networks from different public databases demonstrate that the complexes predicted by FLCD have better correspondence with the yeast protein complex gold standards than other three state-of-the-art algorithms (ClusterONE, LinkComm, and SR-MCL). Additionally, results of FLCD show higher biological relevance with respect to Gene Ontology (GO) terms by GO enrichment analysis.

  6. Hidden State Prediction: a modification of classic ancestral state reconstruction algorithms helps unravel complex symbioses

    Directory of Open Access Journals (Sweden)

    Jesse Robert Zaneveld

    2014-08-01

    Full Text Available Complex symbioses between animal or plant hosts and their associated microbiotas can involve thousands of species and millions of genes. Because of the number of interacting partners, it is often impractical to study all organisms or genes in these host-microbe symbioses individually. Yet new phylogenetic predictive methods can use the wealth of accumulated data on diverse model organisms to make inferences into the properties of less well-studied species and gene families. Predictive functional profiling methods use evolutionary models based on the properties of studied relatives to put bounds on the likely characteristics of an organism or gene that has not yet been studied in detail. These techniques have been applied to predict diverse features of host-associated microbial communities ranging from the enzymatic function of uncharacterized genes to the gene content of uncultured microorganisms. We consider these phylogenetically-informed predictive techniques from disparate fields as examples of a general class of algorithms for Hidden State Prediction (HSP, and argue that HSP methods have broad value in predicting organismal traits in a variety of contexts, including the study of complex host-microbe symbioses.

  7. Hidden state prediction: a modification of classic ancestral state reconstruction algorithms helps unravel complex symbioses.

    Science.gov (United States)

    Zaneveld, Jesse R R; Thurber, Rebecca L V

    2014-01-01

    Complex symbioses between animal or plant hosts and their associated microbiotas can involve thousands of species and millions of genes. Because of the number of interacting partners, it is often impractical to study all organisms or genes in these host-microbe symbioses individually. Yet new phylogenetic predictive methods can use the wealth of accumulated data on diverse model organisms to make inferences into the properties of less well-studied species and gene families. Predictive functional profiling methods use evolutionary models based on the properties of studied relatives to put bounds on the likely characteristics of an organism or gene that has not yet been studied in detail. These techniques have been applied to predict diverse features of host-associated microbial communities ranging from the enzymatic function of uncharacterized genes to the gene content of uncultured microorganisms. We consider these phylogenetically informed predictive techniques from disparate fields as examples of a general class of algorithms for Hidden State Prediction (HSP), and argue that HSP methods have broad value in predicting organismal traits in a variety of contexts, including the study of complex host-microbe symbioses.

  8. Statistical tests to compare motif count exceptionalities

    Directory of Open Access Journals (Sweden)

    Vandewalle Vincent

    2007-03-01

    Full Text Available Abstract Background Finding over- or under-represented motifs in biological sequences is now a common task in genomics. Thanks to p-value calculation for motif counts, exceptional motifs are identified and represent candidate functional motifs. The present work addresses the related question of comparing the exceptionality of one motif in two different sequences. Just comparing the motif count p-values in each sequence is indeed not sufficient to decide if this motif is significantly more exceptional in one sequence compared to the other one. A statistical test is required. Results We develop and analyze two statistical tests, an exact binomial one and an asymptotic likelihood ratio test, to decide whether the exceptionality of a given motif is equivalent or significantly different in two sequences of interest. For that purpose, motif occurrences are modeled by Poisson processes, with a special care for overlapping motifs. Both tests can take the sequence compositions into account. As an illustration, we compare the octamer exceptionalities in the Escherichia coli K-12 backbone versus variable strain-specific loops. Conclusion The exact binomial test is particularly adapted for small counts. For large counts, we advise to use the likelihood ratio test which is asymptotic but strongly correlated with the exact binomial test and very simple to use.

  9. A Simple Decision Rule for Recognition of Poly(A) Tail Signal Motifs in Human Genome

    KAUST Repository

    AbouEisha, Hassan M.; Chikalov, Igor; Moshkov, Mikhail; Jankovic, Boris R.

    2015-01-01

    Background is the numerous attempts were made to predict motifs in genomic sequences that correspond to poly (A) tail signals. Vast portion of this effort has been directed to a plethora of nonlinear classification methods. Even when such approaches

  10. Proteome-level assessment of origin, prevalence and function of Leucine-Aspartic Acid (LD) motifs

    KAUST Repository

    Alam, Tanvir

    2018-03-11

    Short Linear Motifs (SLiMs) contribute to almost every cellular function by connecting appropriate protein partners. Accurate prediction of SLiMs is difficult due to their shortness and sequence degeneracy. Leucine-aspartic acid (LD) motifs are SLiMs that link paxillin family proteins to factors controlling (cancer) cell adhesion, motility and survival. The existence and importance of LD motifs beyond the paxillin family is poorly understood. To enable a proteome-wide assessment of these motifs, we developed an active-learning based framework that iteratively integrates computational predictions with experimental validation. Our analysis of the human proteome identified a dozen proteins that contain LD motifs, all being involved in cell adhesion and migration, and revealed a new type of inverse LD motif consensus. Our evolutionary analysis suggested that LD motif signalling originated in the common unicellular ancestor of opisthokonts and amoebozoa by co-opting nuclear export sequences. Inter-species comparison revealed a conserved LD signalling core, and reveals the emergence of species-specific adaptive connections, while maintaining a strong functional focus of the LD motif interactome. Collectively, our data elucidate the mechanisms underlying the origin and adaptation of an ancestral SLiM.

  11. A Novel Protein Interaction between Nucleotide Binding Domain of Hsp70 and p53 Motif

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    Asita Elengoe

    2015-01-01

    Full Text Available Currently, protein interaction of Homo sapiens nucleotide binding domain (NBD of heat shock 70 kDa protein (PDB: 1HJO with p53 motif remains to be elucidated. The NBD-p53 motif complex enhances the p53 stabilization, thereby increasing the tumor suppression activity in cancer treatment. Therefore, we identified the interaction between NBD and p53 using STRING version 9.1 program. Then, we modeled the three-dimensional structure of p53 motif through homology modeling and determined the binding affinity and stability of NBD-p53 motif complex structure via molecular docking and dynamics (MD simulation. Human DNA binding domain of p53 motif (SCMGGMNR retrieved from UniProt (UniProtKB: P04637 was docked with the NBD protein, using the Autodock version 4.2 program. The binding energy and intermolecular energy for the NBD-p53 motif complex were −0.44 Kcal/mol and −9.90 Kcal/mol, respectively. Moreover, RMSD, RMSF, hydrogen bonds, salt bridge, and secondary structure analyses revealed that the NBD protein had a strong bond with p53 motif and the protein-ligand complex was stable. Thus, the current data would be highly encouraging for designing Hsp70 structure based drug in cancer therapy.

  12. Complex data modeling and computationally intensive methods for estimation and prediction

    CERN Document Server

    Secchi, Piercesare; Advances in Complex Data Modeling and Computational Methods in Statistics

    2015-01-01

    The book is addressed to statisticians working at the forefront of the statistical analysis of complex and high dimensional data and offers a wide variety of statistical models, computer intensive methods and applications: network inference from the analysis of high dimensional data; new developments for bootstrapping complex data; regression analysis for measuring the downsize reputational risk; statistical methods for research on the human genome dynamics; inference in non-euclidean settings and for shape data; Bayesian methods for reliability and the analysis of complex data; methodological issues in using administrative data for clinical and epidemiological research; regression models with differential regularization; geostatistical methods for mobility analysis through mobile phone data exploration. This volume is the result of a careful selection among the contributions presented at the conference "S.Co.2013: Complex data modeling and computationally intensive methods for estimation and prediction" held...

  13. Prediction of Complex Human Traits Using the Genomic Best Linear Unbiased Predictor

    DEFF Research Database (Denmark)

    de los Campos, Gustavo; Vazquez, Ana I; Fernando, Rohan

    2013-01-01

    Despite important advances from Genome Wide Association Studies (GWAS), for most complex human traits and diseases, a sizable proportion of genetic variance remains unexplained and prediction accuracy (PA) is usually low. Evidence suggests that PA can be improved using Whole-Genome Regression (WGR......) models where phenotypes are regressed on hundreds of thousands of variants simultaneously. The Genomic Best Linear Unbiased Prediction G-BLUP, a ridge-regression type method) is a commonly used WGR method and has shown good predictive performance when applied to plant and animal breeding populations....... However, breeding and human populations differ greatly in a number of factors that can affect the predictive performance of G-BLUP. Using theory, simulations, and real data analysis, we study the erformance of G-BLUP when applied to data from related and unrelated human subjects. Under perfect linkage...

  14. Enrichment of Circular Code Motifs in the Genes of the Yeast Saccharomyces cerevisiae

    Directory of Open Access Journals (Sweden)

    Christian J. Michel

    2017-12-01

    , represent the first evidence for a significant enrichment of X motifs in the genes of an extant organism. They raise two hypotheses: the X motifs may be evolutionary relics of the primitive codes used for translation, or they may continue to play a functional role in the complex processes of genome decoding and protein synthesis.

  15. Enrichment of Circular Code Motifs in the Genes of the Yeast Saccharomyces cerevisiae.

    Science.gov (United States)

    Michel, Christian J; Ngoune, Viviane Nguefack; Poch, Olivier; Ripp, Raymond; Thompson, Julie D

    2017-12-03

    evidence for a significant enrichment of X motifs in the genes of an extant organism. They raise two hypotheses: the X motifs may be evolutionary relics of the primitive codes used for translation, or they may continue to play a functional role in the complex processes of genome decoding and protein synthesis.

  16. Rhythmic complexity and predictive coding: A novel approach to modeling rhythm and meter perception in music

    Directory of Open Access Journals (Sweden)

    Peter eVuust

    2014-10-01

    Full Text Available Musical rhythm, consisting of apparently abstract intervals of accented temporal events, has a remarkable capacity to move our minds and bodies. How does the cognitive system enable our experiences of rhythmically complex music? In this paper, we describe some common forms of rhythmic complexity in music and propose the theory of predictive coding as a framework for understanding how rhythm and rhythmic complexity are processed in the brain. We also consider why we feel so compelled by rhythmic tension in music. First, we consider theories of rhythm and meter perception, which provide hierarchical and computational approaches to modeling. Second, we present the theory of predictive coding, which posits a hierarchical organization of brain responses reflecting fundamental, survival-related mechanisms associated with predicting future events. According to this theory, perception and learning is manifested through the brain’s Bayesian minimization of the error between the input to the brain and the brain’s prior expectations. Third, we develop a predictive coding model of musical rhythm, in which rhythm perception is conceptualized as an interaction between what is heard (‘rhythm’ and the brain’s anticipatory structuring of music (‘meter’. Finally, we review empirical studies of the neural and behavioral effects of syncopation, polyrhythm and groove, and propose how these studies can be seen as special cases of the predictive coding theory. We argue that musical rhythm exploits the brain’s general principles of prediction and propose that pleasure and desire for sensorimotor synchronization from musical rhythm may be a result of such mechanisms.

  17. Genome-Wide Prediction of DNA Methylation Using DNA Composition and Sequence Complexity in Human.

    Science.gov (United States)

    Wu, Chengchao; Yao, Shixin; Li, Xinghao; Chen, Chujia; Hu, Xuehai

    2017-02-16

    DNA methylation plays a significant role in transcriptional regulation by repressing activity. Change of the DNA methylation level is an important factor affecting the expression of target genes and downstream phenotypes. Because current experimental technologies can only assay a small proportion of CpG sites in the human genome, it is urgent to develop reliable computational models for predicting genome-wide DNA methylation. Here, we proposed a novel algorithm that accurately extracted sequence complexity features (seven features) and developed a support-vector-machine-based prediction model with integration of the reported DNA composition features (trinucleotide frequency and GC content, 65 features) by utilizing the methylation profiles of embryonic stem cells in human. The prediction results from 22 human chromosomes with size-varied windows showed that the 600-bp window achieved the best average accuracy of 94.7%. Moreover, comparisons with two existing methods further showed the superiority of our model, and cross-species predictions on mouse data also demonstrated that our model has certain generalization ability. Finally, a statistical test of the experimental data and the predicted data on functional regions annotated by ChromHMM found that six out of 10 regions were consistent, which implies reliable prediction of unassayed CpG sites. Accordingly, we believe that our novel model will be useful and reliable in predicting DNA methylation.

  18. BayesMotif: de novo protein sorting motif discovery from impure datasets.

    Science.gov (United States)

    Hu, Jianjun; Zhang, Fan

    2010-01-18

    Protein sorting is the process that newly synthesized proteins are transported to their target locations within or outside of the cell. This process is precisely regulated by protein sorting signals in different forms. A major category of sorting signals are amino acid sub-sequences usually located at the N-terminals or C-terminals of protein sequences. Genome-wide experimental identification of protein sorting signals is extremely time-consuming and costly. Effective computational algorithms for de novo discovery of protein sorting signals is needed to improve the understanding of protein sorting mechanisms. We formulated the protein sorting motif discovery problem as a classification problem and proposed a Bayesian classifier based algorithm (BayesMotif) for de novo identification of a common type of protein sorting motifs in which a highly conserved anchor is present along with a less conserved motif regions. A false positive removal procedure is developed to iteratively remove sequences that are unlikely to contain true motifs so that the algorithm can identify motifs from impure input sequences. Experiments on both implanted motif datasets and real-world datasets showed that the enhanced BayesMotif algorithm can identify anchored sorting motifs from pure or impure protein sequence dataset. It also shows that the false positive removal procedure can help to identify true motifs even when there is only 20% of the input sequences containing true motif instances. We proposed BayesMotif, a novel Bayesian classification based algorithm for de novo discovery of a special category of anchored protein sorting motifs from impure datasets. Compared to conventional motif discovery algorithms such as MEME, our algorithm can find less-conserved motifs with short highly conserved anchors. Our algorithm also has the advantage of easy incorporation of additional meta-sequence features such as hydrophobicity or charge of the motifs which may help to overcome the limitations of

  19. Low-complexity Behavioral Model for Predictive Maintenance of Railway Turnouts

    DEFF Research Database (Denmark)

    Barkhordari, Pegah; Galeazzi, Roberto; Tejada, Alejandro de Miguel

    2017-01-01

    together with the Eigensystem Realization Algorithm – a type of subspace identification – to identify a fourth order model of the infrastructure. The robustness and predictive capability of the low-complexity behavioral model to reproduce track responses under different types of train excitations have been......Maintenance of railway infrastructures represents a major cost driver for any infrastructure manager since reliability and dependability must be guaranteed at all times. Implementation of predictive maintenance policies relies on the availability of condition monitoring systems able to assess...... the infrastructure health state. The core of any condition monitoring system is the a-priori knowledge about the process to be monitored, in the form of either mathematical models of different complexity or signal features characterizing the healthy/faulty behavior. This study investigates the identification...

  20. Structural fragment clustering reveals novel structural and functional motifs in α-helical transmembrane proteins

    Directory of Open Access Journals (Sweden)

    Vassilev Boris

    2010-04-01

    Full Text Available Abstract Background A large proportion of an organism's genome encodes for membrane proteins. Membrane proteins are important for many cellular processes, and several diseases can be linked to mutations in them. With the tremendous growth of sequence data, there is an increasing need to reliably identify membrane proteins from sequence, to functionally annotate them, and to correctly predict their topology. Results We introduce a technique called structural fragment clustering, which learns sequential motifs from 3D structural fragments. From over 500,000 fragments, we obtain 213 statistically significant, non-redundant, and novel motifs that are highly specific to α-helical transmembrane proteins. From these 213 motifs, 58 of them were assigned to function and checked in the scientific literature for a biological assessment. Seventy percent of the motifs are found in co-factor, ligand, and ion binding sites, 30% at protein interaction interfaces, and 12% bind specific lipids such as glycerol or cardiolipins. The vast majority of motifs (94% appear across evolutionarily unrelated families, highlighting the modularity of functional design in membrane proteins. We describe three novel motifs in detail: (1 a dimer interface motif found in voltage-gated chloride channels, (2 a proton transfer motif found in heme-copper oxidases, and (3 a convergently evolved interface helix motif found in an aspartate symporter, a serine protease, and cytochrome b. Conclusions Our findings suggest that functional modules exist in membrane proteins, and that they occur in completely different evolutionary contexts and cover different binding sites. Structural fragment clustering allows us to link sequence motifs to function through clusters of structural fragments. The sequence motifs can be applied to identify and characterize membrane proteins in novel genomes.

  1. Computational Redox Potential Predictions: Applications to Inorganic and Organic Aqueous Complexes, and Complexes Adsorbed to Mineral Surfaces

    Directory of Open Access Journals (Sweden)

    Krishnamoorthy Arumugam

    2014-04-01

    Full Text Available Applications of redox processes range over a number of scientific fields. This review article summarizes the theory behind the calculation of redox potentials in solution for species such as organic compounds, inorganic complexes, actinides, battery materials, and mineral surface-bound-species. Different computational approaches to predict and determine redox potentials of electron transitions are discussed along with their respective pros and cons for the prediction of redox potentials. Subsequently, recommendations are made for certain necessary computational settings required for accurate calculation of redox potentials. This article reviews the importance of computational parameters, such as basis sets, density functional theory (DFT functionals, and relativistic approaches and the role that physicochemical processes play on the shift of redox potentials, such as hydration or spin orbit coupling, and will aid in finding suitable combinations of approaches for different chemical and geochemical applications. Identifying cost-effective and credible computational approaches is essential to benchmark redox potential calculations against experiments. Once a good theoretical approach is found to model the chemistry and thermodynamics of the redox and electron transfer process, this knowledge can be incorporated into models of more complex reaction mechanisms that include diffusion in the solute, surface diffusion, and dehydration, to name a few. This knowledge is important to fully understand the nature of redox processes be it a geochemical process that dictates natural redox reactions or one that is being used for the optimization of a chemical process in industry. In addition, it will help identify materials that will be useful to design catalytic redox agents, to come up with materials to be used for batteries and photovoltaic processes, and to identify new and improved remediation strategies in environmental engineering, for example the

  2. Synthesis of mixed ligand europium complexes: Verification of predicted luminescence intensification

    International Nuclear Information System (INIS)

    Lima, Nathalia B.D.; Silva, Anderson I.S.; Gonçalves, Simone M.C.; Simas, Alfredo M.

    2016-01-01

    Mixed ligand europium complexes are predicted to be more luminescent than what would be expected from their corresponding repeating ligand compounds according to a conjecture recently advanced by our research group; a conjecture that has already been validated for strongly luminescent europium complexes. In this article, we seek to further verify the validity of this conjecture for complexes which are much more symmetric, and which thus display lower levels of luminescence. Accordingly, we synthesized complexes Eu(DBM) 3 (L) 2 , and all novel mixed ligand combinations Eu(DBM) 3 (L,L') with L and L' equal to DBSO, PTSO, and TPPO. The syntheses were carried out via displacement reactions from the starting complex Eu(DBM) 3 (H 2 O) 2 , passing through the intermediates Eu(DBM) 3 (L) 2 and finally, by displacement of L by L', arriving at Eu(DBM) 3 (L,L'). The ligands L obey the following order of displacement TPPO>PTSO>DBSO>H 2 O, which had been previously described by our group. In the present article, we further show that this displacement order could have been predicted by Sparkle/RM1 thermochemical calculations. Subsequently, we determined the radiative decay rates, A rad , for all six compounds by photophysical measurements. As expected, results show that the measured A rad values for all novel mixed ligand complexes are larger than the average of the A rad values for the corresponding repeating ligand coordination compounds. In conclusion, the present article does broaden the scope of our conjecture, which enunciates that an increase in the diversity of ligands around the europium ion tends to intensify the luminescence. - Highlights: • Mixed ligand europium complexes are predicted to be more luminescent than repeating ligand ones. • Radiative decay rates increase with structural coordination asymmetry. • The non-ionic ligands displacement order in substitution reactions is TPPO>PTSO>DBSO>H 2 O. • Sparkle/RM1 correctly predicts the

  3. A novel multilayer model for missing link prediction and future link forecasting in dynamic complex networks

    Science.gov (United States)

    Yasami, Yasser; Safaei, Farshad

    2018-02-01

    The traditional complex network theory is particularly focused on network models in which all network constituents are dealt with equivalently, while fail to consider the supplementary information related to the dynamic properties of the network interactions. This is a main constraint leading to incorrect descriptions of some real-world phenomena or incomplete capturing the details of certain real-life problems. To cope with the problem, this paper addresses the multilayer aspects of dynamic complex networks by analyzing the properties of intrinsically multilayered co-authorship networks, DBLP and Astro Physics, and presenting a novel multilayer model of dynamic complex networks. The model examines the layers evolution (layers birth/death process and lifetime) throughout the network evolution. Particularly, this paper models the evolution of each node's membership in different layers by an Infinite Factorial Hidden Markov Model considering feature cascade, and thereby formulates the link generation process for intra-layer and inter-layer links. Although adjacency matrixes are useful to describe the traditional single-layer networks, such a representation is not sufficient to describe and analyze the multilayer dynamic networks. This paper also extends a generalized mathematical infrastructure to address the problems issued by multilayer complex networks. The model inference is performed using some Markov Chain Monte Carlo sampling strategies, given synthetic and real complex networks data. Experimental results indicate a tremendous improvement in the performance of the proposed multilayer model in terms of sensitivity, specificity, positive and negative predictive values, positive and negative likelihood ratios, F1-score, Matthews correlation coefficient, and accuracy for two important applications of missing link prediction and future link forecasting. The experimental results also indicate the strong predictivepower of the proposed model for the application of

  4. Contribution of diffusion-weighted MR imaging for predicting benignity of complex adnexal masses

    International Nuclear Information System (INIS)

    Thomassin-Naggara, Isabelle; Darai, Emile; Cuenod, Charles A.; Fournier, Laure; Toussaint, Irwin; Marsault, Claude; Bazot, Marc

    2009-01-01

    The purpose of this study was to prospectively assess the contribution of diffusion-weighted MR imaging (DWI) for characterizing complex adnexal masses. Seventy-seven women (22-87 years old) with complex adnexal masses (30 benign and 47 malignant) underwent MR imaging including DWI before surgery. Conventional morphological MR imaging criteria were recorded in addition to b 1,000 signal intensity and apparent diffusion coefficient (ADC) measurements of cystic and solid components. Positive likelihood ratios (PLR) were calculated for predicting benignity and malignancy. The most significant criteria for predicting benignity were low b 1,000 signal intensity within the solid component (PLR = 10.9), low T2 signal intensity within the solid component (PLR = 5.7), absence of solid portion (PLR = 3.1), absence of ascites or peritoneal implants (PLR = 2.3) and absence of papillary projections (PLR = 2.3). ADC measurements did not contribute to differentiating benign from malignant adnexal masses. All masses that displayed simultaneously low signal intensity within the solid component on T2-weighted and on b 1,000 diffusion-weighted images were benign. Alternatively, the presence of a solid component with intermediate T2 signal and high b 1,000 signal intensity was associated with a PLR of 4.5 for a malignant adnexal tumour. DWI signal intensity is an accurate tool for predicting benignity of complex adnexal masses. (orig.)

  5. Contribution of diffusion-weighted MR imaging for predicting benignity of complex adnexal masses

    Energy Technology Data Exchange (ETDEWEB)

    Thomassin-Naggara, Isabelle [Hopital Tenon, Assistance Publique Hopitaux de Pariss, Department of Radiology, Paris (France); Universite Rene Descartes, LRI-EA4062, Paris (France); Darai, Emile [Hopital Tenon, Assistance Publique Hopitaux de Pariss, Department of Gynecology-Obstetrics, Paris (France); Cuenod, Charles A.; Fournier, Laure [Universite Rene Descartes, LRI-EA4062, Paris (France); Hopital Europeen Georges Pompidou (HEGP), Assistance Publique Hopitaux de Paris, Department of Radiology, Paris (France); Toussaint, Irwin; Marsault, Claude; Bazot, Marc [Hopital Tenon, Assistance Publique Hopitaux de Pariss, Department of Radiology, Paris (France)

    2009-06-15

    The purpose of this study was to prospectively assess the contribution of diffusion-weighted MR imaging (DWI) for characterizing complex adnexal masses. Seventy-seven women (22-87 years old) with complex adnexal masses (30 benign and 47 malignant) underwent MR imaging including DWI before surgery. Conventional morphological MR imaging criteria were recorded in addition to b{sub 1,000} signal intensity and apparent diffusion coefficient (ADC) measurements of cystic and solid components. Positive likelihood ratios (PLR) were calculated for predicting benignity and malignancy. The most significant criteria for predicting benignity were low b{sub 1,000} signal intensity within the solid component (PLR = 10.9), low T2 signal intensity within the solid component (PLR = 5.7), absence of solid portion (PLR = 3.1), absence of ascites or peritoneal implants (PLR = 2.3) and absence of papillary projections (PLR = 2.3). ADC measurements did not contribute to differentiating benign from malignant adnexal masses. All masses that displayed simultaneously low signal intensity within the solid component on T2-weighted and on b{sub 1,000} diffusion-weighted images were benign. Alternatively, the presence of a solid component with intermediate T2 signal and high b{sub 1,000} signal intensity was associated with a PLR of 4.5 for a malignant adnexal tumour. DWI signal intensity is an accurate tool for predicting benignity of complex adnexal masses. (orig.)

  6. Kernel-based whole-genome prediction of complex traits: a review.

    Science.gov (United States)

    Morota, Gota; Gianola, Daniel

    2014-01-01

    Prediction of genetic values has been a focus of applied quantitative genetics since the beginning of the 20th century, with renewed interest following the advent of the era of whole genome-enabled prediction. Opportunities offered by the emergence of high-dimensional genomic data fueled by post-Sanger sequencing technologies, especially molecular markers, have driven researchers to extend Ronald Fisher and Sewall Wright's models to confront new challenges. In particular, kernel methods are gaining consideration as a regression method of choice for genome-enabled prediction. Complex traits are presumably influenced by many genomic regions working in concert with others (clearly so when considering pathways), thus generating interactions. Motivated by this view, a growing number of statistical approaches based on kernels attempt to capture non-additive effects, either parametrically or non-parametrically. This review centers on whole-genome regression using kernel methods applied to a wide range of quantitative traits of agricultural importance in animals and plants. We discuss various kernel-based approaches tailored to capturing total genetic variation, with the aim of arriving at an enhanced predictive performance in the light of available genome annotation information. Connections between prediction machines born in animal breeding, statistics, and machine learning are revisited, and their empirical prediction performance is discussed. Overall, while some encouraging results have been obtained with non-parametric kernels, recovering non-additive genetic variation in a validation dataset remains a challenge in quantitative genetics.

  7. Kernel-based whole-genome prediction of complex traits: a review

    Directory of Open Access Journals (Sweden)

    Gota eMorota

    2014-10-01

    Full Text Available Prediction of genetic values has been a focus of applied quantitative genetics since the beginning of the 20th century, with renewed interest following the advent of the era of whole genome-enabled prediction. Opportunities offered by the emergence of high-dimensional genomic data fueled by post-Sanger sequencing technologies, especially molecular markers, have driven researchers to extend Ronald Fisher and Sewall Wright's models to confront new challenges. In particular, kernel methods are gaining consideration as a regression method of choice for genome-enabled prediction. Complex traits are presumably influenced by many genomic regions working in concert with others (clearly so when considering pathways, thus generating interactions. Motivated by this view, a growing number of statistical approaches based on kernels attempt to capture non-additive effects, either parametrically or non-parametrically. This review centers on whole-genome regression using kernel methods applied to a wide range of quantitative traits of agricultural importance in animals and plants. We discuss various kernel-based approaches tailored to capturing total genetic variation, with the aim of arriving at an enhanced predictive performance in the light of available genome annotation information. Connections between prediction machines born in animal breeding, statistics, and machine learning are revisited, and their empirical prediction performance is discussed. Overall, while some encouraging results have been obtained with non-parametric kernels, recovering non-additive genetic variation in a validation dataset remains a challenge in quantitative genetics.

  8. Motifs in triadic random graphs based on Steiner triple systems

    Science.gov (United States)

    Winkler, Marco; Reichardt, Jörg

    2013-08-01

    Conventionally, pairwise relationships between nodes are considered to be the fundamental building blocks of complex networks. However, over the last decade, the overabundance of certain subnetwork patterns, i.e., the so-called motifs, has attracted much attention. It has been hypothesized that these motifs, instead of links, serve as the building blocks of network structures. Although the relation between a network's topology and the general properties of the system, such as its function, its robustness against perturbations, or its efficiency in spreading information, is the central theme of network science, there is still a lack of sound generative models needed for testing the functional role of subgraph motifs. Our work aims to overcome this limitation. We employ the framework of exponential random graph models (ERGMs) to define models based on triadic substructures. The fact that only a small portion of triads can actually be set independently poses a challenge for the formulation of such models. To overcome this obstacle, we use Steiner triple systems (STSs). These are partitions of sets of nodes into pair-disjoint triads, which thus can be specified independently. Combining the concepts of ERGMs and STSs, we suggest generative models capable of generating ensembles of networks with nontrivial triadic Z-score profiles. Further, we discover inevitable correlations between the abundance of triad patterns, which occur solely for statistical reasons and need to be taken into account when discussing the functional implications of motif statistics. Moreover, we calculate the degree distributions of our triadic random graphs analytically.

  9. Data based identification and prediction of nonlinear and complex dynamical systems

    Science.gov (United States)

    Wang, Wen-Xu; Lai, Ying-Cheng; Grebogi, Celso

    2016-07-01

    The problem of reconstructing nonlinear and complex dynamical systems from measured data or time series is central to many scientific disciplines including physical, biological, computer, and social sciences, as well as engineering and economics. The classic approach to phase-space reconstruction through the methodology of delay-coordinate embedding has been practiced for more than three decades, but the paradigm is effective mostly for low-dimensional dynamical systems. Often, the methodology yields only a topological correspondence of the original system. There are situations in various fields of science and engineering where the systems of interest are complex and high dimensional with many interacting components. A complex system typically exhibits a rich variety of collective dynamics, and it is of great interest to be able to detect, classify, understand, predict, and control the dynamics using data that are becoming increasingly accessible due to the advances of modern information technology. To accomplish these goals, especially prediction and control, an accurate reconstruction of the original system is required. Nonlinear and complex systems identification aims at inferring, from data, the mathematical equations that govern the dynamical evolution and the complex interaction patterns, or topology, among the various components of the system. With successful reconstruction of the system equations and the connecting topology, it may be possible to address challenging and significant problems such as identification of causal relations among the interacting components and detection of hidden nodes. The "inverse" problem thus presents a grand challenge, requiring new paradigms beyond the traditional delay-coordinate embedding methodology. The past fifteen years have witnessed rapid development of contemporary complex graph theory with broad applications in interdisciplinary science and engineering. The combination of graph, information, and nonlinear dynamical

  10. Data based identification and prediction of nonlinear and complex dynamical systems

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Wen-Xu [School of Systems Science, Beijing Normal University, Beijing, 100875 (China); Business School, University of Shanghai for Science and Technology, Shanghai 200093 (China); Lai, Ying-Cheng, E-mail: Ying-Cheng.Lai@asu.edu [School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ 85287 (United States); Department of Physics, Arizona State University, Tempe, AZ 85287 (United States); Institute for Complex Systems and Mathematical Biology, King’s College, University of Aberdeen, Aberdeen AB24 3UE (United Kingdom); Grebogi, Celso [Institute for Complex Systems and Mathematical Biology, King’s College, University of Aberdeen, Aberdeen AB24 3UE (United Kingdom)

    2016-07-12

    The problem of reconstructing nonlinear and complex dynamical systems from measured data or time series is central to many scientific disciplines including physical, biological, computer, and social sciences, as well as engineering and economics. The classic approach to phase-space reconstruction through the methodology of delay-coordinate embedding has been practiced for more than three decades, but the paradigm is effective mostly for low-dimensional dynamical systems. Often, the methodology yields only a topological correspondence of the original system. There are situations in various fields of science and engineering where the systems of interest are complex and high dimensional with many interacting components. A complex system typically exhibits a rich variety of collective dynamics, and it is of great interest to be able to detect, classify, understand, predict, and control the dynamics using data that are becoming increasingly accessible due to the advances of modern information technology. To accomplish these goals, especially prediction and control, an accurate reconstruction of the original system is required. Nonlinear and complex systems identification aims at inferring, from data, the mathematical equations that govern the dynamical evolution and the complex interaction patterns, or topology, among the various components of the system. With successful reconstruction of the system equations and the connecting topology, it may be possible to address challenging and significant problems such as identification of causal relations among the interacting components and detection of hidden nodes. The “inverse” problem thus presents a grand challenge, requiring new paradigms beyond the traditional delay-coordinate embedding methodology. The past fifteen years have witnessed rapid development of contemporary complex graph theory with broad applications in interdisciplinary science and engineering. The combination of graph, information, and nonlinear

  11. Data based identification and prediction of nonlinear and complex dynamical systems

    International Nuclear Information System (INIS)

    Wang, Wen-Xu; Lai, Ying-Cheng; Grebogi, Celso

    2016-01-01

    The problem of reconstructing nonlinear and complex dynamical systems from measured data or time series is central to many scientific disciplines including physical, biological, computer, and social sciences, as well as engineering and economics. The classic approach to phase-space reconstruction through the methodology of delay-coordinate embedding has been practiced for more than three decades, but the paradigm is effective mostly for low-dimensional dynamical systems. Often, the methodology yields only a topological correspondence of the original system. There are situations in various fields of science and engineering where the systems of interest are complex and high dimensional with many interacting components. A complex system typically exhibits a rich variety of collective dynamics, and it is of great interest to be able to detect, classify, understand, predict, and control the dynamics using data that are becoming increasingly accessible due to the advances of modern information technology. To accomplish these goals, especially prediction and control, an accurate reconstruction of the original system is required. Nonlinear and complex systems identification aims at inferring, from data, the mathematical equations that govern the dynamical evolution and the complex interaction patterns, or topology, among the various components of the system. With successful reconstruction of the system equations and the connecting topology, it may be possible to address challenging and significant problems such as identification of causal relations among the interacting components and detection of hidden nodes. The “inverse” problem thus presents a grand challenge, requiring new paradigms beyond the traditional delay-coordinate embedding methodology. The past fifteen years have witnessed rapid development of contemporary complex graph theory with broad applications in interdisciplinary science and engineering. The combination of graph, information, and nonlinear

  12. Surface Complexation Modeling in Variable Charge Soils: Prediction of Cadmium Adsorption

    Directory of Open Access Journals (Sweden)

    Giuliano Marchi

    2015-10-01

    Full Text Available ABSTRACT Intrinsic equilibrium constants for 22 representative Brazilian Oxisols were estimated from a cadmium adsorption experiment. Equilibrium constants were fitted to two surface complexation models: diffuse layer and constant capacitance. Intrinsic equilibrium constants were optimized by FITEQL and by hand calculation using Visual MINTEQ in sweep mode, and Excel spreadsheets. Data from both models were incorporated into Visual MINTEQ. Constants estimated by FITEQL and incorporated in Visual MINTEQ software failed to predict observed data accurately. However, FITEQL raw output data rendered good results when predicted values were directly compared with observed values, instead of incorporating the estimated constants into Visual MINTEQ. Intrinsic equilibrium constants optimized by hand calculation and incorporated in Visual MINTEQ reliably predicted Cd adsorption reactions on soil surfaces under changing environmental conditions.

  13. A survey of motif finding Web tools for detecting binding site motifs in ChIP-Seq data.

    Science.gov (United States)

    Tran, Ngoc Tam L; Huang, Chun-Hsi

    2014-02-20

    ChIP-Seq (chromatin immunoprecipitation sequencing) has provided the advantage for finding motifs as ChIP-Seq experiments narrow down the motif finding to binding site locations. Recent motif finding tools facilitate the motif detection by providing user-friendly Web interface. In this work, we reviewed nine motif finding Web tools that are capable for detecting binding site motifs in ChIP-Seq data. We showed each motif finding Web tool has its own advantages for detecting motifs that other tools may not discover. We recommended the users to use multiple motif finding Web tools that implement different algorithms for obtaining significant motifs, overlapping resemble motifs, and non-overlapping motifs. Finally, we provided our suggestions for future development of motif finding Web tool that better assists researchers for finding motifs in ChIP-Seq data.

  14. Ensemble Sensitivity Analysis of a Severe Downslope Windstorm in Complex Terrain: Implications for Forecast Predictability Scales and Targeted Observing Networks

    Science.gov (United States)

    2013-09-01

    observations, linear regression finds the straight line that explains the linear relationship of the sample. This line is given by the equation y = mx + b...SENSITIVITY ANALYSIS OF A SEVERE DOWNSLOPE WINDSTORM IN COMPLEX TERRAIN: IMPLICATIONS FOR FORECAST PREDICTABILITY SCALES AND TARGETED OBSERVING...SENSITIVITY ANALYSIS OF A SEVERE DOWNSLOPE WINDSTORM IN COMPLEX TERRAIN: IMPLICATIONS FOR FORECAST PREDICTABILITY SCALES AND TARGETED OBSERVING NETWORKS

  15. Aggregation of topological motifs in the Escherichia coli transcriptional regulatory network

    Directory of Open Access Journals (Sweden)

    Barabási Albert-László

    2004-01-01

    Full Text Available Abstract Background Transcriptional regulation of cellular functions is carried out through a complex network of interactions among transcription factors and the promoter regions of genes and operons regulated by them.To better understand the system-level function of such networks simplification of their architecture was previously achieved by identifying the motifs present in the network, which are small, overrepresented, topologically distinct regulatory interaction patterns (subgraphs. However, the interaction of such motifs with each other, and their form of integration into the full network has not been previously examined. Results By studying the transcriptional regulatory network of the bacterium, Escherichia coli, we demonstrate that the two previously identified motif types in the network (i.e., feed-forward loops and bi-fan motifs do not exist in isolation, but rather aggregate into homologous motif clusters that largely overlap with known biological functions. Moreover, these clusters further coalesce into a supercluster, thus establishing distinct topological hierarchies that show global statistical properties similar to the whole network. Targeted removal of motif links disintegrates the network into small, isolated clusters, while random disruptions of equal number of links do not cause such an effect. Conclusion Individual motifs aggregate into homologous motif clusters and a supercluster forming the backbone of the E. coli transcriptional regulatory network and play a central role in defining its global topological organization.

  16. Predicting complex acute wound healing in patients from a wound expertise centre registry: a prognostic study.

    Science.gov (United States)

    Ubbink, Dirk T; Lindeboom, Robert; Eskes, Anne M; Brull, Huub; Legemate, Dink A; Vermeulen, Hester

    2015-10-01

    It is important for caregivers and patients to know which wounds are at risk of prolonged wound healing to enable timely communication and treatment. Available prognostic models predict wound healing in chronic ulcers, but not in acute wounds, that is, originating after trauma or surgery. We developed a model to detect which factors can predict (prolonged) healing of complex acute wounds in patients treated in a large wound expertise centre (WEC). Using Cox and linear regression analyses, we determined which patient- and wound-related characteristics best predict time to complete wound healing and derived a prediction formula to estimate how long this may take. We selected 563 patients with acute wounds, documented in the WEC registry between 2007 and 2012. Wounds had existed for a median of 19 days (range 6-46 days). The majority of these were located on the leg (52%). Five significant independent predictors of prolonged wound healing were identified: wound location on the trunk [hazard ratio (HR) 0·565, 95% confidence interval (CI) 0·405-0·788; P = 0·001], wound infection (HR 0·728, 95% CI 0·534-0·991; P = 0·044), wound size (HR 0·993, 95% CI 0·988-0·997; P = 0·001), wound duration (HR 0·998, 95% CI 0·996-0·999; P = 0·005) and patient's age (HR 1·009, 95% CI 1·001-1·018; P = 0·020), but not diabetes. Awareness of the five factors predicting the healing of complex acute wounds, particularly wound infection and location on the trunk, may help caregivers to predict wound healing time and to detect, refer and focus on patients who need additional attention. © 2013 The Authors. International Wound Journal © 2013 Medicalhelplines.com Inc and John Wiley & Sons Ltd.

  17. Sequence-based feature prediction and annotation of proteins

    DEFF Research Database (Denmark)

    Juncker, Agnieszka; Jensen, Lars J.; Pierleoni, Andrea

    2009-01-01

    A recent trend in computational methods for annotation of protein function is that many prediction tools are combined in complex workflows and pipelines to facilitate the analysis of feature combinations, for example, the entire repertoire of kinase-binding motifs in the human proteome....

  18. Temporal motifs in time-dependent networks

    International Nuclear Information System (INIS)

    Kovanen, Lauri; Karsai, Márton; Kaski, Kimmo; Kertész, János; Saramäki, Jari

    2011-01-01

    Temporal networks are commonly used to represent systems where connections between elements are active only for restricted periods of time, such as telecommunication, neural signal processing, biochemical reaction and human social interaction networks. We introduce the framework of temporal motifs to study the mesoscale topological–temporal structure of temporal networks in which the events of nodes do not overlap in time. Temporal motifs are classes of similar event sequences, where the similarity refers not only to topology but also to the temporal order of the events. We provide a mapping from event sequences to coloured directed graphs that enables an efficient algorithm for identifying temporal motifs. We discuss some aspects of temporal motifs, including causality and null models, and present basic statistics of temporal motifs in a large mobile call network

  19. Motif discovery in ranked lists of sequences

    DEFF Research Database (Denmark)

    Nielsen, Morten Muhlig; Tataru, Paula; Madsen, Tobias

    2016-01-01

    Motif analysis has long been an important method to characterize biological functionality and the current growth of sequencing-based genomics experiments further extends its potential. These diverse experiments often generate sequence lists ranked by some functional property. There is therefore...... advantage of the regular expression feature, including enrichments for combinations of different microRNA seed sites. The method is implemented and made publicly available as an R package and supports high parallelization on multi-core machinery....... a growing need for motif analysis methods that can exploit this coupled data structure and be tailored for specific biological questions. Here, we present an exploratory motif analysis tool, Regmex (REGular expression Motif EXplorer), which offers several methods to evaluate the correlation of motifs...

  20. Distance-dependent duplex DNA destabilization proximal to G-quadruplex/i-motif sequences

    Science.gov (United States)

    König, Sebastian L. B.; Huppert, Julian L.; Sigel, Roland K. O.; Evans, Amanda C.

    2013-01-01

    G-quadruplexes and i-motifs are complementary examples of non-canonical nucleic acid substructure conformations. G-quadruplex thermodynamic stability has been extensively studied for a variety of base sequences, but the degree of duplex destabilization that adjacent quadruplex structure formation can cause has yet to be fully addressed. Stable in vivo formation of these alternative nucleic acid structures is likely to be highly dependent on whether sufficient spacing exists between neighbouring duplex- and quadruplex-/i-motif-forming regions to accommodate quadruplexes or i-motifs without disrupting duplex stability. Prediction of putative G-quadruplex-forming regions is likely to be assisted by further understanding of what distance (number of base pairs) is required for duplexes to remain stable as quadruplexes or i-motifs form. Using oligonucleotide constructs derived from precedented G-quadruplexes and i-motif-forming bcl-2 P1 promoter region, initial biophysical stability studies indicate that the formation of G-quadruplex and i-motif conformations do destabilize proximal duplex regions. The undermining effect that quadruplex formation can have on duplex stability is mitigated with increased distance from the duplex region: a spacing of five base pairs or more is sufficient to maintain duplex stability proximal to predicted quadruplex/i-motif-forming regions. PMID:23771141

  1. Prediction of higher cost of antiretroviral therapy (ART) according to clinical complexity. A validated clinical index.

    Science.gov (United States)

    Velasco, Cesar; Pérez, Inaki; Podzamczer, Daniel; Llibre, Josep Maria; Domingo, Pere; González-García, Juan; Puig, Inma; Ayala, Pilar; Martín, Mayte; Trilla, Antoni; Lázaro, Pablo; Gatell, Josep Maria

    2016-03-01

    The financing of antiretroviral therapy (ART) is generally determined by the cost incurred in the previous year, the number of patients on treatment, and the evidence-based recommendations, but not the clinical characteristics of the population. To establish a score relating the cost of ART and patient clinical complexity in order to understand the costing differences between hospitals in the region that could be explained by the clinical complexity of their population. Retrospective analysis of patients receiving ART in a tertiary hospital between 2009 and 2011. Factors potentially associated with a higher cost of ART were assessed by bivariate and multivariate analysis. Two predictive models of "high-cost" were developed. The normalized estimated (adjusted for the complexity scores) costs were calculated and compared with the normalized real costs. In the Hospital Index, 631 (16.8%) of the 3758 patients receiving ART were responsible for a "high-cost" subgroup, defined as the highest 25% of spending on ART. Baseline variables that were significant predictors of high cost in the Clinic-B model in the multivariate analysis were: route of transmission of HIV, AIDS criteria, Spanish nationality, year of initiation of ART, CD4+ lymphocyte count nadir, and number of hospital admissions. The Clinic-B score ranged from 0 to 13, and the mean value (5.97) was lower than the overall mean value of the four hospitals (6.16). The clinical complexity of the HIV patient influences the cost of ART. The Clinic-B and Clinic-BF scores predicted patients with high cost of ART and could be used to compare and allocate costs corrected for the patient clinical complexity. Copyright © 2015 Elsevier España, S.L.U. y Sociedad Española de Enfermedades Infecciosas y Microbiología Clínica. All rights reserved.

  2. Spectral simplicity of apparent complexity. I. The nondiagonalizable metadynamics of prediction

    Science.gov (United States)

    Riechers, Paul M.; Crutchfield, James P.

    2018-03-01

    Virtually all questions that one can ask about the behavioral and structural complexity of a stochastic process reduce to a linear algebraic framing of a time evolution governed by an appropriate hidden-Markov process generator. Each type of question—correlation, predictability, predictive cost, observer synchronization, and the like—induces a distinct generator class. Answers are then functions of the class-appropriate transition dynamic. Unfortunately, these dynamics are generically nonnormal, nondiagonalizable, singular, and so on. Tractably analyzing these dynamics relies on adapting the recently introduced meromorphic functional calculus, which specifies the spectral decomposition of functions of nondiagonalizable linear operators, even when the function poles and zeros coincide with the operator's spectrum. Along the way, we establish special properties of the spectral projection operators that demonstrate how they capture the organization of subprocesses within a complex system. Circumventing the spurious infinities of alternative calculi, this leads in the sequel, Part II [P. M. Riechers and J. P. Crutchfield, Chaos 28, 033116 (2018)], to the first closed-form expressions for complexity measures, couched either in terms of the Drazin inverse (negative-one power of a singular operator) or the eigenvalues and projection operators of the appropriate transition dynamic.

  3. Using Google Earth Surface Metrics to Predict Plant Species Richness in a Complex Landscape

    Directory of Open Access Journals (Sweden)

    Sebastián Block

    2016-10-01

    Full Text Available Google Earth provides a freely available, global mosaic of high-resolution imagery from different sensors that has become popular in environmental and ecological studies. However, such imagery lacks the near-infrared band often used in studying vegetation, thus its potential for estimating vegetation properties remains unclear. In this study, we assess the potential of Google Earth imagery to describe and predict vegetation attributes. Further, we compare it to the potential of SPOT imagery, which has additional spectral information. We measured basal area, vegetation height, crown cover, density of individuals, and species richness in 60 plots in the oak forests of a complex volcanic landscape in central Mexico. We modelled each vegetation attribute as a function of surface metrics derived from Google Earth and SPOT images, and selected the best-supported linear models from each source. Total species richness was the best-described and predicted variable: the best Google Earth-based model explained nearly as much variation in species richness as its SPOT counterpart (R2 = 0.44 and 0.51, respectively. However, Google Earth metrics emerged as poor predictors of all remaining vegetation attributes, whilst SPOT metrics showed potential for predicting vegetation height. We conclude that Google Earth imagery can be used to estimate species richness in complex landscapes. As it is freely available, Google Earth can broaden the use of remote sensing by researchers and managers in low-income tropical countries where most biodiversity hotspots are found.

  4. Per Aspera ad Astra: Through Complex Population Modeling to Predictive Theory.

    Science.gov (United States)

    Topping, Christopher J; Alrøe, Hugo Fjelsted; Farrell, Katharine N; Grimm, Volker

    2015-11-01

    Population models in ecology are often not good at predictions, even if they are complex and seem to be realistic enough. The reason for this might be that Occam's razor, which is key for minimal models exploring ideas and concepts, has been too uncritically adopted for more realistic models of systems. This can tie models too closely to certain situations, thereby preventing them from predicting the response to new conditions. We therefore advocate a new kind of parsimony to improve the application of Occam's razor. This new parsimony balances two contrasting strategies for avoiding errors in modeling: avoiding inclusion of nonessential factors (false inclusions) and avoiding exclusion of sometimes-important factors (false exclusions). It involves a synthesis of traditional modeling and analysis, used to describe the essentials of mechanistic relationships, with elements that are included in a model because they have been reported to be or can arguably be assumed to be important under certain conditions. The resulting models should be able to reflect how the internal organization of populations change and thereby generate representations of the novel behavior necessary for complex predictions, including regime shifts.

  5. Cognitive function predicts listening effort performance during complex tasks in normally aging adults

    Directory of Open Access Journals (Sweden)

    Jennine Harvey

    2017-01-01

    Full Text Available Purpose: This study examines whether cognitive function, as measured by the subtests of the Woodcock–Johnson III (WCJ-III assessment, predicts listening-effort performance during dual tasks across the adults of varying ages. Materials and Methods: Participants were divided into two groups. Group 1 consisted of 14 listeners (number of females = 11 who were 41–61 years old [mean = 53.18; standard deviation (SD = 5.97]. Group 2 consisted of 15 listeners (number of females = 9 who were 63–81 years old (mean = 72.07; SD = 5.11. Participants were administered the WCJ-III Memory for Words, Auditory Working Memory, Visual Matching, and Decision Speed subtests. All participants were tested in each of the following three dual-task experimental conditions, which were varying in complexity: (1 auditory word recognition + visual processing, (2 auditory working memory (word + visual processing, and (3 auditory working memory (sentence + visual processing in noise. Results: A repeated measures analysis of variance revealed that task complexity significantly affected the performance measures of auditory accuracy, visual accuracy, and processing speed. Linear regression revealed that the cognitive subtests of the WCJ-III test significantly predicted performance across dependent variable measures. Conclusion: Listening effort is significantly affected by task complexity, regardless of age. Performance on the WCJ-III test may predict listening effort in adults and may assist speech-language pathologist (SLPs to understand challenges faced by participants when subjected to noise.

  6. Rhythmic complexity and predictive coding: a novel approach to modeling rhythm and meter perception in music

    Science.gov (United States)

    Vuust, Peter; Witek, Maria A. G.

    2014-01-01

    Musical rhythm, consisting of apparently abstract intervals of accented temporal events, has a remarkable capacity to move our minds and bodies. How does the cognitive system enable our experiences of rhythmically complex music? In this paper, we describe some common forms of rhythmic complexity in music and propose the theory of predictive coding (PC) as a framework for understanding how rhythm and rhythmic complexity are processed in the brain. We also consider why we feel so compelled by rhythmic tension in music. First, we consider theories of rhythm and meter perception, which provide hierarchical and computational approaches to modeling. Second, we present the theory of PC, which posits a hierarchical organization of brain responses reflecting fundamental, survival-related mechanisms associated with predicting future events. According to this theory, perception and learning is manifested through the brain’s Bayesian minimization of the error between the input to the brain and the brain’s prior expectations. Third, we develop a PC model of musical rhythm, in which rhythm perception is conceptualized as an interaction between what is heard (“rhythm”) and the brain’s anticipatory structuring of music (“meter”). Finally, we review empirical studies of the neural and behavioral effects of syncopation, polyrhythm and groove, and propose how these studies can be seen as special cases of the PC theory. We argue that musical rhythm exploits the brain’s general principles of prediction and propose that pleasure and desire for sensorimotor synchronization from musical rhythm may be a result of such mechanisms. PMID:25324813

  7. Prediction of thermal and mechanical stress-strain responses of TMC's subjected to complex TMF histories

    Science.gov (United States)

    Johnson, W. S.; Mirdamadi, M.

    1994-01-01

    This paper presents an experimental and analytical evaluation of cross-plied laminates of Ti-15V-3Cr-3Al-3Sn (Ti-15-3) matrix reinforced with continuous silicon-carbide fibers (SCS-6) subjected to a complex TMF loading profile. Thermomechanical fatigue test techniques were developed to conduct a simulation of a generic hypersonic flight profile. A micromechanical analysis was used. The analysis predicts the stress-strain response of the laminate and of the constituents in each ply during thermal and mechanical cycling by using only constituent properties as input. The fiber was modeled as elastic with transverse orthotropic and temperature-dependent properties. The matrix was modeled using a thermoviscoplastic constitutive relation. The fiber transverse modulus was reduced in the analysis to simulate the fiber-matrix interface failures. Excellent correlation was found between measured and predicted laminate stress-strain response due to generic hypersonic flight profile when fiber debonding was modeled.

  8. Predictive ethoinformatics reveals the complex migratory behaviour of a pelagic seabird, the Manx Shearwater

    Science.gov (United States)

    Freeman, Robin; Dean, Ben; Kirk, Holly; Leonard, Kerry; Phillips, Richard A.; Perrins, Chris M.; Guilford, Tim

    2013-01-01

    Understanding the behaviour of animals in the wild is fundamental to conservation efforts. Advances in bio-logging technologies have offered insights into the behaviour of animals during foraging, migration and social interaction. However, broader application of these systems has been limited by device mass, cost and longevity. Here, we use information from multiple logger types to predict individual behaviour in a highly pelagic, migratory seabird, the Manx Shearwater (Puffinus puffinus). Using behavioural states resolved from GPS tracking of foraging during the breeding season, we demonstrate that individual behaviours can be accurately predicted during multi-year migrations from low cost, lightweight, salt-water immersion devices. This reveals a complex pattern of migratory stopovers: some involving high proportions of foraging, and others of rest behaviour. We use this technique to examine three consecutive years of global migrations, revealing the prominence of foraging behaviour during migration and the importance of highly productive waters during migratory stopover. PMID:23635496

  9. Geographic relatedness and predictability of Escherichia coli along a peninsular beach complex of Lake Michigan

    Science.gov (United States)

    Nevers, M.B.; Shively, D.A.; Kleinheinz, G.T.; McDermott, C.M.; Schuster, W.; Chomeau, V.; Whitman, R.L.

    2009-01-01

    To determine more accurately the real-time concentration of fecal indicator bacteria (FIB) in beach water, predictive modeling has been applied in several locations around the Great Lakes to individual or small groups of similar beaches. Using 24 beaches in Door County, Wisconsin, we attempted to expand predictive models to multiple beaches of complex geography. We examined the importance of geographic location and independent variables and the consequential limitations for potential beach or beach group models. An analysis of Escherichia coli populations over 4 yr revealed a geographic gradient to the beaches, with mean E. coli concentrations decreasing with increasing distance from the city of Sturgeon Bay. Beaches grouped strongly by water type (lake, bay, Sturgeon Bay) and proximity to one another, followed by presence of a storm or creek outfall or amount of shoreline enclosure. Predictive models developed for beach groups commonly included wave height and cumulative 48-h rainfall but generally explained little E. coli variation (adj. R2 = 0.19-0.36). Generally low concentrations of E. coli at the beaches influenced the effectiveness of model results presumably because of low signal-to-noise ratios and the rarity of elevated concentrations. Our results highlight the importance of the sensitivity of regressors and the need for careful methods evaluation. Despite the attractiveness of predictive models as an alternative beach monitoring approach, it is likely that FIB fluctuations at some beaches defy simple prediction approaches. Regional, multi-beach, and individual beach predictive models should be explored alongside other techniques for improving monitoring reliability at Great Lakes beaches. Copyright ?? 2009 by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America. All rights reserved.

  10. Developing predictive systems models to address complexity and relevance for ecological risk assessment.

    Science.gov (United States)

    Forbes, Valery E; Calow, Peter

    2013-07-01

    Ecological risk assessments (ERAs) are not used as well as they could be in risk management. Part of the problem is that they often lack ecological relevance; that is, they fail to grasp necessary ecological complexities. Adding realism and complexity can be difficult and costly. We argue that predictive systems models (PSMs) can provide a way of capturing complexity and ecological relevance cost-effectively. However, addressing complexity and ecological relevance is only part of the problem. Ecological risk assessments often fail to meet the needs of risk managers by not providing assessments that relate to protection goals and by expressing risk in ratios that cannot be weighed against the costs of interventions. Once more, PSMs can be designed to provide outputs in terms of value-relevant effects that are modulated against exposure and that can provide a better basis for decision making than arbitrary ratios or threshold values. Recent developments in the modeling and its potential for implementation by risk assessors and risk managers are beginning to demonstrate how PSMs can be practically applied in risk assessment and the advantages that doing so could have. Copyright © 2013 SETAC.

  11. An efficient hybrid technique in RCS predictions of complex targets at high frequencies

    Science.gov (United States)

    Algar, María-Jesús; Lozano, Lorena; Moreno, Javier; González, Iván; Cátedra, Felipe

    2017-09-01

    Most computer codes in Radar Cross Section (RCS) prediction use Physical Optics (PO) and Physical theory of Diffraction (PTD) combined with Geometrical Optics (GO) and Geometrical Theory of Diffraction (GTD). The latter approaches are computationally cheaper and much more accurate for curved surfaces, but not applicable for the computation of the RCS of all surfaces of a complex object due to the presence of caustic problems in the analysis of concave surfaces or flat surfaces in the far field. The main contribution of this paper is the development of a hybrid method based on a new combination of two asymptotic techniques: GTD and PO, considering the advantages and avoiding the disadvantages of each of them. A very efficient and accurate method to analyze the RCS of complex structures at high frequencies is obtained with the new combination. The proposed new method has been validated comparing RCS results obtained for some simple cases using the proposed approach and RCS using the rigorous technique of Method of Moments (MoM). Some complex cases have been examined at high frequencies contrasting the results with PO. This study shows the accuracy and the efficiency of the hybrid method and its suitability for the computation of the RCS at really large and complex targets at high frequencies.

  12. Predicting Chiral Nanostructures, Lattices and Superlattices in Complex Multicomponent Nanoparticle Self-Assembly

    KAUST Repository

    Hur, Kahyun

    2012-06-13

    "Bottom up" type nanoparticle (NP) self-assembly is expected to provide facile routes to nanostructured materials for various, for example, energy related, applications. Despite progress in simulations and theories, structure prediction of self-assembled materials beyond simple model systems remains challenging. Here we utilize a field theory approach for predicting nanostructure of complex and multicomponent hybrid systems with multiple types of short- and long-range interactions. We propose design criteria for controlling a range of NP based nanomaterial structures. In good agreement with recent experiments, the theory predicts that ABC triblock terpolymer directed assemblies with ligand-stabilized NPs can lead to chiral NP network structures. Furthermore, we predict that long-range Coulomb interactions between NPs leading to simple NP lattices, when applied to NP/block copolymer (BCP) assemblies, induce NP superlattice formation within the phase separated BCP nanostructure, a strategy not yet realized experimentally. We expect such superlattices to be of increasing interest to communities involved in research on, for example, energy generation and storage, metamaterials, as well as microelectronics and information storage. © 2012 American Chemical Society.

  13. Predicting Falls in People with Multiple Sclerosis: Fall History Is as Accurate as More Complex Measures

    Directory of Open Access Journals (Sweden)

    Michelle H. Cameron

    2013-01-01

    Full Text Available Background. Many people with MS fall, but the best method for identifying those at increased fall risk is not known. Objective. To compare how accurately fall history, questionnaires, and physical tests predict future falls and injurious falls in people with MS. Methods. 52 people with MS were asked if they had fallen in the past 2 months and the past year. Subjects were also assessed with the Activities-specific Balance Confidence, Falls Efficacy Scale-International, and Multiple Sclerosis Walking Scale-12 questionnaires, the Expanded Disability Status Scale, Timed 25-Foot Walk, and computerized dynamic posturography and recorded their falls daily for the following 6 months with calendars. The ability of baseline assessments to predict future falls was compared using receiver operator curves and logistic regression. Results. All tests individually provided similar fall prediction (area under the curve (AUC 0.60–0.75. A fall in the past year was the best predictor of falls (AUC 0.75, sensitivity 0.89, specificity 0.56 or injurious falls (AUC 0.69, sensitivity 0.96, specificity 0.41 in the following 6 months. Conclusion. Simply asking people with MS if they have fallen in the past year predicts future falls and injurious falls as well as more complex, expensive, or time-consuming approaches.

  14. Spatial Regression and Prediction of Water Quality in a Watershed with Complex Pollution Sources.

    Science.gov (United States)

    Yang, Xiaoying; Liu, Qun; Luo, Xingzhang; Zheng, Zheng

    2017-08-16

    Fast economic development, burgeoning population growth, and rapid urbanization have led to complex pollution sources contributing to water quality deterioration simultaneously in many developing countries including China. This paper explored the use of spatial regression to evaluate the impacts of watershed characteristics on ambient total nitrogen (TN) concentration in a heavily polluted watershed and make predictions across the region. Regression results have confirmed the substantial impact on TN concentration by a variety of point and non-point pollution sources. In addition, spatial regression has yielded better performance than ordinary regression in predicting TN concentrations. Due to its best performance in cross-validation, the river distance based spatial regression model was used to predict TN concentrations across the watershed. The prediction results have revealed a distinct pattern in the spatial distribution of TN concentrations and identified three critical sub-regions in priority for reducing TN loads. Our study results have indicated that spatial regression could potentially serve as an effective tool to facilitate water pollution control in watersheds under diverse physical and socio-economical conditions.

  15. [Predicting individual risk of high healthcare cost to identify complex chronic patients].

    Science.gov (United States)

    Coderch, Jordi; Sánchez-Pérez, Inma; Ibern, Pere; Carreras, Marc; Pérez-Berruezo, Xavier; Inoriza, José M

    2014-01-01

    To develop a predictive model for the risk of high consumption of healthcare resources, and assess the ability of the model to identify complex chronic patients. A cross-sectional study was performed within a healthcare management organization by using individual data from 2 consecutive years (88,795 people). The dependent variable consisted of healthcare costs above the 95th percentile (P95), including all services provided by the organization and pharmaceutical consumption outside of the institution. The predictive variables were age, sex, morbidity-based on clinical risk groups (CRG)-and selected data from previous utilization (use of hospitalization, use of high-cost drugs in ambulatory care, pharmaceutical expenditure). A univariate descriptive analysis was performed. We constructed a logistic regression model with a 95% confidence level and analyzed sensitivity, specificity, positive predictive values (PPV), and the area under the ROC curve (AUC). Individuals incurring costs >P95 accumulated 44% of total healthcare costs and were concentrated in ACRG3 (aggregated CRG level 3) categories related to multiple chronic diseases. All variables were statistically significant except for sex. The model had a sensitivity of 48.4% (CI: 46.9%-49.8%), specificity of 97.2% (CI: 97.0%-97.3%), PPV of 46.5% (CI: 45.0%-47.9%), and an AUC of 0.897 (CI: 0.892 to 0.902). High consumption of healthcare resources is associated with complex chronic morbidity. A model based on age, morbidity, and prior utilization is able to predict high-cost risk and identify a target population requiring proactive care. Copyright © 2013 SESPAS. Published by Elsevier Espana. All rights reserved.

  16. Codon based co-occurrence network motifs in human mitochondria

    Directory of Open Access Journals (Sweden)

    Pramod Shinde

    2017-10-01

    Full Text Available The nucleotide polymorphism in human mitochondrial genome (mtDNA tolled by codon position bias plays an indispensable role in human population dispersion and expansion. Herein, we constructed genome-wide nucleotide co-occurrence networks using a massive data consisting of five different geographical regions and around 3000 samples for each region. We developed a powerful network model to describe complex mitochondrial evolutionary patterns between codon and non-codon positions. It was interesting to report a different evolution of Asian genomes than those of the rest which is divulged by network motifs. We found evidence that mtDNA undergoes substantial amounts of adaptive evolution, a finding which was supported by a number of previous studies. The dominance of higher order motifs indicated the importance of long-range nucleotide co-occurrence in genomic diversity. Most notably, codon motifs apparently underpinned the preferences among codon positions for co-evolution which is probably highly biased during the origin of the genetic code. Our analyses manifested that codon position co-evolution is very well conserved across human sub-populations and independently maintained within human sub-populations implying the selective role of evolutionary processes on codon position co-evolution. Ergo, this study provided a framework to investigate cooperative genomic interactions which are critical in underlying complex mitochondrial evolution.

  17. Identification of important nodes in directed biological networks: a network motif approach.

    Directory of Open Access Journals (Sweden)

    Pei Wang

    Full Text Available Identification of important nodes in complex networks has attracted an increasing attention over the last decade. Various measures have been proposed to characterize the importance of nodes in complex networks, such as the degree, betweenness and PageRank. Different measures consider different aspects of complex networks. Although there are numerous results reported on undirected complex networks, few results have been reported on directed biological networks. Based on network motifs and principal component analysis (PCA, this paper aims at introducing a new measure to characterize node importance in directed biological networks. Investigations on five real-world biological networks indicate that the proposed method can robustly identify actually important nodes in different networks, such as finding command interneurons, global regulators and non-hub but evolutionary conserved actually important nodes in biological networks. Receiver Operating Characteristic (ROC curves for the five networks indicate remarkable prediction accuracy of the proposed measure. The proposed index provides an alternative complex network metric. Potential implications of the related investigations include identifying network control and regulation targets, biological networks modeling and analysis, as well as networked medicine.

  18. Hunting Motifs in Situla Art

    Directory of Open Access Journals (Sweden)

    Andrej Preložnik

    2013-07-01

    Full Text Available Situla art developed as an echo of the toreutic style which had spread from the Near East through the Phoenicians, Greeks and Etruscans as far as the Veneti, Raeti, Histri, and their eastern neighbours in the region of Dolenjska (Lower Carniola. An Early Iron Age phenomenon (c. 600—300 BC, it rep- resents the major and most arresting form of the contemporary visual arts in an area stretching from the foot of the Apennines in the south to the Drava and Sava rivers in the east. Indeed, individual pieces have found their way across the Alpine passes and all the way north to the Danube. In the world and art of the situlae, a prominent role is accorded to ani- mals. They are displayed in numerous representations of human activities on artefacts crafted in the classic situla style – that is, between the late 6th  and early 5th centuries BC – as passive participants (e.g. in pageants or in harness or as an active element of the situla narrative. The most typical example of the latter is the hunting scene. Today we know at least four objects decorat- ed exclusively with hunting themes, and a number of situlae and other larger vessels where hunting scenes are embedded in composite narratives. All this suggests a popularity unparallelled by any other genre. Clearly recognisable are various hunting techniques and weapons, each associated with a particu- lar type of game (Fig. 1. The chase of a stag with javelin, horse and hound is depicted on the long- familiar and repeatedly published fibula of Zagorje (Fig. 2. It displays a hound mauling the stag’s back and a hunter on horseback pursuing a hind, her neck already pierced by the javelin. To judge by the (so far unnoticed shaft end un- der the stag’s muzzle, the hunter would have been brandishing a second jave- lin as well, like the warrior of the Vače fibula or the rider of the Nesactium situla, presumably himself a hunter. Many parallels to his motif are known from Greece, Etruria, and

  19. How Complex, Probable, and Predictable is Genetically Driven Red Queen Chaos?

    Science.gov (United States)

    Duarte, Jorge; Rodrigues, Carla; Januário, Cristina; Martins, Nuno; Sardanyés, Josep

    2015-12-01

    Coevolution between two antagonistic species has been widely studied theoretically for both ecologically- and genetically-driven Red Queen dynamics. A typical outcome of these systems is an oscillatory behavior causing an endless series of one species adaptation and others counter-adaptation. More recently, a mathematical model combining a three-species food chain system with an adaptive dynamics approach revealed genetically driven chaotic Red Queen coevolution. In the present article, we analyze this mathematical model mainly focusing on the impact of species rates of evolution (mutation rates) in the dynamics. Firstly, we analytically proof the boundedness of the trajectories of the chaotic attractor. The complexity of the coupling between the dynamical variables is quantified using observability indices. By using symbolic dynamics theory, we quantify the complexity of genetically driven Red Queen chaos computing the topological entropy of existing one-dimensional iterated maps using Markov partitions. Co-dimensional two bifurcation diagrams are also built from the period ordering of the orbits of the maps. Then, we study the predictability of the Red Queen chaos, found in narrow regions of mutation rates. To extend the previous analyses, we also computed the likeliness of finding chaos in a given region of the parameter space varying other model parameters simultaneously. Such analyses allowed us to compute a mean predictability measure for the system in the explored region of the parameter space. We found that genetically driven Red Queen chaos, although being restricted to small regions of the analyzed parameter space, might be highly unpredictable.

  20. Exploring the C-X…π Halogen Bonding Motif: An Infrared and Raman Study of the Complexes of CF3X (X = Cl, Br and I with the Aromatic Model Compounds Benzene and Toluene

    Directory of Open Access Journals (Sweden)

    Wouter A. Herrebout

    2013-06-01

    Full Text Available The formation of halogen bonded complexes formed between the trifluorohalomethanes CF3Cl, CF3Br and CF3I and the Lewis bases benzene and toluene at temperatures below 150K was investigated using FTIR and Raman spectroscopy. Experiments using liquid krypton as solvent show that for both CF3Br and CF3I substantial fractions of the monomers can be involved in 1:1 complexes. In addition, weak absorptions illustrating the formation of 2:1 complexes between CF3I and benzene are observed. Using spectra recorded at temperatures between 120 and 140 K, observed information on the relative stability was obtained for all complexes by determining the complexation enthalpies in solution. The resulting values for CF3Br.benzene, CF3I.benzene and (CF3I2.benzene are −6.5(3, −7.6(2 and −14.5(9 kJ mol−1. The values for CF3Br.toluene and CF3I.toluene are −6.2(5 and −7.4(5 kJ mol−1. The experimental complexation enthalpies are compared with theoretical data obtained by combining results from MP2/aug-cc-pVDZ(-PP and MP2/aug-cc-pVTZ(-PP ab initio calculations, from statistical thermodynamical calculations and from Monte Carlo Free Energy Perturbation simulations. The data are also compared with results derived for other C-X···π halogen bonded complexes involving unsaturated Lewis bases such as ethene and ethyne.

  1. An AP endonuclease 1-DNA polymerase beta complex: theoretical prediction of interacting surfaces.

    Directory of Open Access Journals (Sweden)

    Alexej Abyzov

    2008-04-01

    Full Text Available Abasic (AP sites in DNA arise through both endogenous and exogenous mechanisms. Since AP sites can prevent replication and transcription, the cell contains systems for their identification and repair. AP endonuclease (APEX1 cleaves the phosphodiester backbone 5' to the AP site. The cleavage, a key step in the base excision repair pathway, is followed by nucleotide insertion and removal of the downstream deoxyribose moiety, performed most often by DNA polymerase beta (pol-beta. While yeast two-hybrid studies and electrophoretic mobility shift assays provide evidence for interaction of APEX1 and pol-beta, the specifics remain obscure. We describe a theoretical study designed to predict detailed interacting surfaces between APEX1 and pol-beta based on published co-crystal structures of each enzyme bound to DNA. Several potentially interacting complexes were identified by sliding the protein molecules along DNA: two with pol-beta located downstream of APEX1 (3' to the damaged site and three with pol-beta located upstream of APEX1 (5' to the damaged site. Molecular dynamics (MD simulations, ensuring geometrical complementarity of interfaces, enabled us to predict interacting residues and calculate binding energies, which in two cases were sufficient (approximately -10.0 kcal/mol to form a stable complex and in one case a weakly interacting complex. Analysis of interface behavior during MD simulation and visual inspection of interfaces allowed us to conclude that complexes with pol-beta at the 3'-side of APEX1 are those most likely to occur in vivo. Additional multiple sequence analyses of APEX1 and pol-beta in related organisms identified a set of correlated mutations of specific residues at the predicted interfaces. Based on these results, we propose that pol-beta in the open or closed conformation interacts and makes a stable interface with APEX1 bound to a cleaved abasic site on the 3' side. The method described here can be used for analysis in

  2. Conserved binding of GCAC motifs by MEC-8, couch potato, and the RBPMS protein family

    Science.gov (United States)

    Soufari, Heddy

    2017-01-01

    Precise regulation of mRNA processing, translation, localization, and stability relies on specific interactions with RNA-binding proteins whose biological function and target preference are dictated by their preferred RNA motifs. The RBPMS family of RNA-binding proteins is defined by a conserved RNA recognition motif (RRM) domain found in metazoan RBPMS/Hermes and RBPMS2, Drosophila couch potato, and MEC-8 from Caenorhabditis elegans. In order to determine the parameters of RNA sequence recognition by the RBPMS family, we have first used the N-terminal domain from MEC-8 in binding assays and have demonstrated a preference for two GCAC motifs optimally separated by >6 nucleotides (nt). We have also determined the crystal structure of the dimeric N-terminal RRM domain from MEC-8 in the unbound form, and in complex with an oligonucleotide harboring two copies of the optimal GCAC motif. The atomic details reveal the molecular network that provides specificity to all four bases in the motif, including multiple hydrogen bonds to the initial guanine. Further studies with human RBPMS, as well as Drosophila couch potato, confirm a general preference for this double GCAC motif by other members of the protein family and the presence of this motif in known targets. PMID:28003515

  3. MODA: an efficient algorithm for network motif discovery in biological networks.

    Science.gov (United States)

    Omidi, Saeed; Schreiber, Falk; Masoudi-Nejad, Ali

    2009-10-01

    In recent years, interest has been growing in the study of complex networks. Since Erdös and Rényi (1960) proposed their random graph model about 50 years ago, many researchers have investigated and shaped this field. Many indicators have been proposed to assess the global features of networks. Recently, an active research area has developed in studying local features named motifs as the building blocks of networks. Unfortunately, network motif discovery is a computationally hard problem and finding rather large motifs (larger than 8 nodes) by means of current algorithms is impractical as it demands too much computational effort. In this paper, we present a new algorithm (MODA) that incorporates techniques such as a pattern growth approach for extracting larger motifs efficiently. We have tested our algorithm and found it able to identify larger motifs with more than 8 nodes more efficiently than most of the current state-of-the-art motif discovery algorithms. While most of the algorithms rely on induced subgraphs as motifs of the networks, MODA is able to extract both induced and non-induced subgraphs simultaneously. The MODA source code is freely available at: http://LBB.ut.ac.ir/Download/LBBsoft/MODA/

  4. Argo_CUDA: Exhaustive GPU based approach for motif discovery in large DNA datasets.

    Science.gov (United States)

    Vishnevsky, Oleg V; Bocharnikov, Andrey V; Kolchanov, Nikolay A

    2018-02-01

    The development of chromatin immunoprecipitation sequencing (ChIP-seq) technology has revolutionized the genetic analysis of the basic mechanisms underlying transcription regulation and led to accumulation of information about a huge amount of DNA sequences. There are a lot of web services which are currently available for de novo motif discovery in datasets containing information about DNA/protein binding. An enormous motif diversity makes their finding challenging. In order to avoid the difficulties, researchers use different stochastic approaches. Unfortunately, the efficiency of the motif discovery programs dramatically declines with the query set size increase. This leads to the fact that only a fraction of top "peak" ChIP-Seq segments can be analyzed or the area of analysis should be narrowed. Thus, the motif discovery in massive datasets remains a challenging issue. Argo_Compute Unified Device Architecture (CUDA) web service is designed to process the massive DNA data. It is a program for the detection of degenerate oligonucleotide motifs of fixed length written in 15-letter IUPAC code. Argo_CUDA is a full-exhaustive approach based on the high-performance GPU technologies. Compared with the existing motif discovery web services, Argo_CUDA shows good prediction quality on simulated sets. The analysis of ChIP-Seq sequences revealed the motifs which correspond to known transcription factor binding sites.

  5. New PAH gene promoter KLF1 and 3'-region C/EBPalpha motifs influence transcription in vitro.

    Science.gov (United States)

    Klaassen, Kristel; Stankovic, Biljana; Kotur, Nikola; Djordjevic, Maja; Zukic, Branka; Nikcevic, Gordana; Ugrin, Milena; Spasovski, Vesna; Srzentic, Sanja; Pavlovic, Sonja; Stojiljkovic, Maja

    2017-02-01

    Phenylketonuria (PKU) is a metabolic disease caused by mutations in the phenylalanine hydroxylase (PAH) gene. Although the PAH genotype remains the main determinant of PKU phenotype severity, genotype-phenotype inconsistencies have been reported. In this study, we focused on unanalysed sequences in non-coding PAH gene regions to assess their possible influence on the PKU phenotype. We transiently transfected HepG2 cells with various chloramphenicol acetyl transferase (CAT) reporter constructs which included PAH gene non-coding regions. Selected non-coding regions were indicated by in silico prediction to contain transcription factor binding sites. Furthermore, electrophoretic mobility shift assay (EMSA) and supershift assays were performed to identify which transcriptional factors were engaged in the interaction. We found novel KLF1 motif in the PAH promoter, which decreases CAT activity by 50 % in comparison to basal transcription in vitro. The cytosine at the c.-170 promoter position creates an additional binding site for the protein complex involving KLF1 transcription factor. Moreover, we assessed for the first time the role of a multivariant variable number tandem repeat (VNTR) region located in the 3'-region of the PAH gene. We found that the VNTR3, VNTR7 and VNTR8 constructs had approximately 60 % of CAT activity. The regulation is mediated by the C/EBPalpha transcription factor, present in protein complex binding to VNTR3. Our study highlighted two novel promoter KLF1 and 3'-region C/EBPalpha motifs in the PAH gene which decrease transcription in vitro and, thus, could be considered as PAH expression modifiers. New transcription motifs in non-coding regions will contribute to better understanding of the PKU phenotype complexity and may become important for the optimisation of PKU treatment.

  6. From nonspecific DNA-protein encounter complexes to the prediction of DNA-protein interactions.

    Directory of Open Access Journals (Sweden)

    Mu Gao

    2009-03-01

    Full Text Available DNA-protein interactions are involved in many essential biological activities. Because there is no simple mapping code between DNA base pairs and protein amino acids, the prediction of DNA-protein interactions is a challenging problem. Here, we present a novel computational approach for predicting DNA-binding protein residues and DNA-protein interaction modes without knowing its specific DNA target sequence. Given the structure of a DNA-binding protein, the method first generates an ensemble of complex structures obtained by rigid-body docking with a nonspecific canonical B-DNA. Representative models are subsequently selected through clustering and ranking by their DNA-protein interfacial energy. Analysis of these encounter complex models suggests that the recognition sites for specific DNA binding are usually favorable interaction sites for the nonspecific DNA probe and that nonspecific DNA-protein interaction modes exhibit some similarity to specific DNA-protein binding modes. Although the method requires as input the knowledge that the protein binds DNA, in benchmark tests, it achieves better performance in identifying DNA-binding sites than three previously established methods, which are based on sophisticated machine-learning techniques. We further apply our method to protein structures predicted through modeling and demonstrate that our method performs satisfactorily on protein models whose root-mean-square Calpha deviation from native is up to 5 A from their native structures. This study provides valuable structural insights into how a specific DNA-binding protein interacts with a nonspecific DNA sequence. The similarity between the specific DNA-protein interaction mode and nonspecific interaction modes may reflect an important sampling step in search of its specific DNA targets by a DNA-binding protein.

  7. QMU as an approach to strengthening the predictive capabilities of complex models.

    Energy Technology Data Exchange (ETDEWEB)

    Gray, Genetha Anne.; Boggs, Paul T.; Grace, Matthew D.

    2010-09-01

    , Bayesian methods for optimal testing in the QMU framework were developed. This completion of this project represent an increased understanding of how to apply and use the QMU process as a means for improving model predictions of the behavior of complex systems. 4

  8. Exploitation of complex network topology for link prediction in biological interactomes

    KAUST Repository

    Alanis Lobato, Gregorio

    2014-06-01

    The network representation of the interactions between proteins and genes allows for a holistic perspective of the complex machinery underlying the living cell. However, the large number of interacting entities within the cell makes network construction a daunting and arduous task, prone to errors and missing information. Fortunately, the structure of biological networks is not different from that of other complex systems, such as social networks, the world-wide web or power grids, for which growth models have been proposed to better understand their structure and function. This means that we can design tools based on these models in order to exploit the topology of biological interactomes with the aim to construct more complete and reliable maps of the cell. In this work, we propose three novel and powerful approaches for the prediction of interactions in biological networks and conclude that it is possible to mine the topology of these complex system representations and produce reliable and biologically meaningful information that enriches the datasets to which we have access today.

  9. Variable complexity online sequential extreme learning machine, with applications to streamflow prediction

    Science.gov (United States)

    Lima, Aranildo R.; Hsieh, William W.; Cannon, Alex J.

    2017-12-01

    In situations where new data arrive continually, online learning algorithms are computationally much less costly than batch learning ones in maintaining the model up-to-date. The extreme learning machine (ELM), a single hidden layer artificial neural network with random weights in the hidden layer, is solved by linear least squares, and has an online learning version, the online sequential ELM (OSELM). As more data become available during online learning, information on the longer time scale becomes available, so ideally the model complexity should be allowed to change, but the number of hidden nodes (HN) remains fixed in OSELM. A variable complexity VC-OSELM algorithm is proposed to dynamically add or remove HN in the OSELM, allowing the model complexity to vary automatically as online learning proceeds. The performance of VC-OSELM was compared with OSELM in daily streamflow predictions at two hydrological stations in British Columbia, Canada, with VC-OSELM significantly outperforming OSELM in mean absolute error, root mean squared error and Nash-Sutcliffe efficiency at both stations.

  10. Predictive Analytics In Healthcare: Medications as a Predictor of Medical Complexity.

    Science.gov (United States)

    Higdon, Roger; Stewart, Elizabeth; Roach, Jared C; Dombrowski, Caroline; Stanberry, Larissa; Clifton, Holly; Kolker, Natali; van Belle, Gerald; Del Beccaro, Mark A; Kolker, Eugene

    2013-12-01

    Children with special healthcare needs (CSHCN) require health and related services that exceed those required by most hospitalized children. A small but growing and important subset of the CSHCN group includes medically complex children (MCCs). MCCs typically have comorbidities and disproportionately consume healthcare resources. To enable strategic planning for the needs of MCCs, simple screens to identify potential MCCs rapidly in a hospital setting are needed. We assessed whether the number of medications used and the class of those medications correlated with MCC status. Retrospective analysis of medication data from the inpatients at Seattle Children's Hospital found that the numbers of inpatient and outpatient medications significantly correlated with MCC status. Numerous variables based on counts of medications, use of individual medications, and use of combinations of medications were considered, resulting in a simple model based on three different counts of medications: outpatient and inpatient drug classes and individual inpatient drug names. The combined model was used to rank the patient population for medical complexity. As a result, simple, objective admission screens for predicting the complexity of patients based on the number and type of medications were implemented.

  11. Binding mode and free energy prediction of fisetin/β-cyclodextrin inclusion complexes

    Directory of Open Access Journals (Sweden)

    Bodee Nutho

    2014-11-01

    Full Text Available In the present study, our aim is to investigate the preferential binding mode and encapsulation of the flavonoid fisetin in the nano-pore of β-cyclodextrin (β-CD at the molecular level using various theoretical approaches: molecular docking, molecular dynamics (MD simulations and binding free energy calculations. The molecular docking suggested four possible fisetin orientations in the cavity through its chromone or phenyl ring with two different geometries of fisetin due to the rotatable bond between the two rings. From the multiple MD results, the phenyl ring of fisetin favours its inclusion into the β-CD cavity, whilst less binding or even unbinding preference was observed in the complexes where the larger chromone ring is located in the cavity. All MM- and QM-PBSA/GBSA free energy predictions supported the more stable fisetin/β-CD complex of the bound phenyl ring. Van der Waals interaction is the key force in forming the complexes. In addition, the quantum mechanics calculations with M06-2X/6-31G(d,p clearly showed that both solvation effect and BSSE correction cannot be neglected for the energy determination of the chosen system.

  12. Simultaneous discovery, estimation and prediction analysis of complex traits using a bayesian mixture model.

    Directory of Open Access Journals (Sweden)

    Gerhard Moser

    2015-04-01

    Full Text Available Gene discovery, estimation of heritability captured by SNP arrays, inference on genetic architecture and prediction analyses of complex traits are usually performed using different statistical models and methods, leading to inefficiency and loss of power. Here we use a Bayesian mixture model that simultaneously allows variant discovery, estimation of genetic variance explained by all variants and prediction of unobserved phenotypes in new samples. We apply the method to simulated data of quantitative traits and Welcome Trust Case Control Consortium (WTCCC data on disease and show that it provides accurate estimates of SNP-based heritability, produces unbiased estimators of risk in new samples, and that it can estimate genetic architecture by partitioning variation across hundreds to thousands of SNPs. We estimated that, depending on the trait, 2,633 to 9,411 SNPs explain all of the SNP-based heritability in the WTCCC diseases. The majority of those SNPs (>96% had small effects, confirming a substantial polygenic component to common diseases. The proportion of the SNP-based variance explained by large effects (each SNP explaining 1% of the variance varied markedly between diseases, ranging from almost zero for bipolar disorder to 72% for type 1 diabetes. Prediction analyses demonstrate that for diseases with major loci, such as type 1 diabetes and rheumatoid arthritis, Bayesian methods outperform profile scoring or mixed model approaches.

  13. Parallel motif extraction from very long sequences

    KAUST Repository

    Sahli, Majed; Mansour, Essam; Kalnis, Panos

    2013-01-01

    Motifs are frequent patterns used to identify biological functionality in genomic sequences, periodicity in time series, or user trends in web logs. In contrast to a lot of existing work that focuses on collections of many short sequences, modern

  14. Deciphering functional glycosaminoglycan motifs in development.

    Science.gov (United States)

    Townley, Robert A; Bülow, Hannes E

    2018-03-23

    Glycosaminoglycans (GAGs) such as heparan sulfate, chondroitin/dermatan sulfate, and keratan sulfate are linear glycans, which when attached to protein backbones form proteoglycans. GAGs are essential components of the extracellular space in metazoans. Extensive modifications of the glycans such as sulfation, deacetylation and epimerization create structural GAG motifs. These motifs regulate protein-protein interactions and are thereby repsonsible for many of the essential functions of GAGs. This review focusses on recent genetic approaches to characterize GAG motifs and their function in defined signaling pathways during development. We discuss a coding approach for GAGs that would enable computational analyses of GAG sequences such as alignments and the computation of position weight matrices to describe GAG motifs. Copyright © 2018 Elsevier Ltd. All rights reserved.

  15. Bayesian centroid estimation for motif discovery.

    Science.gov (United States)

    Carvalho, Luis

    2013-01-01

    Biological sequences may contain patterns that signal important biomolecular functions; a classical example is regulation of gene expression by transcription factors that bind to specific patterns in genomic promoter regions. In motif discovery we are given a set of sequences that share a common motif and aim to identify not only the motif composition, but also the binding sites in each sequence of the set. We propose a new centroid estimator that arises from a refined and meaningful loss function for binding site inference. We discuss the main advantages of centroid estimation for motif discovery, including computational convenience, and how its principled derivation offers further insights about the posterior distribution of binding site configurations. We also illustrate, using simulated and real datasets, that the centroid estimator can differ from the traditional maximum a posteriori or maximum likelihood estimators.

  16. Bayesian centroid estimation for motif discovery.

    Directory of Open Access Journals (Sweden)

    Luis Carvalho

    Full Text Available Biological sequences may contain patterns that signal important biomolecular functions; a classical example is regulation of gene expression by transcription factors that bind to specific patterns in genomic promoter regions. In motif discovery we are given a set of sequences that share a common motif and aim to identify not only the motif composition, but also the binding sites in each sequence of the set. We propose a new centroid estimator that arises from a refined and meaningful loss function for binding site inference. We discuss the main advantages of centroid estimation for motif discovery, including computational convenience, and how its principled derivation offers further insights about the posterior distribution of binding site configurations. We also illustrate, using simulated and real datasets, that the centroid estimator can differ from the traditional maximum a posteriori or maximum likelihood estimators.

  17. ReactionPredictor: prediction of complex chemical reactions at the mechanistic level using machine learning.

    Science.gov (United States)

    Kayala, Matthew A; Baldi, Pierre

    2012-10-22

    Proposing reasonable mechanisms and predicting the course of chemical reactions is important to the practice of organic chemistry. Approaches to reaction prediction have historically used obfuscating representations and manually encoded patterns or rules. Here we present ReactionPredictor, a machine learning approach to reaction prediction that models elementary, mechanistic reactions as interactions between approximate molecular orbitals (MOs). A training data set of productive reactions known to occur at reasonable rates and yields and verified by inclusion in the literature or textbooks is derived from an existing rule-based system and expanded upon with manual curation from graduate level textbooks. Using this training data set of complex polar, hypervalent, radical, and pericyclic reactions, a two-stage machine learning prediction framework is trained and validated. In the first stage, filtering models trained at the level of individual MOs are used to reduce the space of possible reactions to consider. In the second stage, ranking models over the filtered space of possible reactions are used to order the reactions such that the productive reactions are the top ranked. The resulting model, ReactionPredictor, perfectly ranks polar reactions 78.1% of the time and recovers all productive reactions 95.7% of the time when allowing for small numbers of errors. Pericyclic and radical reactions are perfectly ranked 85.8% and 77.0% of the time, respectively, rising to >93% recovery for both reaction types with a small number of allowed errors. Decisions about which of the polar, pericyclic, or radical reaction type ranking models to use can be made with >99% accuracy. Finally, for multistep reaction pathways, we implement the first mechanistic pathway predictor using constrained tree-search to discover a set of reasonable mechanistic steps from given reactants to given products. Webserver implementations of both the single step and pathway versions of Reaction

  18. Structural and Functional Motifs in Influenza Virus RNAs

    Directory of Open Access Journals (Sweden)

    Damien Ferhadian

    2018-03-01

    Full Text Available Influenza A viruses (IAV are responsible for recurrent influenza epidemics and occasional devastating pandemics in humans and animals. They belong to the Orthomyxoviridae family and their genome consists of eight (- sense viral RNA (vRNA segments of different lengths coding for at least 11 viral proteins. A heterotrimeric polymerase complex is bound to the promoter consisting of the 13 5′-terminal and 12 3′-terminal nucleotides of each vRNA, while internal parts of the vRNAs are associated with multiple copies of the viral nucleoprotein (NP, thus forming ribonucleoproteins (vRNP. Transcription and replication of vRNAs result in viral mRNAs (vmRNAs and complementary RNAs (cRNAs, respectively. Complementary RNAs are the exact positive copies of vRNAs; they also form ribonucleoproteins (cRNPs and are intermediate templates in the vRNA amplification process. On the contrary, vmRNAs have a 5′ cap snatched from cellular mRNAs and a 3′ polyA tail, both gained by the viral polymerase complex. Hence, unlike vRNAs and cRNAs, vmRNAs do not have a terminal promoter able to recruit the viral polymerase. Furthermore, synthesis of at least two viral proteins requires vmRNA splicing. Except for extensive analysis of the viral promoter structure and function and a few, mostly bioinformatics, studies addressing the vRNA and vmRNA structure, structural studies of the influenza A vRNAs, cRNAs, and vmRNAs are still in their infancy. The recent crystal structures of the influenza polymerase heterotrimeric complex drastically improved our understanding of the replication and transcription processes. The vRNA structure has been mainly studied in vitro using RNA probing, but its structure has been very recently studied within native vRNPs using crosslinking and RNA probing coupled to next generation RNA sequencing. Concerning vmRNAs, most studies focused on the segment M and NS splice sites and several structures initially predicted by bioinformatics analysis

  19. Pipeline for the Analysis of ChIP-seq Data and New Motif Ranking Procedure

    KAUST Repository

    Ashoor, Haitham

    2011-06-01

    This thesis presents a computational methodology for ab-initio identification of transcription factor binding sites based on ChIP-seq data. This method consists of three main steps, namely ChIP-seq data processing, motif discovery and models selection. A novel method for ranking the models of motifs identified in this process is proposed. This method combines multiple factors in order to rank the provided candidate motifs. It combines the model coverage of the ChIP-seq fragments that contain motifs from which that model is built, the suitable background data made up of shuffled ChIP-seq fragments, and the p-value that resulted from evaluating the model on actual and background data. Two ChIP-seq datasets retrieved from ENCODE project are used to evaluate and demonstrate the ability of the method to predict correct TFBSs with high precision. The first dataset relates to neuron-restrictive silencer factor, NRSF, while the second one corresponds to growth-associated binding protein, GABP. The pipeline system shows high precision prediction for both datasets, as in both cases the top ranked motif closely resembles the known motifs for the respective transcription factors.

  20. Discriminative motif discovery via simulated evolution and random under-sampling.

    Directory of Open Access Journals (Sweden)

    Tao Song

    Full Text Available Conserved motifs in biological sequences are closely related to their structure and functions. Recently, discriminative motif discovery methods have attracted more and more attention. However, little attention has been devoted to the data imbalance problem, which is one of the main reasons affecting the performance of the discriminative models. In this article, a simulated evolution method is applied to solve the multi-class imbalance problem at the stage of data preprocessing, and at the stage of Hidden Markov Models (HMMs training, a random under-sampling method is introduced for the imbalance between the positive and negative datasets. It is shown that, in the task of discovering targeting motifs of nine subcellular compartments, the motifs found by our method are more conserved than the methods without considering data imbalance problem and recover the most known targeting motifs from Minimotif Miner and InterPro. Meanwhile, we use the found motifs to predict protein subcellular localization and achieve higher prediction precision and recall for the minority classes.

  1. Discriminative motif discovery via simulated evolution and random under-sampling.

    Science.gov (United States)

    Song, Tao; Gu, Hong

    2014-01-01

    Conserved motifs in biological sequences are closely related to their structure and functions. Recently, discriminative motif discovery methods have attracted more and more attention. However, little attention has been devoted to the data imbalance problem, which is one of the main reasons affecting the performance of the discriminative models. In this article, a simulated evolution method is applied to solve the multi-class imbalance problem at the stage of data preprocessing, and at the stage of Hidden Markov Models (HMMs) training, a random under-sampling method is introduced for the imbalance between the positive and negative datasets. It is shown that, in the task of discovering targeting motifs of nine subcellular compartments, the motifs found by our method are more conserved than the methods without considering data imbalance problem and recover the most known targeting motifs from Minimotif Miner and InterPro. Meanwhile, we use the found motifs to predict protein subcellular localization and achieve higher prediction precision and recall for the minority classes.

  2. Insertion of tetracysteine motifs into dopamine transporter extracellular domains.

    Directory of Open Access Journals (Sweden)

    Deanna M Navaroli

    Full Text Available The neuronal dopamine transporter (DAT is a major determinant of extracellular dopamine (DA levels and is the primary target for a variety of addictive and therapeutic psychoactive drugs. DAT is acutely regulated by protein kinase C (PKC activation and amphetamine exposure, both of which modulate DAT surface expression by endocytic trafficking. In order to use live imaging approaches to study DAT endocytosis, methods are needed to exclusively label the DAT surface pool. The use of membrane impermeant, sulfonated biarsenic dyes holds potential as one such approach, and requires introduction of an extracellular tetracysteine motif (tetraCys; CCPGCC to facilitate dye binding. In the current study, we took advantage of intrinsic proline-glycine (Pro-Gly dipeptides encoded in predicted DAT extracellular domains to introduce tetraCys motifs into DAT extracellular loops 2, 3, and 4. [(3H]DA uptake studies, surface biotinylation and fluorescence microscopy in PC12 cells indicate that tetraCys insertion into the DAT second extracellular loop results in a functional transporter that maintains PKC-mediated downregulation. Introduction of tetraCys into extracellular loops 3 and 4 yielded DATs with severely compromised function that failed to mature and traffic to the cell surface. This is the first demonstration of successful introduction of a tetracysteine motif into a DAT extracellular domain, and may hold promise for use of biarsenic dyes in live DAT imaging studies.

  3. Organofluorine chemistry: synthesis and conformation of vicinal fluoromethylene motifs.

    Science.gov (United States)

    O'Hagan, David

    2012-04-20

    The C-F bond is the most polar bond in organic chemistry, and thus the bond has a relatively large dipole moment with a significant -ve charge density on the fluorine atom and correspondingly a +ve charge density on carbon. The electrostatic nature of the bond renders it the strongest one in organic chemistry. However, the fluorine atom itself is nonpolarizable, and thus, despite the charge localization on fluorine, it is a poor hydrogen-bonding acceptor. These properties of the C-F bond make it attractive in the design of nonviscous but polar organic compounds, with a polarity limited to influencing the intramolecular nature of the molecule and less so intermolecular interactions with the immediate environment. In this Perspective, the synthesis of aliphatic chains carrying multivicinal fluoromethylene motifs is described. It emerges that the dipoles of adjacent C-F bonds orientate relative to each other, and thus, individual diastereoisomers display different backbone carbon chain conformations. These conformational preferences recognize the influence of the well-known gauche effect associated with 1,2-difluoroethane but extend to considering 1,3-fluorine-fluorine dipolar repulsions. The synthesis of carbon chains carrying two, three, four, five, and six vicinal fluoromethylene motifs is described, with an emphasis on our own research contributions. These motifs obey almost predictable conformational behavior, and they emerge as candidates for inclusion in the design of performance organic molecules. © 2012 American Chemical Society

  4. TOPDOM: database of conservatively located domains and motifs in proteins.

    Science.gov (United States)

    Varga, Julia; Dobson, László; Tusnády, Gábor E

    2016-09-01

    The TOPDOM database-originally created as a collection of domains and motifs located consistently on the same side of the membranes in α-helical transmembrane proteins-has been updated and extended by taking into consideration consistently localized domains and motifs in globular proteins, too. By taking advantage of the recently developed CCTOP algorithm to determine the type of a protein and predict topology in case of transmembrane proteins, and by applying a thorough search for domains and motifs as well as utilizing the most up-to-date version of all source databases, we managed to reach a 6-fold increase in the size of the whole database and a 2-fold increase in the number of transmembrane proteins. TOPDOM database is available at http://topdom.enzim.hu The webpage utilizes the common Apache, PHP5 and MySQL software to provide the user interface for accessing and searching the database. The database itself is generated on a high performance computer. tusnady.gabor@ttk.mta.hu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

  5. Use of Paired Simple and Complex Models to Reduce Predictive Bias and Quantify Uncertainty

    DEFF Research Database (Denmark)

    Doherty, John; Christensen, Steen

    2011-01-01

    -constrained uncertainty analysis. Unfortunately, however, many system and process details on which uncertainty may depend are, by design, omitted from simple models. This can lead to underestimation of the uncertainty associated with many predictions of management interest. The present paper proposes a methodology...... of these details born of the necessity for model outputs to replicate observations of historical system behavior. In contrast, the rapid run times and general numerical reliability of simple models often promulgates good calibration and ready implementation of sophisticated methods of calibration...... that attempts to overcome the problems associated with complex models on the one hand and simple models on the other hand, while allowing access to the benefits each of them offers. It provides a theoretical analysis of the simplification process from a subspace point of view, this yielding insights...

  6. Theoretical prediction of the noble gas complexes HeAuF and NeAuF

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    Ab initio calculations were carried out to investigate the structures and the stability of the noble gas complexes HeAuF and NeAuF through MP2 and CCSD(T) methods.The HeAuF was predicted to have a linear structure with weak He-Au covalent bonding,the distance of which is closer to the covalent limit in comparison with the corresponding van der Waals limit.The dissociation energy with respect to He + AuF was found to be 24 and 26 kJ·mol-1 at the CCSD(T)/basis set B and B’ levels,respectively.However,similar calculations for NeAuF indicate that NeAuF is not a stable species.

  7. Appropriate complexity for the prediction of coastal and estuarine geomorphic behaviour at decadal to centennial scales

    Science.gov (United States)

    French, Jon; Payo, Andres; Murray, Brad; Orford, Julian; Eliot, Matt; Cowell, Peter

    2016-03-01

    Coastal and estuarine landforms provide a physical template that not only accommodates diverse ecosystem functions and human activities, but also mediates flood and erosion risks that are expected to increase with climate change. In this paper, we explore some of the issues associated with the conceptualisation and modelling of coastal morphological change at time and space scales relevant to managers and policy makers. Firstly, we revisit the question of how to define the most appropriate scales at which to seek quantitative predictions of landform change within an age defined by human interference with natural sediment systems and by the prospect of significant changes in climate and ocean forcing. Secondly, we consider the theoretical bases and conceptual frameworks for determining which processes are most important at a given scale of interest and the related problem of how to translate this understanding into models that are computationally feasible, retain a sound physical basis and demonstrate useful predictive skill. In particular, we explore the limitations of a primary scale approach and the extent to which these can be resolved with reference to the concept of the coastal tract and application of systems theory. Thirdly, we consider the importance of different styles of landform change and the need to resolve not only incremental evolution of morphology but also changes in the qualitative dynamics of a system and/or its gross morphological configuration. The extreme complexity and spatially distributed nature of landform systems means that quantitative prediction of future changes must necessarily be approached through mechanistic modelling of some form or another. Geomorphology has increasingly embraced so-called 'reduced complexity' models as a means of moving from an essentially reductionist focus on the mechanics of sediment transport towards a more synthesist view of landform evolution. However, there is little consensus on exactly what constitutes

  8. Consistent on shell renormalisation of electroweakinos in the complex MSSM. LHC and LC predictions

    International Nuclear Information System (INIS)

    Bharucha, Aoife; Weiglein, Georg

    2012-11-01

    We extend the formalism developed earlier (A. C. Fowler and G. Weiglein, 2010) for the renormalisation of the chargino-neutralino sector to the most general case of the MSSM with complex parameters. We show that products of imaginary parts arising from MSSM parameters and from absorptive parts of loop integrals can already contribute to predictions for physical observables at the one-loop level, and demonstrate that the consistent treatment of such contributions gives rise to non-trivial structure, either in the field renormalisation constants or the corrections associated with the external legs of the considered diagrams. We furthermore show that the phases of the parameters in the chargino-neutralino sector do not need to be renormalised at the one-loop level, and demonstrate that the appropriate choice for the mass parameters used as input for the on-shell conditions depends both on the process and the region of MSSM parameter space under consideration. As an application, we compute the complete one-loop results in the MSSM with complex parameters for the process h a →χ + i χ - j (Higgs-propagator corrections have been incorporated up to the two-loop level), which may be of interest for SUSY Higgs searches at the LHC, and for chargino pair-production at an e + e - Linear Collider, e + e - →χ + i χ - j . We investigate the dependence of the theoretical predictions on the phases of the MSSM parameters, analysing in particular the numerical relevance of the absorptive parts of loop integrals.

  9. Consistent on shell renormalisation of electroweakinos in the complex MSSM. LHC and LC predictions

    Energy Technology Data Exchange (ETDEWEB)

    Bharucha, Aoife [Hamburg Univ. (Germany). 2. Inst. fuer Theoretische Physik; Fowler, Alison [Durham Univ. (United Kingdom). IPPP, Dept. of Physics; Moortgat-Pick, Gudrid [Hamburg Univ. (Germany). 2. Inst. fuer Theoretische Physik; Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Weiglein, Georg [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany)

    2012-11-15

    We extend the formalism developed earlier (A. C. Fowler and G. Weiglein, 2010) for the renormalisation of the chargino-neutralino sector to the most general case of the MSSM with complex parameters. We show that products of imaginary parts arising from MSSM parameters and from absorptive parts of loop integrals can already contribute to predictions for physical observables at the one-loop level, and demonstrate that the consistent treatment of such contributions gives rise to non-trivial structure, either in the field renormalisation constants or the corrections associated with the external legs of the considered diagrams. We furthermore show that the phases of the parameters in the chargino-neutralino sector do not need to be renormalised at the one-loop level, and demonstrate that the appropriate choice for the mass parameters used as input for the on-shell conditions depends both on the process and the region of MSSM parameter space under consideration. As an application, we compute the complete one-loop results in the MSSM with complex parameters for the process h{sub a}{yields}{chi}{sup +}{sub i}{chi}{sup -}{sub j} (Higgs-propagator corrections have been incorporated up to the two-loop level), which may be of interest for SUSY Higgs searches at the LHC, and for chargino pair-production at an e{sup +}e{sup -} Linear Collider, e{sup +}e{sup -}{yields}{chi}{sup +}{sub i}{chi}{sup -}{sub j}. We investigate the dependence of the theoretical predictions on the phases of the MSSM parameters, analysing in particular the numerical relevance of the absorptive parts of loop integrals.

  10. Comparative genomics of metabolic capacities of regulons controlled by cis-regulatory RNA motifs in bacteria.

    Science.gov (United States)

    Sun, Eric I; Leyn, Semen A; Kazanov, Marat D; Saier, Milton H; Novichkov, Pavel S; Rodionov, Dmitry A

    2013-09-02

    In silico comparative genomics approaches have been efficiently used for functional prediction and reconstruction of metabolic and regulatory networks. Riboswitches are metabolite-sensing structures often found in bacterial mRNA leaders controlling gene expression on transcriptional or translational levels.An increasing number of riboswitches and other cis-regulatory RNAs have been recently classified into numerous RNA families in the Rfam database. High conservation of these RNA motifs provides a unique advantage for their genomic identification and comparative analysis. A comparative genomics approach implemented in the RegPredict tool was used for reconstruction and functional annotation of regulons controlled by RNAs from 43 Rfam families in diverse taxonomic groups of Bacteria. The inferred regulons include ~5200 cis-regulatory RNAs and more than 12000 target genes in 255 microbial genomes. All predicted RNA-regulated genes were classified into specific and overall functional categories. Analysis of taxonomic distribution of these categories allowed us to establish major functional preferences for each analyzed cis-regulatory RNA motif family. Overall, most RNA motif regulons showed predictable functional content in accordance with their experimentally established effector ligands. Our results suggest that some RNA motifs (including thiamin pyrophosphate and cobalamin riboswitches that control the cofactor metabolism) are widespread and likely originated from the last common ancestor of all bacteria. However, many more analyzed RNA motifs are restricted to a narrow taxonomic group of bacteria and likely represent more recent evolutionary innovations. The reconstructed regulatory networks for major known RNA motifs substantially expand the existing knowledge of transcriptional regulation in bacteria. The inferred regulons can be used for genetic experiments, functional annotations of genes, metabolic reconstruction and evolutionary analysis. The obtained genome

  11. Differential Response of Coral Assemblages to Thermal Stress Underscores the Complexity in Predicting Bleaching Susceptibility.

    Science.gov (United States)

    Chou, Loke Ming; Toh, Tai Chong; Toh, Kok Ben; Ng, Chin Soon Lionel; Cabaitan, Patrick; Tun, Karenne; Goh, Eugene; Afiq-Rosli, Lutfi; Taira, Daisuke; Du, Rosa Celia Poquita; Loke, Hai Xin; Khalis, Aizat; Li, Jinghan; Song, Tiancheng

    2016-01-01

    Coral bleaching events have been predicted to occur more frequently in the coming decades with global warming. The susceptibility of corals to bleaching during thermal stress episodes is dependent on many factors and an understanding of these underlying drivers is crucial for conservation management. In 2013, a mild bleaching episode ensued in response to elevated sea temperature on the sediment-burdened reefs in Singapore. Surveys of seven sites highlighted variable bleaching susceptibility among coral genera-Pachyseris and Podabacia were the most impacted (31% of colonies of both genera bleached). The most susceptible genera such as Acropora and Pocillopora, which were expected to bleach, did not. Susceptibility varied between less than 6% and more than 11% of the corals bleached, at four and three sites respectively. Analysis of four of the most bleached genera revealed that a statistical model that included a combination of the factors (genus, colony size and site) provided a better explanation of the observed bleaching patterns than any single factor alone. This underscored the complexity in predicting the coral susceptibility to future thermal stress events and the importance of monitoring coral bleaching episodes to facilitate more effective management of coral reefs under climate change.

  12. Predicting Mycobacterium tuberculosis Complex Clades Using Knowledge-Based Bayesian Networks

    Directory of Open Access Journals (Sweden)

    Minoo Aminian

    2014-01-01

    Full Text Available We develop a novel approach for incorporating expert rules into Bayesian networks for classification of Mycobacterium tuberculosis complex (MTBC clades. The proposed knowledge-based Bayesian network (KBBN treats sets of expert rules as prior distributions on the classes. Unlike prior knowledge-based support vector machine approaches which require rules expressed as polyhedral sets, KBBN directly incorporates the rules without any modification. KBBN uses data to refine rule-based classifiers when the rule set is incomplete or ambiguous. We develop a predictive KBBN model for 69 MTBC clades found in the SITVIT international collection. We validate the approach using two testbeds that model knowledge of the MTBC obtained from two different experts and large DNA fingerprint databases to predict MTBC genetic clades and sublineages. These models represent strains of MTBC using high-throughput biomarkers called spacer oligonucleotide types (spoligotypes, since these are routinely gathered from MTBC isolates of tuberculosis (TB patients. Results show that incorporating rules into problems can drastically increase classification accuracy if data alone are insufficient. The SITVIT KBBN is publicly available for use on the World Wide Web.

  13. Differential Response of Coral Assemblages to Thermal Stress Underscores the Complexity in Predicting Bleaching Susceptibility

    Science.gov (United States)

    Toh, Kok Ben; Ng, Chin Soon Lionel; Cabaitan, Patrick; Tun, Karenne; Goh, Eugene; Afiq-Rosli, Lutfi; Taira, Daisuke; Du, Rosa Celia Poquita; Loke, Hai Xin; Khalis, Aizat; Li, Jinghan; Song, Tiancheng

    2016-01-01

    Coral bleaching events have been predicted to occur more frequently in the coming decades with global warming. The susceptibility of corals to bleaching during thermal stress episodes is dependent on many factors and an understanding of these underlying drivers is crucial for conservation management. In 2013, a mild bleaching episode ensued in response to elevated sea temperature on the sediment-burdened reefs in Singapore. Surveys of seven sites highlighted variable bleaching susceptibility among coral genera–Pachyseris and Podabacia were the most impacted (31% of colonies of both genera bleached). The most susceptible genera such as Acropora and Pocillopora, which were expected to bleach, did not. Susceptibility varied between less than 6% and more than 11% of the corals bleached, at four and three sites respectively. Analysis of four of the most bleached genera revealed that a statistical model that included a combination of the factors (genus, colony size and site) provided a better explanation of the observed bleaching patterns than any single factor alone. This underscored the complexity in predicting the coral susceptibility to future thermal stress events and the importance of monitoring coral bleaching episodes to facilitate more effective management of coral reefs under climate change. PMID:27438593

  14. Differential Response of Coral Assemblages to Thermal Stress Underscores the Complexity in Predicting Bleaching Susceptibility.

    Directory of Open Access Journals (Sweden)

    Loke Ming Chou

    Full Text Available Coral bleaching events have been predicted to occur more frequently in the coming decades with global warming. The susceptibility of corals to bleaching during thermal stress episodes is dependent on many factors and an understanding of these underlying drivers is crucial for conservation management. In 2013, a mild bleaching episode ensued in response to elevated sea temperature on the sediment-burdened reefs in Singapore. Surveys of seven sites highlighted variable bleaching susceptibility among coral genera-Pachyseris and Podabacia were the most impacted (31% of colonies of both genera bleached. The most susceptible genera such as Acropora and Pocillopora, which were expected to bleach, did not. Susceptibility varied between less than 6% and more than 11% of the corals bleached, at four and three sites respectively. Analysis of four of the most bleached genera revealed that a statistical model that included a combination of the factors (genus, colony size and site provided a better explanation of the observed bleaching patterns than any single factor alone. This underscored the complexity in predicting the coral susceptibility to future thermal stress events and the importance of monitoring coral bleaching episodes to facilitate more effective management of coral reefs under climate change.

  15. Revealing the hidden networks of interaction in mobile animal groups allows prediction of complex behavioral contagion.

    Science.gov (United States)

    Rosenthal, Sara Brin; Twomey, Colin R; Hartnett, Andrew T; Wu, Hai Shan; Couzin, Iain D

    2015-04-14

    Coordination among social animals requires rapid and efficient transfer of information among individuals, which may depend crucially on the underlying structure of the communication network. Establishing the decision-making circuits and networks that give rise to individual behavior has been a central goal of neuroscience. However, the analogous problem of determining the structure of the communication network among organisms that gives rise to coordinated collective behavior, such as is exhibited by schooling fish and flocking birds, has remained almost entirely neglected. Here, we study collective evasion maneuvers, manifested through rapid waves, or cascades, of behavioral change (a ubiquitous behavior among taxa) in schooling fish (Notemigonus crysoleucas). We automatically track the positions and body postures, calculate visual fields of all individuals in schools of ∼150 fish, and determine the functional mapping between socially generated sensory input and motor response during collective evasion. We find that individuals use simple, robust measures to assess behavioral changes in neighbors, and that the resulting networks by which behavior propagates throughout groups are complex, being weighted, directed, and heterogeneous. By studying these interaction networks, we reveal the (complex, fractional) nature of social contagion and establish that individuals with relatively few, but strongly connected, neighbors are both most socially influential and most susceptible to social influence. Furthermore, we demonstrate that we can predict complex cascades of behavioral change at their moment of initiation, before they actually occur. Consequently, despite the intrinsic stochasticity of individual behavior, establishing the hidden communication networks in large self-organized groups facilitates a quantitative understanding of behavioral contagion.

  16. Variation in predicted internal concentrations in relation to PBPK model complexity for rainbow trout

    Energy Technology Data Exchange (ETDEWEB)

    Salmina, E.S.; Wondrousch, D. [UFZ Department of Ecological Chemistry, Helmholtz Centre for Environmental Research, Permoserstr. 15, 04318 Leipzig (Germany); Institute for Organic Chemistry, Technical University Bergakademie Freiberg, Leipziger Str. 29, 09596 Freiberg (Germany); Kühne, R. [UFZ Department of Ecological Chemistry, Helmholtz Centre for Environmental Research, Permoserstr. 15, 04318 Leipzig (Germany); Potemkin, V.A. [Department of Chemistry, South Ural State Medical University, Vorovskogo 64, 454048, Chelyabinsk (Russian Federation); Schüürmann, G. [UFZ Department of Ecological Chemistry, Helmholtz Centre for Environmental Research, Permoserstr. 15, 04318 Leipzig (Germany); Institute for Organic Chemistry, Technical University Bergakademie Freiberg, Leipziger Str. 29, 09596 Freiberg (Germany)

    2016-04-15

    The present study is motivated by the increasing demand to consider internal partitioning into tissues instead of exposure concentrations for the environmental toxicity assessment. To this end, physiologically based pharmacokinetic (PBPK) models can be applied. We evaluated the variation in accuracy of PBPK model outcomes depending on tissue constituents modeled as sorptive phases and chemical distribution tendencies addressed by molecular descriptors. The model performance was examined using data from 150 experiments for 28 chemicals collected from US EPA databases. The simplest PBPK model is based on the “K{sub ow}-lipid content” approach as being traditional for environmental toxicology. The most elaborated one considers five biological sorptive phases (polar and non-polar lipids, water, albumin and the remaining proteins) and makes use of LSER (linear solvation energy relationship) parameters to describe the compound partitioning behavior. The “K{sub ow}-lipid content”-based PBPK model shows more than one order of magnitude difference in predicted and measured values for 37% of the studied exposure experiments while for the most elaborated model this happens only for 7%. It is shown that further improvements could be achieved by introducing corrections for metabolic biotransformation and compound transmission hindrance through a cellular membrane. The analysis of the interface distribution tendencies shows that polar tissue constituents, namely water, polar lipids and proteins, play an important role in the accumulation behavior of polar compounds with H-bond donating functional groups. For compounds without H-bond donating fragments preferable accumulation phases are storage lipids and water depending on compound polarity. - Highlights: • For reliable predictions, models of a certain complexity should be compared. • For reliable predictions non-lipid fish tissue constituents should be considered. • H-donor compounds preferably accumulate in water

  17. Prediction of iodide adsorption on oxides by surface complexation modeling with spectroscopic confirmation.

    Science.gov (United States)

    Nagata, Takahiro; Fukushi, Keisuke; Takahashi, Yoshio

    2009-04-15

    A deficiency in environmental iodine can cause a number of health problems. Understanding how iodine is sequestered by materials is helpful for evaluating and developing methods for minimizing human health effects related to iodine. In addition, (129)I is considered to be strategically important for safety assessment of underground radioactive waste disposal. To assess the long-term stability of disposed radioactive waste, an understanding of (129)I adsorption on geologic materials is essential. Therefore, the adsorption of I(-) on naturally occurring oxides is of environmental concern. The surface charges of hydrous ferric oxide (HFO) in NaI electrolyte solutions were measured by potentiometric acid-base titration. The surface charge data were analyzed by means of an extended triple-layer model (ETLM) for surface complexation modeling to obtain the I(-) adsorption reaction and its equilibrium constant. The adsorption of I(-) was determined to be an outer-sphere process from ETLM analysis, which was consistent with independent X-ray absorption near-edge structure (XANES) observation of I(-) adsorbed on HFO. The adsorption equilibrium constants for I(-) on beta-TiO(2) and gamma-Al(2)O(3) were also evaluated by analyzing the surface charge data of these oxides in NaI solution as reported in the literature. Comparison of these adsorption equilibrium constants for HFO, beta-TiO(2), and gamma-Al(2)O(3) based on site-occupancy standard states permitted prediction of I(-) adsorption equilibrium constants for all oxides by means of the Born solvation theory. The batch adsorption data for I(-) on HFO and amorphous aluminum oxide were reasonably reproduced by ETLM with the predicted equilibrium constants, confirming the validity of the present approach. Using the predicted adsorption equilibrium constants, we calculated distribution coefficient (K(d)) values for I(-) adsorption on common soil minerals as a function of pH and ionic strength.

  18. Variation in predicted internal concentrations in relation to PBPK model complexity for rainbow trout

    International Nuclear Information System (INIS)

    Salmina, E.S.; Wondrousch, D.; Kühne, R.; Potemkin, V.A.; Schüürmann, G.

    2016-01-01

    The present study is motivated by the increasing demand to consider internal partitioning into tissues instead of exposure concentrations for the environmental toxicity assessment. To this end, physiologically based pharmacokinetic (PBPK) models can be applied. We evaluated the variation in accuracy of PBPK model outcomes depending on tissue constituents modeled as sorptive phases and chemical distribution tendencies addressed by molecular descriptors. The model performance was examined using data from 150 experiments for 28 chemicals collected from US EPA databases. The simplest PBPK model is based on the “K_o_w-lipid content” approach as being traditional for environmental toxicology. The most elaborated one considers five biological sorptive phases (polar and non-polar lipids, water, albumin and the remaining proteins) and makes use of LSER (linear solvation energy relationship) parameters to describe the compound partitioning behavior. The “K_o_w-lipid content”-based PBPK model shows more than one order of magnitude difference in predicted and measured values for 37% of the studied exposure experiments while for the most elaborated model this happens only for 7%. It is shown that further improvements could be achieved by introducing corrections for metabolic biotransformation and compound transmission hindrance through a cellular membrane. The analysis of the interface distribution tendencies shows that polar tissue constituents, namely water, polar lipids and proteins, play an important role in the accumulation behavior of polar compounds with H-bond donating functional groups. For compounds without H-bond donating fragments preferable accumulation phases are storage lipids and water depending on compound polarity. - Highlights: • For reliable predictions, models of a certain complexity should be compared. • For reliable predictions non-lipid fish tissue constituents should be considered. • H-donor compounds preferably accumulate in water, polar

  19. Discovery of cell-type specific DNA motif grammar in cis-regulatory elements using random Forest.

    Science.gov (United States)

    Wang, Xin; Lin, Peijie; Ho, Joshua W K

    2018-01-19

    It has been observed that many transcription factors (TFs) can bind to different genomic loci depending on the cell type in which a TF is expressed in, even though the individual TF usually binds to the same core motif in different cell types. How a TF can bind to the genome in such a highly cell-type specific manner, is a critical research question. One hypothesis is that a TF requires co-binding of different TFs in different cell types. If this is the case, it may be possible to observe different combinations of TF motifs - a motif grammar - located at the TF binding sites in different cell types. In this study, we develop a bioinformatics method to systematically identify DNA motifs in TF binding sites across multiple cell types based on published ChIP-seq data, and address two questions: (1) can we build a machine learning classifier to predict cell-type specificity based on motif combinations alone, and (2) can we extract meaningful cell-type specific motif grammars from this classifier model. We present a Random Forest (RF) based approach to build a multi-class classifier to predict the cell-type specificity of a TF binding site given its motif content. We applied this RF classifier to two published ChIP-seq datasets of TF (TCF7L2 and MAX) across multiple cell types. Using cross-validation, we show that motif combinations alone are indeed predictive of cell types. Furthermore, we present a rule mining approach to extract the most discriminatory rules in the RF classifier, thus allowing us to discover the underlying cell-type specific motif grammar. Our bioinformatics analysis supports the hypothesis that combinatorial TF motif patterns are cell-type specific.

  20. The MHC motif viewer: a visualization tool for MHC binding motifs

    DEFF Research Database (Denmark)

    Rapin, Nicolas; Hoof, Ilka; Lund, Ole

    2010-01-01

    is hampered by the lack of tools for browsing and comparing specificity of these molecules. We have developed a Web server, MHC Motif Viewer, which allows the display of the binding motif for MHC class I proteins for human, chimpanzee, rhesus monkey, mouse, and swine, as well as HLA-DR protein sequences...

  1. Analisis Unsur Matematika pada Motif Sulam Usus

    Directory of Open Access Journals (Sweden)

    Fredi Ganda Putra

    2017-12-01

    Full Text Available Based on interviews with researchers sources said that the beginning of the intestine embroidery is an art of genuine crafts. Called the intestine embroidery because this technique is a technique of combining a strand of cloth resembling the intestine formed according to the pattern by means of embroidered using a thread. Intestinal embroidery techniques were originally used to create a cover of the women's customary wardrobe of Lampung or often referred to as bebe. But not many people in Lampung, especially people who live in Lampung are still many who do not know and recognize the intestine embroidery because most only know tapis only characteristic of Lampung, besides that there are other cultural results that is embroidered intestine. There are still many who do not know that the intestine motif there is a knowledge of mathematics. The researcher's problem formulation is whether there are mathematical elements contained in the intestine embroidery motif based on the concept of geometry. The purpose of this study is to determine whether there are elements of mathematics contained in the intestine motif based on the concept of geometry. Subjects in this study consisted of 4 people obtained by purposive sampling technique. From the results of data analysis conducted by using descriptive analysis and discussion as follows: (1 Intestinal embroidery motif contains the meaning of mathematics and culture or often called Etnomatematika. On the meaning of culture there is a link between the embroidery intestine with a culture that has been there before as the existence of cultural linkage between Hindu belief Buddhism and there are similarities of motifs and decorative patterns contained in the motif embroidery intestine with ornamental variety in Indonesia. (2 The relationship between the intestine with mathematical motifs there are elements of mathematics such as geometry elements in the form of geometry of dimension one and dimension two, and the

  2. WildSpan: mining structured motifs from protein sequences

    Directory of Open Access Journals (Sweden)

    Chen Chien-Yu

    2011-03-01

    Full Text Available Abstract Background Automatic extraction of motifs from biological sequences is an important research problem in study of molecular biology. For proteins, it is desired to discover sequence motifs containing a large number of wildcard symbols, as the residues associated with functional sites are usually largely separated in sequences. Discovering such patterns is time-consuming because abundant combinations exist when long gaps (a gap consists of one or more successive wildcards are considered. Mining algorithms often employ constraints to narrow down the search space in order to increase efficiency. However, improper constraint models might degrade the sensitivity and specificity of the motifs discovered by computational methods. We previously proposed a new constraint model to handle large wildcard regions for discovering functional motifs of proteins. The patterns that satisfy the proposed constraint model are called W-patterns. A W-pattern is a structured motif that groups motif symbols into pattern blocks interleaved with large irregular gaps. Considering large gaps reflects the fact that functional residues are not always from a single region of protein sequences, and restricting motif symbols into clusters corresponds to the observation that short motifs are frequently present within protein families. To efficiently discover W-patterns for large-scale sequence annotation and function prediction, this paper first formally introduces the problem to solve and proposes an algorithm named WildSpan (sequential pattern mining across large wildcard regions that incorporates several pruning strategies to largely reduce the mining cost. Results WildSpan is shown to efficiently find W-patterns containing conserved residues that are far separated in sequences. We conducted experiments with two mining strategies, protein-based and family-based mining, to evaluate the usefulness of W-patterns and performance of WildSpan. The protein-based mining mode

  3. Dimensionality of social networks using motifs and eigenvalues.

    Directory of Open Access Journals (Sweden)

    Anthony Bonato

    Full Text Available We consider the dimensionality of social networks, and develop experiments aimed at predicting that dimension. We find that a social network model with nodes and links sampled from an m-dimensional metric space with power-law distributed influence regions best fits samples from real-world networks when m scales logarithmically with the number of nodes of the network. This supports a logarithmic dimension hypothesis, and we provide evidence with two different social networks, Facebook and LinkedIn. Further, we employ two different methods for confirming the hypothesis: the first uses the distribution of motif counts, and the second exploits the eigenvalue distribution.

  4. The occipitofrontal circumference: reliable prediction of the intracranial volume in children with syndromic and complex craniosynostosis.

    Science.gov (United States)

    Rijken, Bianca Francisca Maria; den Ottelander, Bianca Kelly; van Veelen, Marie-Lise Charlotte; Lequin, Maarten Hans; Mathijssen, Irene Margreet Jacqueline

    2015-05-01

    OBJECT Patients with syndromic and complex craniosynostosis are characterized by the premature fusion of one or more cranial sutures. These patients are at risk for developing elevated intracranial pressure (ICP). There are several factors known to contribute to elevated ICP in these patients, including craniocerebral disproportion, hydrocephalus, venous hypertension, and obstructive sleep apnea. However, the causal mechanism is unknown, and patients develop elevated ICP even after skull surgery. In clinical practice, the occipitofrontal circumference (OFC) is used as an indirect measure for intracranial volume (ICV), to evaluate skull growth. However, it remains unknown whether OFC is a reliable predictor of ICV in patients with a severe skull deformity. Therefore, in this study the authors evaluated the relation between ICV and OFC. METHODS Eighty-four CT scans obtained in 69 patients with syndromic and complex craniosynostosis treated at the Erasmus University Medical Center-Sophia Children's Hospital were included. The ICV was calculated based on CT scans by using autosegmentation with an HU threshold CT scans and OFC measurements were matched based on a maximum amount of the time that was allowed between these examinations, which was dependent on age. A Pearson correlation coefficient was calculated to evaluate the correlations between OFC and ICV. The predictive value of OFC, age, and sex on ICV was then further evaluated using a univariate linear mixed model. The significant factors in the univariate analysis were subsequently entered in a multivariate mixed model. RESULTS The correlations found between OFC and ICV were r = 0.908 for the total group (p < 0.001), r = 0.981 for Apert (p < 0.001), r = 0.867 for Crouzon-Pfeiffer (p < 0.001), r = 0.989 for Muenke (p < 0.001), r = 0.858 for Saethre- Chotzen syndrome (p = 0.001), and r = 0.917 for complex craniosynostosis (p < 0.001). Age and OFC were significant predictors of ICV in the univariate linear mixed

  5. Prediction of extreme floods in the Central Andes by means of Complex Networks

    Science.gov (United States)

    Boers, Niklas; Bookhagen, Bodo; Barbosa, Henrique; Marwan, Norbert; Kurths, Jürgen; Marengo, Jose

    2014-05-01

    Based on a non-linear synchronisation measure and complex network theory, we present a novel framework for the prediction of extreme events of spatially embedded, interrelated time series. This method is general in the sense that it can be applied to any type of spatially sampled time series with significant interrelations, ranging from climate observables to biological or stock market data. In this presentation, we apply our method to extreme rainfall in South America and show how this leads to the prediction of more than 60% (90% during El Niño conditions) of extreme rainfall events in the eastern Central Andes of Bolivia and northern Argentina, with only 1% false alarms. From paleoclimatic to decadal time scales, the Central Andes continue to be subject to pronounced changes in climatic conditions. In particular, our and past work shows that frequency as well as magnitudes of extreme rainfall events have increased significantly during past decades, calling for a better understanding of the involved climatic mechanisms. Due to their large spatial extend and occurrence at high elevations, these extreme events often lead to severe floods and landslides with disastrous socioeconomic impacts. They regularly affect tens of thousands of people and produce estimated costs of the order of several hundred million USD. Alongside with the societal value of predicting natural hazards, our study provides insights into the responsible climatic features and suggests interactions between Rossby waves in polar regions and large scale (sub-)tropical moisture transport as a driver of subseasonal variability of the South American monsoon system. Predictable extreme events result from the propagation of extreme rainfall from the region of Buenos Aires towards the Central Andes given characteristic atmospheric conditions. Our results indicate that the role of frontal systems originating from Rossby waves in polar latitudes is much more dominant for controlling extreme rainfall in

  6. Armadillo motifs involved in vesicular transport.

    Directory of Open Access Journals (Sweden)

    Harald Striegl

    Full Text Available Armadillo (ARM repeat proteins function in various cellular processes including vesicular transport and membrane tethering. They contain an imperfect repeating sequence motif that forms a conserved three-dimensional structure. Recently, structural and functional insight into tethering mediated by the ARM-repeat protein p115 has been provided. Here we describe the p115 ARM-motifs for reasons of clarity and nomenclature and show that both sequence and structure are highly conserved among ARM-repeat proteins. We argue that there is no need to invoke repeat types other than ARM repeats for a proper description of the structure of the p115 globular head region. Additionally, we propose to define a new subfamily of ARM-like proteins and show lack of evidence that the ARM motifs found in p115 are present in other long coiled-coil tethering factors of the golgin family.

  7. Motif formation and industry specific topologies in the Japanese business firm network

    Science.gov (United States)

    Maluck, Julian; Donner, Reik V.; Takayasu, Hideki; Takayasu, Misako

    2017-05-01

    Motifs and roles are basic quantities for the characterization of interactions among 3-node subsets in complex networks. In this work, we investigate how the distribution of 3-node motifs can be influenced by modifying the rules of an evolving network model while keeping the statistics of simpler network characteristics, such as the link density and the degree distribution, invariant. We exemplify this problem for the special case of the Japanese Business Firm Network, where a well-studied and relatively simple yet realistic evolving network model is available, and compare the resulting motif distribution in the real-world and simulated networks. To better approximate the motif distribution of the real-world network in the model, we introduce both subgraph dependent and global additional rules. We find that a specific rule that allows only for the merging process between nodes with similar link directionality patterns reduces the observed excess of densely connected motifs with bidirectional links. Our study improves the mechanistic understanding of motif formation in evolving network models to better describe the characteristic features of real-world networks with a scale-free topology.

  8. Short Arginine Motifs Drive Protein Stickiness in the Escherichia coli Cytoplasm.

    Science.gov (United States)

    Kyne, Ciara; Crowley, Peter B

    2017-09-19

    Although essential to numerous biotech applications, knowledge of molecular recognition by arginine-rich motifs in live cells remains limited. 1 H, 15 N HSQC and 19 F NMR spectroscopies were used to investigate the effects of C-terminal -GR n (n = 1-5) motifs on GB1 interactions in Escherichia coli cells and cell extracts. While the "biologically inert" GB1 yields high-quality in-cell spectra, the -GR n fusions with n = 4 or 5 were undetectable. This result suggests that a tetra-arginine motif is sufficient to drive interactions between a test protein and macromolecules in the E. coli cytoplasm. The inclusion of a 12 residue flexible linker between GB1 and the -GR 5 motif did not improve detection of the "inert" domain. In contrast, all of the constructs were detectable in cell lysates and extracts, suggesting that the arginine-mediated complexes were weak. Together these data reveal the significance of weak interactions between short arginine-rich motifs and the E. coli cytoplasm and demonstrate the potential of such motifs to modify protein interactions in living cells. These interactions must be considered in the design of (in vivo) nanoscale assemblies that rely on arginine-rich sequences.

  9. Assessment of algorithms for inferring positional weight matrix motifs of transcription factor binding sites using protein binding microarray data.

    Directory of Open Access Journals (Sweden)

    Yaron Orenstein

    Full Text Available The new technology of protein binding microarrays (PBMs allows simultaneous measurement of the binding intensities of a transcription factor to tens of thousands of synthetic double-stranded DNA probes, covering all possible 10-mers. A key computational challenge is inferring the binding motif from these data. We present a systematic comparison of four methods developed specifically for reconstructing a binding site motif represented as a positional weight matrix from PBM data. The reconstructed motifs were evaluated in terms of three criteria: concordance with reference motifs from the literature and ability to predict in vivo and in vitro bindings. The evaluation encompassed over 200 transcription factors and some 300 assays. The results show a tradeoff between how the methods perform according to the different criteria, and a dichotomy of method types. Algorithms that construct motifs with low information content predict PBM probe ranking more faithfully, while methods that produce highly informative motifs match reference motifs better. Interestingly, in predicting high-affinity binding, all methods give far poorer results for in vivo assays compared to in vitro assays.

  10. Sulfur-induced structural motifs on copper and gold surfaces

    Energy Technology Data Exchange (ETDEWEB)

    Walen, Holly [Iowa State Univ., Ames, IA (United States)

    2016-01-01

    The interaction of sulfur with copper and gold surfaces plays a fundamental role in important phenomena that include coarsening of surface nanostructures, and self-assembly of alkanethiols. Here, we identify and analyze unique sulfur-induced structural motifs observed on the low-index surfaces of these two metals. We seek out these structures in an effort to better understand the fundamental interactions between these metals and sulfur that lends to the stability and favorability of metal-sulfur complexes vs. chemisorbed atomic sulfur. The experimental observations presented here—made under identical conditions—together with extensive DFT analyses, allow comparisons and insights into factors that favor the existence of metal-sulfur complexes, vs. chemisorbed atomic sulfur, on metal terraces. We believe this data will be instrumental in better understanding the complex phenomena occurring between the surfaces of coinage metals and sulfur.

  11. Prediction of posterior ligamentous complex injury in thoracolumbar fractures using non-MRI imaging techniques.

    Science.gov (United States)

    Rajasekaran, Shanmuganathan; Maheswaran, Anupama; Aiyer, Siddharth N; Kanna, Rishi; Dumpa, Srikanth Reddy; Shetty, Ajoy Prasad

    2016-06-01

    We aimed to formulate a radiological index based on plain radiographs and computer tomography (CT) to reliably detect posterior ligamentous complex (PLC) injury without need for MRI. Sixty out of 148 consecutive thoracolumbar fractures with doubtful PLC were assessed with MRI, CT and radiographs. PLC injury was assessed with the following radiological parameters: superior-inferior end plate angle (SIEA), vertebral body height (BH), local kyphosis (LK), inter-spinous distance (ISD) and inter-pedicular distance (IPD) and correlated with MRI findings of PLC injury. Statistical analysis was performed to identify the predictive values for the parameters to identify PLC damage. MRI identified PLC injury in 25/60 cases. The ISD and LK were found to be significant predictors of PLC injury. On radiographs the mean LK with PLC damage was 25.86° compared to 21.02° with an intact PLC (p = 0.006). The ISD difference was 6.70 mm in cases with PLC damage compared to 2.86 mm with an intact PLC (p = 0.011). In CT images, the mean LK with PLC damage was 22.96° compared to 18.44° with an intact PLC ( p = 0.019). The ISD difference was 3.10 mm with PLC damage compared to 1.62 mm without PLC damage (p = 0.005). On plain radiographs the presence of LK greater than 20 °(CI 64-95) and ISD difference greater than 2 mm (CI 70-97) can predict PLC injury. These guidelines may be utilised in the emergency room especially when the associated cost, availability and time delay in performing MRI are a concern.

  12. Simplified Method for Predicting a Functional Class of Proteins in Transcription Factor Complexes

    KAUST Repository

    Piatek, Marek J.

    2013-07-12

    Background:Initiation of transcription is essential for most of the cellular responses to environmental conditions and for cell and tissue specificity. This process is regulated through numerous proteins, their ligands and mutual interactions, as well as interactions with DNA. The key such regulatory proteins are transcription factors (TFs) and transcription co-factors (TcoFs). TcoFs are important since they modulate the transcription initiation process through interaction with TFs. In eukaryotes, transcription requires that TFs form different protein complexes with various nuclear proteins. To better understand transcription regulation, it is important to know the functional class of proteins interacting with TFs during transcription initiation. Such information is not fully available, since not all proteins that act as TFs or TcoFs are yet annotated as such, due to generally partial functional annotation of proteins. In this study we have developed a method to predict, using only sequence composition of the interacting proteins, the functional class of human TF binding partners to be (i) TF, (ii) TcoF, or (iii) other nuclear protein. This allows for complementing the annotation of the currently known pool of nuclear proteins. Since only the knowledge of protein sequences is required in addition to protein interaction, the method should be easily applicable to many species.Results:Based on experimentally validated interactions between human TFs with different TFs, TcoFs and other nuclear proteins, our two classification systems (implemented as a web-based application) achieve high accuracies in distinguishing TFs and TcoFs from other nuclear proteins, and TFs from TcoFs respectively.Conclusion:As demonstrated, given the fact that two proteins are capable of forming direct physical interactions and using only information about their sequence composition, we have developed a completely new method for predicting a functional class of TF interacting protein partners

  13. Comprehensive human transcription factor binding site map for combinatory binding motifs discovery.

    Directory of Open Access Journals (Sweden)

    Arnoldo J Müller-Molina

    Full Text Available To know the map between transcription factors (TFs and their binding sites is essential to reverse engineer the regulation process. Only about 10%-20% of the transcription factor binding motifs (TFBMs have been reported. This lack of data hinders understanding gene regulation. To address this drawback, we propose a computational method that exploits never used TF properties to discover the missing TFBMs and their sites in all human gene promoters. The method starts by predicting a dictionary of regulatory "DNA words." From this dictionary, it distills 4098 novel predictions. To disclose the crosstalk between motifs, an additional algorithm extracts TF combinatorial binding patterns creating a collection of TF regulatory syntactic rules. Using these rules, we narrowed down a list of 504 novel motifs that appear frequently in syntax patterns. We tested the predictions against 509 known motifs confirming that our system can reliably predict ab initio motifs with an accuracy of 81%-far higher than previous approaches. We found that on average, 90% of the discovered combinatorial binding patterns target at least 10 genes, suggesting that to control in an independent manner smaller gene sets, supplementary regulatory mechanisms are required. Additionally, we discovered that the new TFBMs and their combinatorial patterns convey biological meaning, targeting TFs and genes related to developmental functions. Thus, among all the possible available targets in the genome, the TFs tend to regulate other TFs and genes involved in developmental functions. We provide a comprehensive resource for regulation analysis that includes a dictionary of "DNA words," newly predicted motifs and their corresponding combinatorial patterns. Combinatorial patterns are a useful filter to discover TFBMs that play a major role in orchestrating other factors and thus, are likely to lock/unlock cellular functional clusters.

  14. Prediction of radiation ratio and sound transmission of complex extruded panel using wavenumber domain Unite element and boundary element methods

    International Nuclear Information System (INIS)

    Kim, H; Ryue, J; Thompson, D J; Müller, A D

    2016-01-01

    Recently, complex shaped aluminium panels have been adopted in many structures to make them lighter and stronger. The vibro-acoustic behaviour of these complex panels has been of interest for many years but conventional finite element and boundary element methods are not efficient to predict their performance at higher frequencies. Where the cross-sectional properties of the panels are constant in one direction, wavenumber domain numerical analysis can be applied and this becomes more suitable for panels with complex cross-sectional geometries. In this paper, a coupled wavenumber domain finite element and boundary element method is applied to predict the sound radiation from and sound transmission through a double-layered aluminium extruded panel, having a typical shape used in railway carriages. The predicted results are compared with measured ones carried out on a finite length panel and good agreement is found. (paper)

  15. Interdependence of clinical factors predicting cognition in children with tuberous sclerosis complex.

    Science.gov (United States)

    Overwater, I E; Verhaar, B J H; Lingsma, H F; Bindels-de Heus, G C B; van den Ouweland, A M W; Nellist, M; Ten Hoopen, L W; Elgersma, Y; Moll, H A; de Wit, M C Y

    2017-01-01

    Cognitive development in patients with tuberous sclerosis complex is highly variable. Predictors in the infant years would be valuable to counsel parents and to support development. The aim of this study was to confirm factors that have been reported to be independently correlated with cognitive development. 102 patients included in this study were treated at the ENCORE-TSC expertise center of the Erasmus Medical Center-Sophia Children's Hospital. Data from the first 24 months of life were used, including details on epilepsy, motor development and mutation status. Outcome was defined as cognitive development (intellectual equivalent, IE) as measured using tests appropriate to the patients age and cognitive abilities (median age at testing 8.2 years, IQR 4.7-12.0). Univariable and multivariable regression analyses were used. In a univariable analysis, predictors of lower IE were: the presence of infantile spasms (β = -18.3, p = 0.000), a larger number of antiepileptic drugs used (β = -6.3, p = 0.000), vigabatrin not used as first drug (β = -14.6, p = 0.020), corticosteroid treatment (β = -33.2, p = 0.005), and a later age at which the child could walk independently (β = -2.1, p = 0.000). An older age at seizure onset predicted higher IE (β = 1.7, p = 0.000). In a multivariable analysis, only age at seizure onset was significantly correlated to IE (β = 1.2, p = 0.005), contributing to 28% of the variation in IE. In our cohort, age at seizure onset was the only variable that independently predicted IE. Factors predicting cognitive development could aid parents and physicians in finding the appropriate support and schooling for these patients.

  16. Evidence for the additions of clustered interacting nodes during the evolution of protein interaction networks from network motifs

    Directory of Open Access Journals (Sweden)

    Guo Hao

    2011-05-01

    Full Text Available Abstract Background High-throughput screens have revealed large-scale protein interaction networks defining most cellular functions. How the proteins were added to the protein interaction network during its growth is a basic and important issue. Network motifs represent the simplest building blocks of cellular machines and are of biological significance. Results Here we study the evolution of protein interaction networks from the perspective of network motifs. We find that in current protein interaction networks, proteins of the same age class tend to form motifs and such co-origins of motif constituents are affected by their topologies and biological functions. Further, we find that the proteins within motifs whose constituents are of the same age class tend to be densely interconnected, co-evolve and share the same biological functions, and these motifs tend to be within protein complexes. Conclusions Our findings provide novel evidence for the hypothesis of the additions of clustered interacting nodes and point out network motifs, especially the motifs with the dense topology and specific function may play important roles during this process. Our results suggest functional constraints may be the underlying driving force for such additions of clustered interacting nodes.

  17. Latitude, temperature, and habitat complexity predict predation pressure in eelgrass beds across the Northern Hemisphere.

    Science.gov (United States)

    Reynolds, Pamela L; Stachowicz, John J; Hovel, Kevin; Boström, Christoffer; Boyer, Katharyn; Cusson, Mathieu; Eklöf, Johan S; Engel, Friederike G; Engelen, Aschwin H; Eriksson, Britas Klemens; Fodrie, F Joel; Griffin, John N; Hereu, Clara M; Hori, Masakazu; Hanley, Torrance C; Ivanov, Mikhail; Jorgensen, Pablo; Kruschel, Claudia; Lee, Kun-Seop; McGlathery, Karen; Moksnes, Per-Olav; Nakaoka, Masahiro; O'Connor, Mary I; O'Connor, Nessa E; Orth, Robert J; Rossi, Francesca; Ruesink, Jennifer; Sotka, Erik E; Thormar, Jonas; Tomas, Fiona; Unsworth, Richard K F; Whalen, Matthew A; Duffy, J Emmett

    2018-01-01

    Latitudinal gradients in species interactions are widely cited as potential causes or consequences of global patterns of biodiversity. However, mechanistic studies documenting changes in interactions across broad geographic ranges are limited. We surveyed predation intensity on common prey (live amphipods and gastropods) in communities of eelgrass (Zostera marina) at 48 sites across its Northern Hemisphere range, encompassing over 37° of latitude and four continental coastlines. Predation on amphipods declined with latitude on all coasts but declined more strongly along western ocean margins where temperature gradients are steeper. Whereas in situ water temperature at the time of the experiments was uncorrelated with predation, mean annual temperature strongly positively predicted predation, suggesting a more complex mechanism than simply increased metabolic activity at the time of predation. This large-scale biogeographic pattern was modified by local habitat characteristics; predation declined with higher shoot density both among and within sites. Predation rates on gastropods, by contrast, were uniformly low and varied little among sites. The high replication and geographic extent of our study not only provides additional evidence to support biogeographic variation in predation intensity, but also insight into the mechanisms that relate temperature and biogeographic gradients in species interactions. © 2017 by the Ecological Society of America.

  18. Numerical Prediction Of Elastic Springback In An Automotive Complex Structural Part

    International Nuclear Information System (INIS)

    Fratini, Livan; Ingarao, Giuseppe; Micari, Fabrizio; Lo Franco, Andrea

    2007-01-01

    The routing and production of 3D complex parts for automotive applications is characterized by springback phenomena affecting the final geometry of the components both after the stamping operations and the trimming ones. FE analyses have to assure effectiveness and consistency in order to be utilized as design tool to be coupled to proper compensating techniques allowing to obtain the desired geometry at the and of the production sequence. In the present paper the full routing of a DP 600 steel automotive structural part is considered and the springback phenomena occurring after forming and trimming are investigated through FE analyses utilizing two different commercial codes. Althought finite element analysis is successful in simulating industrial sheet forming operations, the accurate and reliable applications of this phenomenon and its numerical prediction has not been widely demonstrated. In this paper the influence of the main numerical parameters has been considered i.e. type of the utilized shell element and number of integration points along the thickness, with the aim to improve the effectiveness and reliability of the numerical results. The obtained results have been compared with the experimental evidences derived from CMM acquisitions

  19. Predictability problems of global change as seen through natural systems complexity description. 2. Approach

    Directory of Open Access Journals (Sweden)

    Vladimir V. Kozoderov

    1998-01-01

    Full Text Available Developing the general statements of the proposed global change theory, outlined in Part 1 of the publication, Kolmogorov's probability space is used to study properties of information measures (unconditional, joint and conditional entropies, information divergence, mutual information, etc.. Sets of elementary events, the specified algebra of their sub-sets and probability measures for the algebra are composite parts of the space. The information measures are analyzed using the mathematical expectance operator and the adequacy between an additive function of sets and their equivalents in the form of the measures. As a result, explanations are given to multispectral satellite imagery visualization procedures using Markov's chains of random variables represented by pixels of the imagery. The proposed formalism of the information measures application enables to describe the natural targets complexity by syntactically governing probabilities. Asserted as that of signal/noise ratios finding for anomalies of natural processes, the predictability problem is solved by analyses of temporal data sets of related measurements for key regions and their background within contextually coherent structures of natural targets and between particular boundaries of the structures.

  20. Disturbance Regimes Predictably Alter Diversity in an Ecologically Complex Bacterial System

    Directory of Open Access Journals (Sweden)

    Sean M. Gibbons

    2016-12-01

    Full Text Available Diversity is often associated with the functional stability of ecological communities from microbes to macroorganisms. Understanding how diversity responds to environmental perturbations and the consequences of this relationship for ecosystem function are thus central challenges in microbial ecology. Unimodal diversity-disturbance relationships, in which maximum diversity occurs at intermediate levels of disturbance, have been predicted for ecosystems where life history tradeoffs separate organisms along a disturbance gradient. However, empirical support for such peaked relationships in macrosystems is mixed, and few studies have explored these relationships in microbial systems. Here we use complex microbial microcosm communities to systematically determine diversity-disturbance relationships over a range of disturbance regimes. We observed a reproducible switch between community states, which gave rise to transient diversity maxima when community states were forced to mix. Communities showed reduced compositional stability when diversity was highest. To further explore these dynamics, we formulated a simple model that reveals specific regimes under which diversity maxima are stable. Together, our results show how both unimodal and non-unimodal diversity-disturbance relationships can be observed as a system switches between two distinct microbial community states; this process likely occurs across a wide range of spatially and temporally heterogeneous microbial ecosystems.

  1. Highly scalable Ab initio genomic motif identification

    KAUST Repository

    Marchand, Benoit; Bajic, Vladimir B.; Kaushik, Dinesh

    2011-01-01

    We present results of scaling an ab initio motif family identification system, Dragon Motif Finder (DMF), to 65,536 processor cores of IBM Blue Gene/P. DMF seeks groups of mutually similar polynucleotide patterns within a set of genomic sequences and builds various motif families from them. Such information is of relevance to many problems in life sciences. Prior attempts to scale such ab initio motif-finding algorithms achieved limited success. We solve the scalability issues using a combination of mixed-mode MPI-OpenMP parallel programming, master-slave work assignment, multi-level workload distribution, multi-level MPI collectives, and serial optimizations. While the scalability of our algorithm was excellent (94% parallel efficiency on 65,536 cores relative to 256 cores on a modest-size problem), the final speedup with respect to the original serial code exceeded 250,000 when serial optimizations are included. This enabled us to carry out many large-scale ab initio motiffinding simulations in a few hours while the original serial code would have needed decades of execution time. Copyright 2011 ACM.

  2. Regulation of TCF ETS-domain transcription factors by helix-loop-helix motifs.

    Science.gov (United States)

    Stinson, Julie; Inoue, Toshiaki; Yates, Paula; Clancy, Anne; Norton, John D; Sharrocks, Andrew D

    2003-08-15

    DNA binding by the ternary complex factor (TCF) subfamily of ETS-domain transcription factors is tightly regulated by intramolecular and intermolecular interactions. The helix-loop-helix (HLH)-containing Id proteins are trans-acting negative regulators of DNA binding by the TCFs. In the TCF, SAP-2/Net/ERP, intramolecular inhibition of DNA binding is promoted by the cis-acting NID region that also contains an HLH-like motif. The NID also acts as a transcriptional repression domain. Here, we have studied the role of HLH motifs in regulating DNA binding and transcription by the TCF protein SAP-1 and how Cdk-mediated phosphorylation affects the inhibitory activity of the Id proteins towards the TCFs. We demonstrate that the NID region of SAP-1 is an autoinhibitory motif that acts to inhibit DNA binding and also functions as a transcription repression domain. This region can be functionally replaced by fusion of Id proteins to SAP-1, whereby the Id moiety then acts to repress DNA binding in cis. Phosphorylation of the Ids by cyclin-Cdk complexes results in reduction in protein-protein interactions between the Ids and TCFs and relief of their DNA-binding inhibitory activity. In revealing distinct mechanisms through which HLH motifs modulate the activity of TCFs, our results therefore provide further insight into the role of HLH motifs in regulating TCF function and how the inhibitory properties of the trans-acting Id HLH proteins are themselves regulated by phosphorylation.

  3. Identification of helix capping and {beta}-turn motifs from NMR chemical shifts

    Energy Technology Data Exchange (ETDEWEB)

    Shen Yang; Bax, Ad, E-mail: bax@nih.gov [National Institutes of Health, Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases (United States)

    2012-03-15

    We present an empirical method for identification of distinct structural motifs in proteins on the basis of experimentally determined backbone and {sup 13}C{sup {beta}} chemical shifts. Elements identified include the N-terminal and C-terminal helix capping motifs and five types of {beta}-turns: I, II, I Prime , II Prime and VIII. Using a database of proteins of known structure, the NMR chemical shifts, together with the PDB-extracted amino acid preference of the helix capping and {beta}-turn motifs are used as input data for training an artificial neural network algorithm, which outputs the statistical probability of finding each motif at any given position in the protein. The trained neural networks, contained in the MICS (motif identification from chemical shifts) program, also provide a confidence level for each of their predictions, and values ranging from ca 0.7-0.9 for the Matthews correlation coefficient of its predictions far exceed those attainable by sequence analysis. MICS is anticipated to be useful both in the conventional NMR structure determination process and for enhancing on-going efforts to determine protein structures solely on the basis of chemical shift information, where it can aid in identifying protein database fragments suitable for use in building such structures.

  4. Dragon polya spotter: Predictor of poly(A) motifs within human genomic DNA sequences

    KAUST Repository

    Kalkatawi, Manal M.

    2011-11-15

    Motivation: Recognition of poly(A) signals in mRNA is relatively straightforward due to the presence of easily recognizable polyadenylic acid tail. However, the task of identifying poly(A) motifs in the primary genomic DNA sequence that correspond to poly(A) signals in mRNA is a far more challenging problem. Recognition of poly(A) signals is important for better gene annotation and understanding of the gene regulation mechanisms. In this work, we present one such poly(A) motif prediction method based on properties of human genomic DNA sequence surrounding a poly(A) motif. These properties include thermodynamic, physico-chemical and statistical characteristics. For predictions, we developed Artificial Neural Network and Random Forest models. These models are trained to recognize 12 most common poly(A) motifs in human DNA. Our predictors are available as a free web-based tool accessible at http://cbrc.kaust.edu.sa/dps. Compared with other reported predictors, our models achieve higher sensitivity and specificity and furthermore provide a consistent level of accuracy for 12 poly(A) motif variants. The Author(s) 2011. Published by Oxford University Press. All rights reserved.

  5. Identification of helix capping and β-turn motifs from NMR chemical shifts

    International Nuclear Information System (INIS)

    Shen Yang; Bax, Ad

    2012-01-01

    We present an empirical method for identification of distinct structural motifs in proteins on the basis of experimentally determined backbone and 13 C β chemical shifts. Elements identified include the N-terminal and C-terminal helix capping motifs and five types of β-turns: I, II, I′, II′ and VIII. Using a database of proteins of known structure, the NMR chemical shifts, together with the PDB-extracted amino acid preference of the helix capping and β-turn motifs are used as input data for training an artificial neural network algorithm, which outputs the statistical probability of finding each motif at any given position in the protein. The trained neural networks, contained in the MICS (motif identification from chemical shifts) program, also provide a confidence level for each of their predictions, and values ranging from ca 0.7–0.9 for the Matthews correlation coefficient of its predictions far exceed those attainable by sequence analysis. MICS is anticipated to be useful both in the conventional NMR structure determination process and for enhancing on-going efforts to determine protein structures solely on the basis of chemical shift information, where it can aid in identifying protein database fragments suitable for use in building such structures.

  6. Energy optimization and prediction of complex petrochemical industries using an improved artificial neural network approach integrating data envelopment analysis

    International Nuclear Information System (INIS)

    Han, Yong-Ming; Geng, Zhi-Qiang; Zhu, Qun-Xiong

    2016-01-01

    Graphical abstract: This paper proposed an energy optimization and prediction of complex petrochemical industries based on a DEA-integrated ANN approach (DEA-ANN). The proposed approach utilizes the DEA model with slack variables for sensitivity analysis to determine the effective decision making units (DMUs) and indicate the optimized direction of the ineffective DMUs. Compared with the traditional ANN approach, the DEA-ANN prediction model is effectively verified by executing a linear comparison between all DMUs and the effective DMUs through the standard data source from the UCI (University of California at Irvine) repository. Finally, the proposed model is validated through an application in a complex ethylene production system of China petrochemical industry. Meanwhile, the optimization result and the prediction value are obtained to reduce energy consumption of the ethylene production system, guide ethylene production and improve energy efficiency. - Highlights: • The DEA-integrated ANN approach is proposed. • The DEA-ANN prediction model is effectively verified through the standard data source from the UCI repository. • The energy optimization and prediction framework of complex petrochemical industries based on the proposed method is obtained. • The proposed method is valid and efficient in improvement of energy efficiency in complex petrochemical plants. - Abstract: Since the complex petrochemical data have characteristics of multi-dimension, uncertainty and noise, it is difficult to accurately optimize and predict the energy usage of complex petrochemical systems. Therefore, this paper proposes a data envelopment analysis (DEA) integrated artificial neural network (ANN) approach (DEA-ANN). The proposed approach utilizes the DEA model with slack variables for sensitivity analysis to determine the effective decision making units (DMUs) and indicate the optimized direction of the ineffective DMUs. Compared with the traditional ANN approach, the DEA

  7. Parallel motif extraction from very long sequences

    KAUST Repository

    Sahli, Majed

    2013-01-01

    Motifs are frequent patterns used to identify biological functionality in genomic sequences, periodicity in time series, or user trends in web logs. In contrast to a lot of existing work that focuses on collections of many short sequences, modern applications require mining of motifs in one very long sequence (i.e., in the order of several gigabytes). For this case, there exist statistical approaches that are fast but inaccurate; or combinatorial methods that are sound and complete. Unfortunately, existing combinatorial methods are serial and very slow. Consequently, they are limited to very short sequences (i.e., a few megabytes), small alphabets (typically 4 symbols for DNA sequences), and restricted types of motifs. This paper presents ACME, a combinatorial method for extracting motifs from a single very long sequence. ACME arranges the search space in contiguous blocks that take advantage of the cache hierarchy in modern architectures, and achieves almost an order of magnitude performance gain in serial execution. It also decomposes the search space in a smart way that allows scalability to thousands of processors with more than 90% speedup. ACME is the only method that: (i) scales to gigabyte-long sequences; (ii) handles large alphabets; (iii) supports interesting types of motifs with minimal additional cost; and (iv) is optimized for a variety of architectures such as multi-core systems, clusters in the cloud, and supercomputers. ACME reduces the extraction time for an exact-length query from 4 hours to 7 minutes on a typical workstation; handles 3 orders of magnitude longer sequences; and scales up to 16, 384 cores on a supercomputer. Copyright is held by the owner/author(s).

  8. DNA motif elucidation using belief propagation

    KAUST Repository

    Wong, Ka-Chun; Chan, Tak-Ming; Peng, Chengbin; Li, Yue; Zhang, Zhaolei

    2013-01-01

    Protein-binding microarray (PBM) is a high-throughout platform that can measure the DNA-binding preference of a protein in a comprehensive and unbiased manner. A typical PBM experiment can measure binding signal intensities of a protein to all the possible DNA k-mers (k = 8 ?10); such comprehensive binding affinity data usually need to be reduced and represented as motif models before they can be further analyzed and applied. Since proteins can often bind to DNA in multiple modes, one of the major challenges is to decompose the comprehensive affinity data into multimodal motif representations. Here, we describe a new algorithm that uses Hidden Markov Models (HMMs) and can derive precise and multimodal motifs using belief propagations. We describe an HMM-based approach using belief propagations (kmerHMM), which accepts and preprocesses PBM probe raw data into median-binding intensities of individual k-mers. The k-mers are ranked and aligned for training an HMM as the underlying motif representation. Multiple motifs are then extracted from the HMM using belief propagations. Comparisons of kmerHMM with other leading methods on several data sets demonstrated its effectiveness and uniqueness. Especially, it achieved the best performance on more than half of the data sets. In addition, the multiple binding modes derived by kmerHMM are biologically meaningful and will be useful in interpreting other genome-wide data such as those generated from ChIP-seq. The executables and source codes are available at the authors' websites: e.g. http://www.cs.toronto.edu/?wkc/kmerHMM. 2013 The Author(s).

  9. DNA motif elucidation using belief propagation.

    Science.gov (United States)

    Wong, Ka-Chun; Chan, Tak-Ming; Peng, Chengbin; Li, Yue; Zhang, Zhaolei

    2013-09-01

    Protein-binding microarray (PBM) is a high-throughout platform that can measure the DNA-binding preference of a protein in a comprehensive and unbiased manner. A typical PBM experiment can measure binding signal intensities of a protein to all the possible DNA k-mers (k=8∼10); such comprehensive binding affinity data usually need to be reduced and represented as motif models before they can be further analyzed and applied. Since proteins can often bind to DNA in multiple modes, one of the major challenges is to decompose the comprehensive affinity data into multimodal motif representations. Here, we describe a new algorithm that uses Hidden Markov Models (HMMs) and can derive precise and multimodal motifs using belief propagations. We describe an HMM-based approach using belief propagations (kmerHMM), which accepts and preprocesses PBM probe raw data into median-binding intensities of individual k-mers. The k-mers are ranked and aligned for training an HMM as the underlying motif representation. Multiple motifs are then extracted from the HMM using belief propagations. Comparisons of kmerHMM with other leading methods on several data sets demonstrated its effectiveness and uniqueness. Especially, it achieved the best performance on more than half of the data sets. In addition, the multiple binding modes derived by kmerHMM are biologically meaningful and will be useful in interpreting other genome-wide data such as those generated from ChIP-seq. The executables and source codes are available at the authors' websites: e.g. http://www.cs.toronto.edu/∼wkc/kmerHMM.

  10. DNA motif elucidation using belief propagation

    KAUST Repository

    Wong, Ka-Chun

    2013-06-29

    Protein-binding microarray (PBM) is a high-throughout platform that can measure the DNA-binding preference of a protein in a comprehensive and unbiased manner. A typical PBM experiment can measure binding signal intensities of a protein to all the possible DNA k-mers (k = 8 ?10); such comprehensive binding affinity data usually need to be reduced and represented as motif models before they can be further analyzed and applied. Since proteins can often bind to DNA in multiple modes, one of the major challenges is to decompose the comprehensive affinity data into multimodal motif representations. Here, we describe a new algorithm that uses Hidden Markov Models (HMMs) and can derive precise and multimodal motifs using belief propagations. We describe an HMM-based approach using belief propagations (kmerHMM), which accepts and preprocesses PBM probe raw data into median-binding intensities of individual k-mers. The k-mers are ranked and aligned for training an HMM as the underlying motif representation. Multiple motifs are then extracted from the HMM using belief propagations. Comparisons of kmerHMM with other leading methods on several data sets demonstrated its effectiveness and uniqueness. Especially, it achieved the best performance on more than half of the data sets. In addition, the multiple binding modes derived by kmerHMM are biologically meaningful and will be useful in interpreting other genome-wide data such as those generated from ChIP-seq. The executables and source codes are available at the authors\\' websites: e.g. http://www.cs.toronto.edu/?wkc/kmerHMM. 2013 The Author(s).

  11. Prediction of heterodimeric protein complexes from weighted protein-protein interaction networks using novel features and kernel functions.

    Directory of Open Access Journals (Sweden)

    Peiying Ruan

    Full Text Available Since many proteins express their functional activity by interacting with other proteins and forming protein complexes, it is very useful to identify sets of proteins that form complexes. For that purpose, many prediction methods for protein complexes from protein-protein interactions have been developed such as MCL, MCODE, RNSC, PCP, RRW, and NWE. These methods have dealt with only complexes with size of more than three because the methods often are based on some density of subgraphs. However, heterodimeric protein complexes that consist of two distinct proteins occupy a large part according to several comprehensive databases of known complexes. In this paper, we propose several feature space mappings from protein-protein interaction data, in which each interaction is weighted based on reliability. Furthermore, we make use of prior knowledge on protein domains to develop feature space mappings, domain composition kernel and its combination kernel with our proposed features. We perform ten-fold cross-validation computational experiments. These results suggest that our proposed kernel considerably outperforms the naive Bayes-based method, which is the best existing method for predicting heterodimeric protein complexes.

  12. CombiMotif: A new algorithm for network motifs discovery in protein-protein interaction networks

    Science.gov (United States)

    Luo, Jiawei; Li, Guanghui; Song, Dan; Liang, Cheng

    2014-12-01

    Discovering motifs in protein-protein interaction networks is becoming a current major challenge in computational biology, since the distribution of the number of network motifs can reveal significant systemic differences among species. However, this task can be computationally expensive because of the involvement of graph isomorphic detection. In this paper, we present a new algorithm (CombiMotif) that incorporates combinatorial techniques to count non-induced occurrences of subgraph topologies in the form of trees. The efficiency of our algorithm is demonstrated by comparing the obtained results with the current state-of-the art subgraph counting algorithms. We also show major differences between unicellular and multicellular organisms. The datasets and source code of CombiMotif are freely available upon request.

  13. The prediction and representation of phase equilibria and physicochemical properties in complex coal ash slag systems

    Energy Technology Data Exchange (ETDEWEB)

    E. Jak; A. Kondratiev; S. Christie; P.C. Hayes [Centre for Coal in Sustainable Development (CCSD), Brisbane (Australia)

    2003-07-01

    A range of problems in coal utilisation technologies, including ash slag flow in slagging gasifiers, deposit formation, slagging, fouling, fusibility tests, fluxing, blending etc, are related to the melting behaviour of the mineral matter in the coal. To assist with solving these practical issues i) thermodynamic modelling of phase equilibria, and ii) viscosity modelling studies are being undertaken at the Pyrometallurgy Research Centre (The University of Queensland, Australia) with support from the Collaborative Research Centre for Coal in Sustainable Development (CCSD). The thermodynamic modelling has been carried out using the computer system FactSage, which is used for the calculation of multi-phase slag / solid / gas / matte / alloy / salt equilibria in multi-component systems of industrial interest. A modified quasi-chemical solution model is used for the liquid slag phase. New model optimisations have been carried out, which have significantly improved the accuracy of the thermodynamic models for coal combustion processes. Viscosity modelling, using a modified Urbain formalism, is carried out in conjunction with FactSage calculations to predict the viscosities of fully liquid as well as heterogeneous, partly crystallised slags. Custom designed software packages are developed using these fundamental models for wider use by industrial researchers and engineers, and for incorporation as process control modules. The new custom-designed computer software package can be used to produce limiting operability diagrams for slag systems. These diagrams are used to describe phase equilibria and physico-chemical properties in complex slag systems. The approach is illustrated with calculations on the system SiO{sub 2}-Al{sub 2}O{sub 3}-FeO-Fe{sub 2}O{sub 3}-CaO at metallic iron saturation, slags produced in coal slagging gasifiers. 28 refs., 7 figs., 1 tab.

  14. Regional differences in brain volume predict the acquisition of skill in a complex real-time strategy videogame.

    Science.gov (United States)

    Basak, Chandramallika; Voss, Michelle W; Erickson, Kirk I; Boot, Walter R; Kramer, Arthur F

    2011-08-01

    Previous studies have found that differences in brain volume among older adults predict performance in laboratory tasks of executive control, memory, and motor learning. In the present study we asked whether regional differences in brain volume as assessed by the application of a voxel-based morphometry technique on high resolution MRI would also be useful in predicting the acquisition of skill in complex tasks, such as strategy-based video games. Twenty older adults were trained for over 20 h to play Rise of Nations, a complex real-time strategy game. These adults showed substantial improvements over the training period in game performance. MRI scans obtained prior to training revealed that the volume of a number of brain regions, which have been previously associated with subsets of the trained skills, predicted a substantial amount of variance in learning on the complex game. Thus, regional differences in brain volume can predict learning in complex tasks that entail the use of a variety of perceptual, cognitive and motor processes. Copyright © 2011 Elsevier Inc. All rights reserved.

  15. EVALUATING PREDICTIVE ERRORS OF A COMPLEX ENVIRONMENTAL MODEL USING A GENERAL LINEAR MODEL AND LEAST SQUARE MEANS

    Science.gov (United States)

    A General Linear Model (GLM) was used to evaluate the deviation of predicted values from expected values for a complex environmental model. For this demonstration, we used the default level interface of the Regional Mercury Cycling Model (R-MCM) to simulate epilimnetic total mer...

  16. Validity of the MicroDYN Approach: Complex Problem Solving Predicts School Grades beyond Working Memory Capacity

    Science.gov (United States)

    Schweizer, Fabian; Wustenberg, Sascha; Greiff, Samuel

    2013-01-01

    This study examines the validity of the complex problem solving (CPS) test MicroDYN by investigating a) the relation between its dimensions--rule identification (exploration strategy), rule knowledge (acquired knowledge), rule application (control performance)--and working memory capacity (WMC), and b) whether CPS predicts school grades in…

  17. Low-Complexity Model Predictive Control of Single-Phase Three-Level Rectifiers with Unbalanced Load

    DEFF Research Database (Denmark)

    Ma, Junpeng; Song, Wensheng; Wang, Xiongfei

    2018-01-01

    The fluctuation of the neutral-point potential in single-phase three-level rectifiers leads to coupling between the line current regulation and dc-link voltage balancing, deteriorating the quality of line current. For addressing this issue, this paper proposes a low-complexity model predictive...

  18. Sequence-based classification using discriminatory motif feature selection.

    Directory of Open Access Journals (Sweden)

    Hao Xiong

    Full Text Available Most existing methods for sequence-based classification use exhaustive feature generation, employing, for example, all k-mer patterns. The motivation behind such (enumerative approaches is to minimize the potential for overlooking important features. However, there are shortcomings to this strategy. First, practical constraints limit the scope of exhaustive feature generation to patterns of length ≤ k, such that potentially important, longer (> k predictors are not considered. Second, features so generated exhibit strong dependencies, which can complicate understanding of derived classification rules. Third, and most importantly, numerous irrelevant features are created. These concerns can compromise prediction and interpretation. While remedies have been proposed, they tend to be problem-specific and not broadly applicable. Here, we develop a generally applicable methodology, and an attendant software pipeline, that is predicated on discriminatory motif finding. In addition to the traditional training and validation partitions, our framework entails a third level of data partitioning, a discovery partition. A discriminatory motif finder is used on sequences and associated class labels in the discovery partition to yield a (small set of features. These features are then used as inputs to a classifier in the training partition. Finally, performance assessment occurs on the validation partition. Important attributes of our approach are its modularity (any discriminatory motif finder and any classifier can be deployed and its universality (all data, including sequences that are unaligned and/or of unequal length, can be accommodated. We illustrate our approach on two nucleosome occupancy datasets and a protein solubility dataset, previously analyzed using enumerative feature generation. Our method achieves excellent performance results, with and without optimization of classifier tuning parameters. A Python pipeline implementing the approach is

  19. Wind Resource Assessment in Complex Terrain with a High-Resolution Numerical Weather Prediction Model

    Science.gov (United States)

    Gruber, Karin; Serafin, Stefano; Grubišić, Vanda; Dorninger, Manfred; Zauner, Rudolf; Fink, Martin

    2014-05-01

    , considering the frequency of wind speed between cut-in and cut-out speed and of winds with a low vertical velocity component only. Wind turbines do not turn on at wind speeds below cut-in speed. Wind turbines are taken off from the generator in the case of wind speeds higher than cut-out speed and inclination angles of the wind vector greater than 8o. All of these parameters were computed at each model grid point in the innermost domain in order to map their spatial variability. The results show that in complex terrain the annual mean wind speed at hub height is not sufficient to predict the capacity factor of a turbine; vertical wind speed and the frequency of horizontal wind speed out of the range of cut-in and cut-out speed contribute substantially to a reduction of the energy harvest and locally high turbulence may considerably raise the building costs.

  20. Solution NMR characterization of Sgf73(1-104) indicates that Zn ion is required to stabilize zinc finger motif

    International Nuclear Information System (INIS)

    Lai, Chaohua; Wu, Minhao; Li, Pan; Shi, Chaowei; Tian, Changlin; Zang, Jianye

    2010-01-01

    Zinc finger motif contains a zinc ion coordinated by several conserved amino acid residues. Yeast Sgf73 protein was identified as a component of SAGA (Spt/Ada/Gcn5 acetyltransferase) multi-subunit complex and Sgf73 protein was known to contain two zinc finger motifs. Sgf73(1-104), containing the first zinc finger motif, was necessary to modulate the deubiquitinase activity of SAGA complex. Here, Sgf73(1-104) was over-expressed using bacterial expression system and purified for solution NMR (nuclear magnetic resonance) structural studies. Secondary structure and site-specific relaxation analysis of Sgf73(1-104) were achieved after solution NMR backbone assignment. Solution NMR and circular dichroism analysis of Sgf73(1-104) after zinc ion removal using chelation reagent EDTA (ethylene-diamine-tetraacetic acid) demonstrated that zinc ion was required to maintain stable conformation of the zinc finger motif.

  1. The WSXWS motif in cytokine receptors is a molecular switch involved in receptor activation

    DEFF Research Database (Denmark)

    Dagil, Robert; Knudsen, Maiken J.; Olsen, Johan Gotthardt

    2012-01-01

    The prolactin receptor (PRLR) is activated by binding of prolactin in a 2:1 complex, but the activation mechanism is poorly understood. PRLR has a conserved WSXWS motif generic to cytokine class I receptors. We have determined the nuclear magnetic resonance solution structure of the membrane...

  2. Intact Mre11/Rad50/Nbs1 Complex Predicts Good Response to Radiotherapy in Early Breast Cancer

    International Nuclear Information System (INIS)

    Soederlund, Karin; Stal, Olle; Skoog, Lambert; Rutqvist, Lars Erik; Nordenskjoeld, Bo; Askmalm, Marie Stenmark

    2007-01-01

    Purpose: To investigate the expression and predictive role of the Mre11/Rad50/Nbs1 (MRN) complex and the ataxia-telangiectasia mutated protein (ATM) for the outcome of radiotherapy in breast cancer patients. Methods and Materials: The protein expression of ATM and the DNA repair proteins in the MRN complex were investigated using immunohistochemistry in tumors from 224 women with early breast cancer, who were randomized to receive postoperative radiotherapy or adjuvant chemotherapy. Results: Compared with normal breast tissue, the staining intensity of Mre11, Rad50, Nbs1, and ATM was reduced in a majority of the tumors. Weak expression of the MRN complex was correlated with high histologic grade and estrogen receptor negativity (p = 0.01 and p 0.0001, respectively). Radiotherapy significantly reduced the risk of local recurrence as compared with chemotherapy (p = 0.04). The greatest benefit of radiotherapy was seen in patients with moderate/strong expression of the MRN complex (relative risk = 0.27, 95% confidence interval = 0.098-0.72, p 0.009), whereas patients with negative/weak MRN expression had no benefit of radiotherapy compared with adjuvant chemotherapy. These results suggest that an intact MRN complex is important for the tumor cell eradicating effect of radiotherapy. Conclusions: Reduced expression of the MRN complex predicts a poor effect of radiotherapy in patients with early breast cancer

  3. Identify Beta-Hairpin Motifs with Quadratic Discriminant Algorithm Based on the Chemical Shifts.

    Directory of Open Access Journals (Sweden)

    Feng YongE

    Full Text Available Successful prediction of the beta-hairpin motif will be helpful for understanding the of the fold recognition. Some algorithms have been proposed for the prediction of beta-hairpin motifs. However, the parameters used by these methods were primarily based on the amino acid sequences. Here, we proposed a novel model for predicting beta-hairpin structure based on the chemical shift. Firstly, we analyzed the statistical distribution of chemical shifts of six nuclei in not beta-hairpin and beta-hairpin motifs. Secondly, we used these chemical shifts as features combined with three algorithms to predict beta-hairpin structure. Finally, we achieved the best prediction, namely sensitivity of 92%, the specificity of 94% with 0.85 of Mathew's correlation coefficient using quadratic discriminant analysis algorithm, which is clearly superior to the same method for the prediction of beta-hairpin structure from 20 amino acid compositions in the three-fold cross-validation. Our finding showed that the chemical shift is an effective parameter for beta-hairpin prediction, suggesting the quadratic discriminant analysis is a powerful algorithm for the prediction of beta-hairpin.

  4. Predicting protein complexes using a supervised learning method combined with local structural information.

    Science.gov (United States)

    Dong, Yadong; Sun, Yongqi; Qin, Chao

    2018-01-01

    The existing protein complex detection methods can be broadly divided into two categories: unsupervised and supervised learning methods. Most of the unsupervised learning methods assume that protein complexes are in dense regions of protein-protein interaction (PPI) networks even though many true complexes are not dense subgraphs. Supervised learning methods utilize the informative properties of known complexes; they often extract features from existing complexes and then use the features to train a classification model. The trained model is used to guide the search process for new complexes. However, insufficient extracted features, noise in the PPI data and the incompleteness of complex data make the classification model imprecise. Consequently, the classification model is not sufficient for guiding the detection of complexes. Therefore, we propose a new robust score function that combines the classification model with local structural information. Based on the score function, we provide a search method that works both forwards and backwards. The results from experiments on six benchmark PPI datasets and three protein complex datasets show that our approach can achieve better performance compared with the state-of-the-art supervised, semi-supervised and unsupervised methods for protein complex detection, occasionally significantly outperforming such methods.

  5. Predicting protein complexes from weighted protein-protein interaction graphs with a novel unsupervised methodology: Evolutionary enhanced Markov clustering.

    Science.gov (United States)

    Theofilatos, Konstantinos; Pavlopoulou, Niki; Papasavvas, Christoforos; Likothanassis, Spiros; Dimitrakopoulos, Christos; Georgopoulos, Efstratios; Moschopoulos, Charalampos; Mavroudi, Seferina

    2015-03-01

    Proteins are considered to be the most important individual components of biological systems and they combine to form physical protein complexes which are responsible for certain molecular functions. Despite the large availability of protein-protein interaction (PPI) information, not much information is available about protein complexes. Experimental methods are limited in terms of time, efficiency, cost and performance constraints. Existing computational methods have provided encouraging preliminary results, but they phase certain disadvantages as they require parameter tuning, some of them cannot handle weighted PPI data and others do not allow a protein to participate in more than one protein complex. In the present paper, we propose a new fully unsupervised methodology for predicting protein complexes from weighted PPI graphs. The proposed methodology is called evolutionary enhanced Markov clustering (EE-MC) and it is a hybrid combination of an adaptive evolutionary algorithm and a state-of-the-art clustering algorithm named enhanced Markov clustering. EE-MC was compared with state-of-the-art methodologies when applied to datasets from the human and the yeast Saccharomyces cerevisiae organisms. Using public available datasets, EE-MC outperformed existing methodologies (in some datasets the separation metric was increased by 10-20%). Moreover, when applied to new human datasets its performance was encouraging in the prediction of protein complexes which consist of proteins with high functional similarity. In specific, 5737 protein complexes were predicted and 72.58% of them are enriched for at least one gene ontology (GO) function term. EE-MC is by design able to overcome intrinsic limitations of existing methodologies such as their inability to handle weighted PPI networks, their constraint to assign every protein in exactly one cluster and the difficulties they face concerning the parameter tuning. This fact was experimentally validated and moreover, new

  6. Improving Radar QPE's in Complex Terrain for Improved Flash Flood Monitoring and Prediction

    Science.gov (United States)

    Cifelli, R.; Streubel, D. P.; Reynolds, D.

    2010-12-01

    Quantitative Precipitation Estimation (QPE) is extremely challenging in regions of complex terrain due to a combination of issues related to sampling. In particular, radar beams are often blocked or scan above the liquid precipitation zone while rain gauge density is often too low to properly characterize the spatial distribution of precipitation. Due to poor radar coverage, rain gauge networks are used by the National Weather Service (NWS) River Forecast Centers as the principal source for QPE across the western U.S. The California Nevada River Forecast Center (CNRFC) uses point rainfall measurements and historical rainfall runoff relationships to derive river stage forecasts. The point measurements are interpolated to a 4 km grid using Parameter-elevation Regressions on Independent Slopes Model (PRISM) data to develop a gridded 6-hour QPE product (hereafter referred to as RFC QPE). Local forecast offices can utilize the Multi-sensor Precipitation Estimator (MPE) software to improve local QPE’s and thus local flash flood monitoring and prediction. MPE uses radar and rain gauge data to develop a combined QPE product at 1-hour intervals. The rain gauge information is used to bias correct the radar precipitation estimates so that, in situations where the rain gauge density and radar coverage are adequate, MPE can take advantage of the spatial coverage of the radar and the “ground truth” of the rain gauges to provide an accurate QPE. The MPE 1-hour QPE analysis should provide better spatial and temporal resolution for short duration hydrologic events as compared to 6-hour analyses. These hourly QPEs are then used to correct radar derived rain rates used by the Flash Flood Monitoring and Prediction (FFMP) software in forecast offices for issuance of flash flood warnings. Although widely used by forecasters across the eastern U.S., MPE is not used extensively by the NWS in the west. Part of the reason for the lack of use of MPE across the west is that there has

  7. Network motif frequency vectors reveal evolving metabolic network organisation.

    Science.gov (United States)

    Pearcy, Nicole; Crofts, Jonathan J; Chuzhanova, Nadia

    2015-01-01

    At the systems level many organisms of interest may be described by their patterns of interaction, and as such, are perhaps best characterised via network or graph models. Metabolic networks, in particular, are fundamental to the proper functioning of many important biological processes, and thus, have been widely studied over the past decade or so. Such investigations have revealed a number of shared topological features, such as a short characteristic path-length, large clustering coefficient and hierarchical modular structure. However, the extent to which evolutionary and functional properties of metabolism manifest via this underlying network architecture remains unclear. In this paper, we employ a novel graph embedding technique, based upon low-order network motifs, to compare metabolic network structure for 383 bacterial species categorised according to a number of biological features. In particular, we introduce a new global significance score which enables us to quantify important evolutionary relationships that exist between organisms and their physical environments. Using this new approach, we demonstrate a number of significant correlations between environmental factors, such as growth conditions and habitat variability, and network motif structure, providing evidence that organism adaptability leads to increased complexities in the resultant metabolic networks.

  8. Prediction of extraction ability during metal complexing with organic phosphorus extractants

    International Nuclear Information System (INIS)

    Rozen, A.M.; Krupnov, B.V.

    1995-01-01

    Quantum-chemical calculations of thermodynamic parameters of complexing of neutral organic phosphorus compounds (phosphates, phosphine oxides and diphosphine dioxides with different substituents) with seven acceptors of different strength have been made. It is shown that in a wide range of the complexes strength change the entropy contribution of the Gibbs energy of complexing depends but slightly both on the ligand basicity and on the acceptor nature. It is ascertained that this reaction series is isoentropic for any Lewis acid. Practicability of the previously used correlation between extractability and complexing enthalpy has been proved. 17 refs., 1 fig., 1 tab

  9. Prediction of complexes of uranyl and organic substances by molecular orbital calculation

    International Nuclear Information System (INIS)

    Nagasaki, S.; Tsushima, S.; Todoriki, M.; Tanaka, S.; Suzuki, A.

    1999-01-01

    Structure of UO 2 2+ complexes with salicylic acid was optimized by using molecular orbital calculation (ab initio method). The bond distances between U and O atoms (O eq ) of carboxyl group and phenyl group in salicylic acid were evaluated and compared with those measured experimentally by Denecke et al. The calculated distance relatively agrees with the experimental one. The frontier electron densities in the complexes were also calculated. Strong localization of frontier electron density in the complexes was not observed, suggesting that the complexes are subject to only weak interactions with rocks, minerals and other compounds in the geosphere. (author)

  10. Host–guest complexes of mixed glycol-bipyridine cryptands: prediction of ion selectivity by quantum chemical calculations, part V

    Directory of Open Access Journals (Sweden)

    Svetlana Begel

    2013-06-01

    Full Text Available The selectivity of the cryptands [2.2.bpy] and [2.bpy.bpy] for the endohedral complexation of alkali, alkaline-earth and earth metal ions was predicted on the basis of the DFT (B3LYP/LANL2DZp calculated structures and complex-formation energies. The cavity size in both cryptands lay between that for [2.2.2] and [bpy.bpy.bpy], such that the complexation of K+, Sr2+ and Tl3+ is most favorable. While the [2.2.bpy] is moderately larger, preferring Rb+ complexation and demonstrating equal priority for Sr2+ and Ba2+, the slightly smaller [2.bpy.bpy] yields more stable cryptates with Na+ and Ca2+. Although the CH2-units containing molecular bars fixed at the bridgehead nitrogen atoms determine the flexibility of the cryptands, the twist angles associated with the bipyridine and glycol building blocks also contribute considerably.

  11. An auxiliary optimization method for complex public transit route network based on link prediction

    Science.gov (United States)

    Zhang, Lin; Lu, Jian; Yue, Xianfei; Zhou, Jialin; Li, Yunxuan; Wan, Qian

    2018-02-01

    Inspired by the missing (new) link prediction and the spurious existing link identification in link prediction theory, this paper establishes an auxiliary optimization method for public transit route network (PTRN) based on link prediction. First, link prediction applied to PTRN is described, and based on reviewing the previous studies, the summary indices set and its algorithms set are collected for the link prediction experiment. Second, through analyzing the topological properties of Jinan’s PTRN established by the Space R method, we found that this is a typical small-world network with a relatively large average clustering coefficient. This phenomenon indicates that the structural similarity-based link prediction will show a good performance in this network. Then, based on the link prediction experiment of the summary indices set, three indices with maximum accuracy are selected for auxiliary optimization of Jinan’s PTRN. Furthermore, these link prediction results show that the overall layout of Jinan’s PTRN is stable and orderly, except for a partial area that requires optimization and reconstruction. The above pattern conforms to the general pattern of the optimal development stage of PTRN in China. Finally, based on the missing (new) link prediction and the spurious existing link identification, we propose optimization schemes that can be used not only to optimize current PTRN but also to evaluate PTRN planning.

  12. Performance of predictive models in phase equilibria of complex associating systems: PC-SAFT and CEOS/GE

    Directory of Open Access Journals (Sweden)

    N. Bender

    2013-03-01

    Full Text Available Cubic equations of state combined with excess Gibbs energy predictive models (like UNIFAC and equations of state based on applied statistical mechanics are among the main alternatives for phase equilibria prediction involving polar substances in wide temperature and pressure ranges. In this work, the predictive performances of the PC-SAFT with association contribution and Peng-Robinson (PR combined with UNIFAC (Do through mixing rules are compared. Binary and multi-component systems involving polar and non-polar substances were analyzed. Results were also compared to experimental data available in the literature. Results show a similar predictive performance for PC-SAFT with association and cubic equations combined with UNIFAC (Do through mixing rules. Although PC-SAFT with association requires less parameters, it is more complex and requires more computation time.

  13. Molecular dynamics simulations of electrostatics and hydration distributions around RNA and DNA motifs

    Science.gov (United States)

    Marlowe, Ashley E.; Singh, Abhishek; Semichaevsky, Andrey V.; Yingling, Yaroslava G.

    2009-03-01

    Nucleic acid nanoparticles can self-assembly through the formation of complementary loop-loop interactions or stem-stem interactions. Presence and concentration of ions can significantly affect the self-assembly process and the stability of the nanostructure. In this presentation we use explicit molecular dynamics simulations to examine the variations in cationic distributions and hydration environment around DNA and RNA helices and loop-loop interactions. Our simulations show that the potassium and sodium ionic distributions are different around RNA and DNA motifs which could be indicative of ion mediated relative stability of loop-loop complexes. Moreover in RNA loop-loop motifs ions are consistently present and exchanged through a distinct electronegative channel. We will also show how we used the specific RNA loop-loop motif to design a RNA hexagonal nanoparticle.

  14. Statistical downscaling of historical monthly mean winds over a coastal region of complex terrain. II. Predicting wind components

    Energy Technology Data Exchange (ETDEWEB)

    Kamp, Derek van der [University of Victoria, Pacific Climate Impacts Consortium, Victoria, BC (Canada); University of Victoria, School of Earth and Ocean Sciences, Victoria, BC (Canada); Curry, Charles L. [Environment Canada University of Victoria, Canadian Centre for Climate Modelling and Analysis, Victoria, BC (Canada); University of Victoria, School of Earth and Ocean Sciences, Victoria, BC (Canada); Monahan, Adam H. [University of Victoria, School of Earth and Ocean Sciences, Victoria, BC (Canada)

    2012-04-15

    A regression-based downscaling technique was applied to monthly mean surface wind observations from stations throughout western Canada as well as from buoys in the Northeast Pacific Ocean over the period 1979-2006. A predictor set was developed from principal component analysis of the three wind components at 500 hPa and mean sea-level pressure taken from the NCEP Reanalysis II. Building on the results of a companion paper, Curry et al. (Clim Dyn 2011), the downscaling was applied to both wind speed and wind components, in an effort to evaluate the utility of each type of predictand. Cross-validated prediction skill varied strongly with season, with autumn and summer displaying the highest and lowest skill, respectively. In most cases wind components were predicted with better skill than wind speeds. The predictive ability of wind components was found to be strongly related to their orientation. Wind components with the best predictions were often oriented along topographically significant features such as constricted valleys, mountain ranges or ocean channels. This influence of directionality on predictive ability is most prominent during autumn and winter at inland sites with complex topography. Stations in regions with relatively flat terrain (where topographic steering is minimal) exhibit inter-station consistencies including region-wide seasonal shifts in the direction of the best predicted wind component. The conclusion that wind components can be skillfully predicted only over a limited range of directions at most stations limits the scope of statistically downscaled wind speed predictions. It seems likely that such limitations apply to other regions of complex terrain as well. (orig.)

  15. Annotating RNA motifs in sequences and alignments.

    Science.gov (United States)

    Gardner, Paul P; Eldai, Hisham

    2015-01-01

    RNA performs a diverse array of important functions across all cellular life. These functions include important roles in translation, building translational machinery and maturing messenger RNA. More recent discoveries include the miRNAs and bacterial sRNAs that regulate gene expression, the thermosensors, riboswitches and other cis-regulatory elements that help prokaryotes sense their environment and eukaryotic piRNAs that suppress transposition. However, there can be a long period between the initial discovery of a RNA and determining its function. We present a bioinformatic approach to characterize RNA motifs, which are critical components of many RNA structure-function relationships. These motifs can, in some instances, provide researchers with functional hypotheses for uncharacterized RNAs. Moreover, we introduce a new profile-based database of RNA motifs--RMfam--and illustrate some applications for investigating the evolution and functional characterization of RNA. All the data and scripts associated with this work are available from: https://github.com/ppgardne/RMfam. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  16. Dynamic motifs in socio-economic networks

    Science.gov (United States)

    Zhang, Xin; Shao, Shuai; Stanley, H. Eugene; Havlin, Shlomo

    2014-12-01

    Socio-economic networks are of central importance in economic life. We develop a method of identifying and studying motifs in socio-economic networks by focusing on “dynamic motifs,” i.e., evolutionary connection patterns that, because of “node acquaintances” in the network, occur much more frequently than random patterns. We examine two evolving bi-partite networks: i) the world-wide commercial ship chartering market and ii) the ship build-to-order market. We find similar dynamic motifs in both bipartite networks, even though they describe different economic activities. We also find that “influence” and “persistence” are strong factors in the interaction behavior of organizations. When two companies are doing business with the same customer, it is highly probable that another customer who currently only has business relationship with one of these two companies, will become customer of the second in the future. This is the effect of influence. Persistence means that companies with close business ties to customers tend to maintain their relationships over a long period of time.

  17. Improving biological understanding and complex trait prediction by integrating prior information in genomic feature models

    DEFF Research Database (Denmark)

    Edwards, Stefan McKinnon

    externally founded information, such as KEGG pathways, Gene Ontology gene sets, or genomic features, and estimate the joint contribution of the genetic variants within these sets to complex trait phenotypes. The analysis of complex trait phenotypes is hampered by the myriad of genes that control the trait...

  18. Exploration of the dynamic properties of protein complexes predicted from spatially constrained protein-protein interaction networks.

    Directory of Open Access Journals (Sweden)

    Eric A Yen

    2014-05-01

    Full Text Available Protein complexes are not static, but rather highly dynamic with subunits that undergo 1-dimensional diffusion with respect to each other. Interactions within protein complexes are modulated through regulatory inputs that alter interactions and introduce new components and deplete existing components through exchange. While it is clear that the structure and function of any given protein complex is coupled to its dynamical properties, it remains a challenge to predict the possible conformations that complexes can adopt. Protein-fragment Complementation Assays detect physical interactions between protein pairs constrained to ≤8 nm from each other in living cells. This method has been used to build networks composed of 1000s of pair-wise interactions. Significantly, these networks contain a wealth of dynamic information, as the assay is fully reversible and the proteins are expressed in their natural context. In this study, we describe a method that extracts this valuable information in the form of predicted conformations, allowing the user to explore the conformational landscape, to search for structures that correlate with an activity state, and estimate the abundance of conformations in the living cell. The generator is based on a Markov Chain Monte Carlo simulation that uses the interaction dataset as input and is constrained by the physical resolution of the assay. We applied this method to an 18-member protein complex composed of the seven core proteins of the budding yeast Arp2/3 complex and 11 associated regulators and effector proteins. We generated 20,480 output structures and identified conformational states using principle component analysis. We interrogated the conformation landscape and found evidence of symmetry breaking, a mixture of likely active and inactive conformational states and dynamic exchange of the core protein Arc15 between core and regulatory components. Our method provides a novel tool for prediction and

  19. Algorithm for predicting the evolution of series of dynamics of complex systems in solving information problems

    Science.gov (United States)

    Kasatkina, T. I.; Dushkin, A. V.; Pavlov, V. A.; Shatovkin, R. R.

    2018-03-01

    In the development of information, systems and programming to predict the series of dynamics, neural network methods have recently been applied. They are more flexible, in comparison with existing analogues and are capable of taking into account the nonlinearities of the series. In this paper, we propose a modified algorithm for predicting the series of dynamics, which includes a method for training neural networks, an approach to describing and presenting input data, based on the prediction by the multilayer perceptron method. To construct a neural network, the values of a series of dynamics at the extremum points and time values corresponding to them, formed based on the sliding window method, are used as input data. The proposed algorithm can act as an independent approach to predicting the series of dynamics, and be one of the parts of the forecasting system. The efficiency of predicting the evolution of the dynamics series for a short-term one-step and long-term multi-step forecast by the classical multilayer perceptron method and a modified algorithm using synthetic and real data is compared. The result of this modification was the minimization of the magnitude of the iterative error that arises from the previously predicted inputs to the inputs to the neural network, as well as the increase in the accuracy of the iterative prediction of the neural network.

  20. CONTEMPORARY USAGE OF TRADITIONAL TURKISH MOTIFS IN PRODUCT DESIGNS

    Directory of Open Access Journals (Sweden)

    Tulay Gumuser

    2012-12-01

    Full Text Available The aim of this study is to identify the traditional Turkish motifs and its relations among present industrial designs. Traditional Turkish motifs played a very important role in 16th century onwards. The arts of the Ottoman Empire were used because of their symbolic meanings and unique styles. When we examine these motifs we encounter; Tiger Stripe, Three Spot (Çintemani, Rumi, Hatayi, Penç, Cloud, Crescent, Star, Crown, Hyacinth, Tulip and Carnation motifs. Nowadays, Turkish designers have begun to use these traditional Turkish motifs in their designs so as to create differences and awareness in the world design. The examples of these industrial designs, using the Turkish motifs, have survived and have Ottoman heritage and historical value. In this study, the Turkish motifs will be examined along with their focus on contemporary Turkish industrial designs used today.

  1. Steady state statistical correlations predict bistability in reaction motifs.

    Science.gov (United States)

    Chakravarty, Suchana; Barik, Debashis

    2017-03-28

    Various cellular decision making processes are regulated by bistable switches that take graded input signals and convert them to binary all-or-none responses. Traditionally, a bistable switch generated by a positive feedback loop is characterized either by a hysteretic signal response curve with two distinct signaling thresholds or by characterizing the bimodality of the response distribution in the bistable region. To identify the intrinsic bistability of a feedback regulated network, here we propose that bistability can be determined by correlating higher order moments and cumulants (≥2) of the joint steady state distributions of two components connected in a positive feedback loop. We performed stochastic simulations of four feedback regulated models with intrinsic bistability and we show that for a bistable switch with variation of the signal dose, the steady state variance vs. covariance adopts a signatory cusp-shaped curve. Further, we find that the (n + 1)th order cross-cumulant vs. nth order cross-cumulant adopts a closed loop structure for at least n = 3. We also propose that our method is capable of identifying systems without intrinsic bistability even though the system may show bimodality in the marginal response distribution. The proposed method can be used to analyze single cell protein data measured at steady state from experiments such as flow cytometry.

  2. Low-complexity Behavioral Model for Predictive Maintenance of Railway Turnouts

    DEFF Research Database (Denmark)

    Barkhordari, Pegah; Galeazzi, Roberto; Tejada, Alejandro de Miguel

    2017-01-01

    Maintenance of railway infrastructures represents a major cost driver for any infrastructure manager since reliability and dependability must be guaranteed at all times. Implementation of predictive maintenance policies relies on the availability of condition monitoring systems able to assess...

  3. Predicting Chiral Nanostructures, Lattices and Superlattices in Complex Multicomponent Nanoparticle Self-Assembly

    KAUST Repository

    Hur, Kahyun; Hennig, Richard G.; Escobedo, Fernando A.; Wiesner, Ulrich

    2012-01-01

    "Bottom up" type nanoparticle (NP) self-assembly is expected to provide facile routes to nanostructured materials for various, for example, energy related, applications. Despite progress in simulations and theories, structure prediction of self

  4. Aplikasi Ornamen Khas Maluku untuk Pengembangan Desain Motif Batik

    Directory of Open Access Journals (Sweden)

    Masiswo Masiswo

    2016-04-01

    Full Text Available ABSTRAKMaluku memiliki banyak ragam hias budaya warisan nilai leluhur berupa ornamen etnis yang merupakan kesenian dan keterampilan kerajinan. Hasil warisan tersebut sampai saat ini masih lestari hidup serta dapat dinikmati sebagai konsumsi rohani yang memuaskan manusia. Berkaitan dengan keberlangsungan nilai-nilai tradisi etnis yang berwujud pada ornamen-ornamen daerah Maluku, maka dikembangkan untuk kebutuhan manusia berupa motif batik pada kain. Pengembangan ornamen ini lebih menekankan pada representasi akan bentuk-bentuk ornamen yang diterapkan pada kerajinan batik berupa motif khas Maluku. Pengembangan alternatif desain motif batik dibuat tiga variasi yang bersumber dari ornamen khas Maluku dibuat prototipe produknya dan diuji ketahanan luntur warnanya. Hasil uji ketahanan luntur warna terhadap gosokan basah dari tiga prototipe produk berpredikat baik sekali terdapat pada “Motif Siwa” dan predikat baik pada motif “Siwa Talang” dan motif “Matahari Siwa Talang”.Kata kunci: desain, Maluku, motif batik, ornamenABSTRACTMaluku has much decorative ancestral cultural heritage value in the form of ornament ethnic arts and crafts skills. The result of the legacy is still sustainable living can be enjoyed as well as satisfying spiritual human consumption.Related to the sustainability of traditional values in the form of ethnic ornaments Maluku, it was developed for human needs in the form of batik cloth . The development of these ornaments will be more emphasis on the representation forms of ornamentation that is applied to a batik motif Maluku. Development of alternative design motif made three variations. The development of three alternative design motifs derived from the Maluku ornaments made and tested a prototype product color fastness. The test results of color fastness to wet rubbing of the three prototypes are excellent products predicated on the "Motif Siwa" and a good rating on the motif "Siwa Talang" and motif "Matahari Siwa

  5. Identity and functions of CxxC-derived motifs.

    Science.gov (United States)

    Fomenko, Dmitri E; Gladyshev, Vadim N

    2003-09-30

    Two cysteines separated by two other residues (the CxxC motif) are employed by many redox proteins for formation, isomerization, and reduction of disulfide bonds and for other redox functions. The place of the C-terminal cysteine in this motif may be occupied by serine (the CxxS motif), modifying the functional repertoire of redox proteins. Here we found that the CxxC motif may also give rise to a motif, in which the C-terminal cysteine is replaced with threonine (the CxxT motif). Moreover, in contrast to a view that the N-terminal cysteine in the CxxC motif always serves as a nucleophilic attacking group, this residue could also be replaced with threonine (the TxxC motif), serine (the SxxC motif), or other residues. In each of these CxxC-derived motifs, the presence of a downstream alpha-helix was strongly favored. A search for conserved CxxC-derived motif/helix patterns in four complete genomes representing bacteria, archaea, and eukaryotes identified known redox proteins and suggested possible redox functions for several additional proteins. Catalytic sites in peroxiredoxins were major representatives of the TxxC motif, whereas those in glutathione peroxidases represented the CxxT motif. Structural assessments indicated that threonines in these enzymes could stabilize catalytic thiolates, suggesting revisions to previously proposed catalytic triads. Each of the CxxC-derived motifs was also observed in natural selenium-containing proteins, in which selenocysteine was present in place of a catalytic cysteine.

  6. Genetic interaction motif finding by expectation maximization – a novel statistical model for inferring gene modules from synthetic lethality

    Directory of Open Access Journals (Sweden)

    Ye Ping

    2005-12-01

    Full Text Available Abstract Background Synthetic lethality experiments identify pairs of genes with complementary function. More direct functional associations (for example greater probability of membership in a single protein complex may be inferred between genes that share synthetic lethal interaction partners than genes that are directly synthetic lethal. Probabilistic algorithms that identify gene modules based on motif discovery are highly appropriate for the analysis of synthetic lethal genetic interaction data and have great potential in integrative analysis of heterogeneous datasets. Results We have developed Genetic Interaction Motif Finding (GIMF, an algorithm for unsupervised motif discovery from synthetic lethal interaction data. Interaction motifs are characterized by position weight matrices and optimized through expectation maximization. Given a seed gene, GIMF performs a nonlinear transform on the input genetic interaction data and automatically assigns genes to the motif or non-motif category. We demonstrate the capacity to extract known and novel pathways for Saccharomyces cerevisiae (budding yeast. Annotations suggested for several uncharacterized genes are supported by recent experimental evidence. GIMF is efficient in computation, requires no training and automatically down-weights promiscuous genes with high degrees. Conclusion GIMF effectively identifies pathways from synthetic lethality data with several unique features. It is mostly suitable for building gene modules around seed genes. Optimal choice of one single model parameter allows construction of gene networks with different levels of confidence. The impact of hub genes the generic probabilistic framework of GIMF may be used to group other types of biological entities such as proteins based on stochastic motifs. Analysis of the strongest motifs discovered by the algorithm indicates that synthetic lethal interactions are depleted between genes within a motif, suggesting that synthetic

  7. Governing Laws of Complex System Predictability under Co-evolving Uncertainty Sources: Theory and Nonlinear Geophysical Applications

    Science.gov (United States)

    Perdigão, R. A. P.

    2017-12-01

    Predictability assessments are traditionally made on a case-by-case basis, often by running the particular model of interest with randomly perturbed initial/boundary conditions and parameters, producing computationally expensive ensembles. These approaches provide a lumped statistical view of uncertainty evolution, without eliciting the fundamental processes and interactions at play in the uncertainty dynamics. In order to address these limitations, we introduce a systematic dynamical framework for predictability assessment and forecast, by analytically deriving governing equations of predictability in terms of the fundamental architecture of dynamical systems, independent of any particular problem under consideration. The framework further relates multiple uncertainty sources along with their coevolutionary interplay, enabling a comprehensive and explicit treatment of uncertainty dynamics along time, without requiring the actual model to be run. In doing so, computational resources are freed and a quick and effective a-priori systematic dynamic evaluation is made of predictability evolution and its challenges, including aspects in the model architecture and intervening variables that may require optimization ahead of initiating any model runs. It further brings out universal dynamic features in the error dynamics elusive to any case specific treatment, ultimately shedding fundamental light on the challenging issue of predictability. The formulated approach, framed with broad mathematical physics generality in mind, is then implemented in dynamic models of nonlinear geophysical systems with various degrees of complexity, in order to evaluate their limitations and provide informed assistance on how to optimize their design and improve their predictability in fundamental dynamical terms.

  8. The value and cost of complexity in predictive modelling: role of tissue anisotropic conductivity and fibre tracts in neuromodulation.

    Science.gov (United States)

    Shahid, Syed Salman; Bikson, Marom; Salman, Humaira; Wen, Peng; Ahfock, Tony

    2014-06-01

    Computational methods are increasingly used to optimize transcranial direct current stimulation (tDCS) dose strategies and yet complexities of existing approaches limit their clinical access. Since predictive modelling indicates the relevance of subject/pathology based data and hence the need for subject specific modelling, the incremental clinical value of increasingly complex modelling methods must be balanced against the computational and clinical time and costs. For example, the incorporation of multiple tissue layers and measured diffusion tensor (DTI) based conductivity estimates increase model precision but at the cost of clinical and computational resources. Costs related to such complexities aggregate when considering individual optimization and the myriad of potential montages. Here, rather than considering if additional details change current-flow prediction, we consider when added complexities influence clinical decisions. Towards developing quantitative and qualitative metrics of value/cost associated with computational model complexity, we considered field distributions generated by two 4 × 1 high-definition montages (m1 = 4 × 1 HD montage with anode at C3 and m2 = 4 × 1 HD montage with anode at C1) and a single conventional (m3 = C3-Fp2) tDCS electrode montage. We evaluated statistical methods, including residual error (RE) and relative difference measure (RDM), to consider the clinical impact and utility of increased complexities, namely the influence of skull, muscle and brain anisotropic conductivities in a volume conductor model. Anisotropy modulated current-flow in a montage and region dependent manner. However, significant statistical changes, produced within montage by anisotropy, did not change qualitative peak and topographic comparisons across montages. Thus for the examples analysed, clinical decision on which dose to select would not be altered by the omission of anisotropic brain conductivity. Results illustrate the need to rationally

  9. The value and cost of complexity in predictive modelling: role of tissue anisotropic conductivity and fibre tracts in neuromodulation

    Science.gov (United States)

    Salman Shahid, Syed; Bikson, Marom; Salman, Humaira; Wen, Peng; Ahfock, Tony

    2014-06-01

    Objectives. Computational methods are increasingly used to optimize transcranial direct current stimulation (tDCS) dose strategies and yet complexities of existing approaches limit their clinical access. Since predictive modelling indicates the relevance of subject/pathology based data and hence the need for subject specific modelling, the incremental clinical value of increasingly complex modelling methods must be balanced against the computational and clinical time and costs. For example, the incorporation of multiple tissue layers and measured diffusion tensor (DTI) based conductivity estimates increase model precision but at the cost of clinical and computational resources. Costs related to such complexities aggregate when considering individual optimization and the myriad of potential montages. Here, rather than considering if additional details change current-flow prediction, we consider when added complexities influence clinical decisions. Approach. Towards developing quantitative and qualitative metrics of value/cost associated with computational model complexity, we considered field distributions generated by two 4 × 1 high-definition montages (m1 = 4 × 1 HD montage with anode at C3 and m2 = 4 × 1 HD montage with anode at C1) and a single conventional (m3 = C3-Fp2) tDCS electrode montage. We evaluated statistical methods, including residual error (RE) and relative difference measure (RDM), to consider the clinical impact and utility of increased complexities, namely the influence of skull, muscle and brain anisotropic conductivities in a volume conductor model. Main results. Anisotropy modulated current-flow in a montage and region dependent manner. However, significant statistical changes, produced within montage by anisotropy, did not change qualitative peak and topographic comparisons across montages. Thus for the examples analysed, clinical decision on which dose to select would not be altered by the omission of anisotropic brain conductivity

  10. Making oxidation potentials predictable: Coordination of additives applied to the electronic fine tuning of an iron(II) complex

    KAUST Repository

    Haslinger, Stefan

    2014-11-03

    This work examines the impact of axially coordinating additives on the electronic structure of a bioinspired octahedral low-spin iron(II) N-heterocyclic carbene (Fe-NHC) complex. Bearing two labile trans-acetonitrile ligands, the Fe-NHC complex, which is also an excellent oxidation catalyst, is prone to axial ligand exchange. Phosphine- and pyridine-based additives are used for substitution of the acetonitrile ligands. On the basis of the resulting defined complexes, predictability of the oxidation potentials is demonstrated, based on a correlation between cyclic voltammetry experiments and density functional theory calculated molecular orbital energies. Fundamental insights into changes of the electronic properties upon axial ligand exchange and the impact on related attributes will finally lead to target-oriented manipulation of the electronic properties and consequently to the effective tuning of the reactivity of bioinspired systems.

  11. Making oxidation potentials predictable: Coordination of additives applied to the electronic fine tuning of an iron(II) complex

    KAUST Repository

    Haslinger, Stefan; Kü ck, Jens W.; Hahn, Eva M.; Cokoja, Mirza; Pö thig, Alexander; Basset, Jean-Marie; Kü hn, Fritz

    2014-01-01

    This work examines the impact of axially coordinating additives on the electronic structure of a bioinspired octahedral low-spin iron(II) N-heterocyclic carbene (Fe-NHC) complex. Bearing two labile trans-acetonitrile ligands, the Fe-NHC complex, which is also an excellent oxidation catalyst, is prone to axial ligand exchange. Phosphine- and pyridine-based additives are used for substitution of the acetonitrile ligands. On the basis of the resulting defined complexes, predictability of the oxidation potentials is demonstrated, based on a correlation between cyclic voltammetry experiments and density functional theory calculated molecular orbital energies. Fundamental insights into changes of the electronic properties upon axial ligand exchange and the impact on related attributes will finally lead to target-oriented manipulation of the electronic properties and consequently to the effective tuning of the reactivity of bioinspired systems.

  12. A range of complex probabilistic models for RNA secondary structure prediction that includes the nearest-neighbor model and more.

    Science.gov (United States)

    Rivas, Elena; Lang, Raymond; Eddy, Sean R

    2012-02-01

    The standard approach for single-sequence RNA secondary structure prediction uses a nearest-neighbor thermodynamic model with several thousand experimentally determined energy parameters. An attractive alternative is to use statistical approaches with parameters estimated from growing databases of structural RNAs. Good results have been reported for discriminative statistical methods using complex nearest-neighbor models, including CONTRAfold, Simfold, and ContextFold. Little work has been reported on generative probabilistic models (stochastic context-free grammars [SCFGs]) of comparable complexity, although probabilistic models are generally easier to train and to use. To explore a range of probabilistic models of increasing complexity, and to directly compare probabilistic, thermodynamic, and discriminative approaches, we created TORNADO, a computational tool that can parse a wide spectrum of RNA grammar architectures (including the standard nearest-neighbor model and more) using a generalized super-grammar that can be parameterized with probabilities, energies, or arbitrary scores. By using TORNADO, we find that probabilistic nearest-neighbor models perform comparably to (but not significantly better than) discriminative methods. We find that complex statistical models are prone to overfitting RNA structure and that evaluations should use structurally nonhomologous training and test data sets. Overfitting has affected at least one published method (ContextFold). The most important barrier to improving statistical approaches for RNA secondary structure prediction is the lack of diversity of well-curated single-sequence RNA secondary structures in current RNA databases.

  13. From link-prediction in brain connectomes and protein interactomes to the local-community-paradigm in complex networks.

    KAUST Repository

    Cannistraci, C.V.

    2013-04-08

    Growth and remodelling impact the network topology of complex systems, yet a general theory explaining how new links arise between existing nodes has been lacking, and little is known about the topological properties that facilitate link-prediction. Here we investigate the extent to which the connectivity evolution of a network might be predicted by mere topological features. We show how a link/community-based strategy triggers substantial prediction improvements because it accounts for the singular topology of several real networks organised in multiple local communities - a tendency here named local-community-paradigm (LCP). We observe that LCP networks are mainly formed by weak interactions and characterise heterogeneous and dynamic systems that use self-organisation as a major adaptation strategy. These systems seem designed for global delivery of information and processing via multiple local modules. Conversely, non-LCP networks have steady architectures formed by strong interactions, and seem designed for systems in which information/energy storage is crucial.

  14. New horizons in mouse immunoinformatics: reliable in silico prediction of mouse class I histocompatibility major complex peptide binding affinity.

    Science.gov (United States)

    Hattotuwagama, Channa K; Guan, Pingping; Doytchinova, Irini A; Flower, Darren R

    2004-11-21

    Quantitative structure-activity relationship (QSAR) analysis is a main cornerstone of modern informatic disciplines. Predictive computational models, based on QSAR technology, of peptide-major histocompatibility complex (MHC) binding affinity have now become a vital component of modern day computational immunovaccinology. Historically, such approaches have been built around semi-qualitative, classification methods, but these are now giving way to quantitative regression methods. The additive method, an established immunoinformatics technique for the quantitative prediction of peptide-protein affinity, was used here to identify the sequence dependence of peptide binding specificity for three mouse class I MHC alleles: H2-D(b), H2-K(b) and H2-K(k). As we show, in terms of reliability the resulting models represent a significant advance on existing methods. They can be used for the accurate prediction of T-cell epitopes and are freely available online ( http://www.jenner.ac.uk/MHCPred).

  15. Multifractality and autoregressive processes of dry spell lengths in Europe: an approach to their complexity and predictability

    Science.gov (United States)

    Lana, X.; Burgueño, A.; Serra, C.; Martínez, M. D.

    2017-01-01

    Dry spell lengths, DSL, defined as the number of consecutive days with daily rain amounts below a given threshold, may provide relevant information about drought regimes. Taking advantage of a daily pluviometric database covering a great extension of Europe, a detailed analysis of the multifractality of the dry spell regimes is achieved. At the same time, an autoregressive process is applied with the aim of predicting DSL. A set of parameters, namely Hurst exponent, H, estimated from multifractal spectrum, f( α), critical Hölder exponent, α 0, for which f( α) reaches its maximum value, spectral width, W, and spectral asymmetry, B, permits a first clustering of European rain gauges in terms of the complexity of their DSL series. This set of parameters also allows distinguishing between time series describing fine- or smooth-structure of the DSL regime by using the complexity index, CI. Results of previous monofractal analyses also permits establishing comparisons between smooth-structures, relatively low correlation dimensions, notable predictive instability and anti-persistence of DSL for European areas, sometimes submitted to long droughts. Relationships are also found between the CI and the mean absolute deviation, MAD, and the optimum autoregressive order, OAO, of an ARIMA( p, d,0) autoregressive process applied to the DSL series. The detailed analysis of the discrepancies between empiric and predicted DSL underlines the uncertainty over predictability of long DSL, particularly for the Mediterranean region.

  16. A dynamic predictive maintenance policy for complex multi-component systems

    International Nuclear Information System (INIS)

    Van Horenbeek, Adriaan; Pintelon, Liliane

    2013-01-01

    The use of prognostic methods in maintenance in order to predict remaining useful life is receiving more attention over the past years. The use of these techniques in maintenance decision making and optimization in multi-component systems is however a still underexplored area. The objective of this paper is to optimally plan maintenance for a multi-component system based on prognostic/predictive information while considering different component dependencies (i.e. economic, structural and stochastic dependence). Consequently, this paper presents a dynamic predictive maintenance policy for multi-component systems that minimizes the long-term mean maintenance cost per unit time. The proposed maintenance policy is a dynamic method as the maintenance schedule is updated when new information on the degradation and remaining useful life of components becomes available. The performance, regarding the objective of minimal long-term mean cost per unit time, of the developed dynamic predictive maintenance policy is compared to five other conventional maintenance policies, these are: block-based maintenance, age-based maintenance, age-based maintenance with grouping, inspection condition-based maintenance and continuous condition-based maintenance. The ability of the predictive maintenance policy to react to changing component deterioration and dependencies within a multi-component system is quantified and the results show significant cost savings

  17. TACO: a general-purpose tool for predicting cell-type-specific transcription factor dimers.

    Science.gov (United States)

    Jankowski, Aleksander; Prabhakar, Shyam; Tiuryn, Jerzy

    2014-03-19

    Cooperative binding of transcription factor (TF) dimers to DNA is increasingly recognized as a major contributor to binding specificity. However, it is likely that the set of known TF dimers is highly incomplete, given that they were discovered using ad hoc approaches, or through computational analyses of limited datasets. Here, we present TACO (Transcription factor Association from Complex Overrepresentation), a general-purpose standalone software tool that takes as input any genome-wide set of regulatory elements and predicts cell-type-specific TF dimers based on enrichment of motif complexes. TACO is the first tool that can accommodate motif complexes composed of overlapping motifs, a characteristic feature of many known TF dimers. Our method comprehensively outperforms existing tools when benchmarked on a reference set of 29 known dimers. We demonstrate the utility and consistency of TACO by applying it to 152 DNase-seq datasets and 94 ChIP-seq datasets. Based on these results, we uncover a general principle governing the structure of TF-TF-DNA ternary complexes, namely that the flexibility of the complex is correlated with, and most likely a consequence of, inter-motif spacing.

  18. UKIRAN KERAWANG ACEH GAYO SEBAGAI INSPIRASI PENCIPTAAN MOTIF BATIK KHAS GAYO

    Directory of Open Access Journals (Sweden)

    Irfa ina Rohana Salma

    2016-12-01

    Full Text Available ABSTRAK Industri batik mulai berkembang di Gayo, tetapi belum memiliki motif batik khas daerah. Oleh karena itu perlu diciptakan motif batik khas Gayo, dengan mengambil inspirasi dari ukiran yang terdapat pada rumah tradisional yang biasa disebut ukiran kerawang Gayo. Tujuan penciptaan seni ini adalah untuk menciptakan motif batik yang memiliki ciri khas Gayo. Metode yang digunakan yaitu eksplorasi ide, perancangan, dan perwujudan menjadi motif batik. Dalam kegiatan ini telah diciptakan enam motif batik khas Gayo yaitu: (1 Motif Ceplok Gayo; (2 Motif Gayo Tegak; (3 Motif Gayo Lurus; (4 Motif Parang Gayo; (5 Motif Gayo Lembut; dan (6 Motif Geometris Gayo. Hasil uji kesukaan terhadap motif kepada lima puluh responden menunjukkan bahwa Motif Ceplok Gayo paling banyak dipilih oleh responden yaitu sebesar 19%, sedangkan Motif Parang Gayo 18%, Motif Gayo Lembut 17%, Motif Geometris Gayo 17%, Motif Gayo Lurus 15% dan Motif Gayo Tegak 14%. Rata-rata motif yang dihasilkan mendapatkan apresiasi yang baik dari responden, sehingga semua motif layak diproduksi sebagai batik khas Gayo.Kata kunci: batik Gayo, Motif Ceplok Gayo, Motif Parang Gayo.ABSTRACTBatik industry began to develop in Gayo, but have not had a typical batik motif itself. Therefore, it is necessary to create batik motifs of Gayo, by taking inspiration from the carvings found in traditional houses commonly called kerawang Gayo. The purpose of this art is to create motifs those have a Gayo characteristic. The method used are the idea exploration, design, and motifs embodiment. In this activity has created six Gayo batik motifs, namely: (1 Motif Ceplok Gayo; (2 Motif Gayo Tegak; (3 Motif GayoLurus; (4 Motif Parang Gayo; (5 Motif Gayo Lembut; dan (6 Motif Geometris Gayo. The test results fondness of the motives to fifty respondents indicated that the Motif Ceplok Gayo most preferred by respondents ie 19%, while Motif Parang Gayo 18%, Motif Gayo Lembut 17%, Motif Geometris Gayo 17%, Motif Gayo

  19. Time Factor in the Theory of Anthropogenic Risk Prediction in Complex Dynamic Systems

    Science.gov (United States)

    Ostreikovsky, V. A.; Shevchenko, Ye N.; Yurkov, N. K.; Kochegarov, I. I.; Grishko, A. K.

    2018-01-01

    The article overviews the anthropogenic risk models that take into consideration the development of different factors in time that influence the complex system. Three classes of mathematical models have been analyzed for the use in assessing the anthropogenic risk of complex dynamic systems. These models take into consideration time factor in determining the prospect of safety change of critical systems. The originality of the study is in the analysis of five time postulates in the theory of anthropogenic risk and the safety of highly important objects. It has to be stressed that the given postulates are still rarely used in practical assessment of equipment service life of critically important systems. That is why, the results of study presented in the article can be used in safety engineering and analysis of critically important complex technical systems.

  20. Temporal motifs reveal collaboration patterns in online task-oriented networks

    Science.gov (United States)

    Xuan, Qi; Fang, Huiting; Fu, Chenbo; Filkov, Vladimir

    2015-05-01

    Real networks feature layers of interactions and complexity. In them, different types of nodes can interact with each other via a variety of events. Examples of this complexity are task-oriented social networks (TOSNs), where teams of people share tasks towards creating a quality artifact, such as academic research papers or software development in commercial or open source environments. Accomplishing those tasks involves both work, e.g., writing the papers or code, and communication, to discuss and coordinate. Taking into account the different types of activities and how they alternate over time can result in much more precise understanding of the TOSNs behaviors and outcomes. That calls for modeling techniques that can accommodate both node and link heterogeneity as well as temporal change. In this paper, we report on methodology for finding temporal motifs in TOSNs, limited to a system of two people and an artifact. We apply the methods to publicly available data of TOSNs from 31 Open Source Software projects. We find that these temporal motifs are enriched in the observed data. When applied to software development outcome, temporal motifs reveal a distinct dependency between collaboration and communication in the code writing process. Moreover, we show that models based on temporal motifs can be used to more precisely relate both individual developer centrality and team cohesion to programmer productivity than models based on aggregated TOSNs.

  1. Predictive Big Data Analytics: A Study of Parkinson's Disease Using Large, Complex, Heterogeneous, Incongruent, Multi-Source and Incomplete Observations.

    Science.gov (United States)

    Dinov, Ivo D; Heavner, Ben; Tang, Ming; Glusman, Gustavo; Chard, Kyle; Darcy, Mike; Madduri, Ravi; Pa, Judy; Spino, Cathie; Kesselman, Carl; Foster, Ian; Deutsch, Eric W; Price, Nathan D; Van Horn, John D; Ames, Joseph; Clark, Kristi; Hood, Leroy; Hampstead, Benjamin M; Dauer, William; Toga, Arthur W

    2016-01-01

    A unique archive of Big Data on Parkinson's Disease is collected, managed and disseminated by the Parkinson's Progression Markers Initiative (PPMI). The integration of such complex and heterogeneous Big Data from multiple sources offers unparalleled opportunities to study the early stages of prevalent neurodegenerative processes, track their progression and quickly identify the efficacies of alternative treatments. Many previous human and animal studies have examined the relationship of Parkinson's disease (PD) risk to trauma, genetics, environment, co-morbidities, or life style. The defining characteristics of Big Data-large size, incongruency, incompleteness, complexity, multiplicity of scales, and heterogeneity of information-generating sources-all pose challenges to the classical techniques for data management, processing, visualization and interpretation. We propose, implement, test and validate complementary model-based and model-free approaches for PD classification and prediction. To explore PD risk using Big Data methodology, we jointly processed complex PPMI imaging, genetics, clinical and demographic data. Collective representation of the multi-source data facilitates the aggregation and harmonization of complex data elements. This enables joint modeling of the complete data, leading to the development of Big Data analytics, predictive synthesis, and statistical validation. Using heterogeneous PPMI data, we developed a comprehensive protocol for end-to-end data characterization, manipulation, processing, cleaning, analysis and validation. Specifically, we (i) introduce methods for rebalancing imbalanced cohorts, (ii) utilize a wide spectrum of classification methods to generate consistent and powerful phenotypic predictions, and (iii) generate reproducible machine-learning based classification that enables the reporting of model parameters and diagnostic forecasting based on new data. We evaluated several complementary model-based predictive approaches

  2. Predictive Big Data Analytics: A Study of Parkinson's Disease Using Large, Complex, Heterogeneous, Incongruent, Multi-Source and Incomplete Observations.

    Directory of Open Access Journals (Sweden)

    Ivo D Dinov

    Full Text Available A unique archive of Big Data on Parkinson's Disease is collected, managed and disseminated by the Parkinson's Progression Markers Initiative (PPMI. The integration of such complex and heterogeneous Big Data from multiple sources offers unparalleled opportunities to study the early stages of prevalent neurodegenerative processes, track their progression and quickly identify the efficacies of alternative treatments. Many previous human and animal studies have examined the relationship of Parkinson's disease (PD risk to trauma, genetics, environment, co-morbidities, or life style. The defining characteristics of Big Data-large size, incongruency, incompleteness, complexity, multiplicity of scales, and heterogeneity of information-generating sources-all pose challenges to the classical techniques for data management, processing, visualization and interpretation. We propose, implement, test and validate complementary model-based and model-free approaches for PD classification and prediction. To explore PD risk using Big Data methodology, we jointly processed complex PPMI imaging, genetics, clinical and demographic data.Collective representation of the multi-source data facilitates the aggregation and harmonization of complex data elements. This enables joint modeling of the complete data, leading to the development of Big Data analytics, predictive synthesis, and statistical validation. Using heterogeneous PPMI data, we developed a comprehensive protocol for end-to-end data characterization, manipulation, processing, cleaning, analysis and validation. Specifically, we (i introduce methods for rebalancing imbalanced cohorts, (ii utilize a wide spectrum of classification methods to generate consistent and powerful phenotypic predictions, and (iii generate reproducible machine-learning based classification that enables the reporting of model parameters and diagnostic forecasting based on new data. We evaluated several complementary model

  3. Characterization of hydrogen bonding motifs in proteins: hydrogen elimination monitoring by ultraviolet photodissociation mass spectrometry.

    Science.gov (United States)

    Morrison, Lindsay J; Chai, Wenrui; Rosenberg, Jake A; Henkelman, Graeme; Brodbelt, Jennifer S

    2017-08-02

    Determination of structure and folding of certain classes of proteins remains intractable by conventional structural characterization strategies and has spurred the development of alternative methodologies. Mass spectrometry-based approaches have a unique capacity to differentiate protein heterogeneity due to the ability to discriminate populations, whether minor or major, featuring modifications or complexation with non-covalent ligands on the basis of m/z. Cleavage of the peptide backbone can be further utilized to obtain residue-specific structural information. Here, hydrogen elimination monitoring (HEM) upon ultraviolet photodissociation (UVPD) of proteins transferred to the gas phase via nativespray ionization is introduced as an innovative approach to deduce backbone hydrogen bonding patterns. Using well-characterized peptides and a series of proteins, prediction of the engagement of the amide carbonyl oxygen of the protein backbone in hydrogen bonding using UVPD-HEM is demonstrated to show significant agreement with the hydrogen-bonding motifs derived from molecular dynamics simulations and X-ray crystal structures.

  4. Accurate quantification of microRNA via single strand displacement reaction on DNA origami motif.

    Directory of Open Access Journals (Sweden)

    Jie Zhu

    Full Text Available DNA origami is an emerging technology that assembles hundreds of staple strands and one single-strand DNA into certain nanopattern. It has been widely used in various fields including detection of biological molecules such as DNA, RNA and proteins. MicroRNAs (miRNAs play important roles in post-transcriptional gene repression as well as many other biological processes such as cell growth and differentiation. Alterations of miRNAs' expression contribute to many human diseases. However, it is still a challenge to quantitatively detect miRNAs by origami technology. In this study, we developed a novel approach based on streptavidin and quantum dots binding complex (STV-QDs labeled single strand displacement reaction on DNA origami to quantitatively detect the concentration of miRNAs. We illustrated a linear relationship between the concentration of an exemplary miRNA as miRNA-133 and the STV-QDs hybridization efficiency; the results demonstrated that it is an accurate nano-scale miRNA quantifier motif. In addition, both symmetrical rectangular motif and asymmetrical China-map motif were tested. With significant linearity in both motifs, our experiments suggested that DNA Origami motif with arbitrary shape can be utilized in this method. Since this DNA origami-based method we developed owns the unique advantages of simple, time-and-material-saving, potentially multi-targets testing in one motif and relatively accurate for certain impurity samples as counted directly by atomic force microscopy rather than fluorescence signal detection, it may be widely used in quantification of miRNAs.

  5. Accurate Quantification of microRNA via Single Strand Displacement Reaction on DNA Origami Motif

    Science.gov (United States)

    Lou, Jingyu; Li, Weidong; Li, Sheng; Zhu, Hongxin; Yang, Lun; Zhang, Aiping; He, Lin; Li, Can

    2013-01-01

    DNA origami is an emerging technology that assembles hundreds of staple strands and one single-strand DNA into certain nanopattern. It has been widely used in various fields including detection of biological molecules such as DNA, RNA and proteins. MicroRNAs (miRNAs) play important roles in post-transcriptional gene repression as well as many other biological processes such as cell growth and differentiation. Alterations of miRNAs' expression contribute to many human diseases. However, it is still a challenge to quantitatively detect miRNAs by origami technology. In this study, we developed a novel approach based on streptavidin and quantum dots binding complex (STV-QDs) labeled single strand displacement reaction on DNA origami to quantitatively detect the concentration of miRNAs. We illustrated a linear relationship between the concentration of an exemplary miRNA as miRNA-133 and the STV-QDs hybridization efficiency; the results demonstrated that it is an accurate nano-scale miRNA quantifier motif. In addition, both symmetrical rectangular motif and asymmetrical China-map motif were tested. With significant linearity in both motifs, our experiments suggested that DNA Origami motif with arbitrary shape can be utilized in this method. Since this DNA origami-based method we developed owns the unique advantages of simple, time-and-material-saving, potentially multi-targets testing in one motif and relatively accurate for certain impurity samples as counted directly by atomic force microscopy rather than fluorescence signal detection, it may be widely used in quantification of miRNAs. PMID:23990889

  6. Accurate quantification of microRNA via single strand displacement reaction on DNA origami motif.

    Science.gov (United States)

    Zhu, Jie; Feng, Xiaolu; Lou, Jingyu; Li, Weidong; Li, Sheng; Zhu, Hongxin; Yang, Lun; Zhang, Aiping; He, Lin; Li, Can

    2013-01-01

    DNA origami is an emerging technology that assembles hundreds of staple strands and one single-strand DNA into certain nanopattern. It has been widely used in various fields including detection of biological molecules such as DNA, RNA and proteins. MicroRNAs (miRNAs) play important roles in post-transcriptional gene repression as well as many other biological processes such as cell growth and differentiation. Alterations of miRNAs' expression contribute to many human diseases. However, it is still a challenge to quantitatively detect miRNAs by origami technology. In this study, we developed a novel approach based on streptavidin and quantum dots binding complex (STV-QDs) labeled single strand displacement reaction on DNA origami to quantitatively detect the concentration of miRNAs. We illustrated a linear relationship between the concentration of an exemplary miRNA as miRNA-133 and the STV-QDs hybridization efficiency; the results demonstrated that it is an accurate nano-scale miRNA quantifier motif. In addition, both symmetrical rectangular motif and asymmetrical China-map motif were tested. With significant linearity in both motifs, our experiments suggested that DNA Origami motif with arbitrary shape can be utilized in this method. Since this DNA origami-based method we developed owns the unique advantages of simple, time-and-material-saving, potentially multi-targets testing in one motif and relatively accurate for certain impurity samples as counted directly by atomic force microscopy rather than fluorescence signal detection, it may be widely used in quantification of miRNAs.

  7. Predicting the stability constants of metal-ion complexes from first principles

    Czech Academy of Sciences Publication Activity Database

    Gutten, Ondrej; Rulíšek, Lubomír

    2013-01-01

    Roč. 52, č. 18 (2013), s. 10347-10355 ISSN 0020-1669 Institutional support: RVO:61388963 Keywords : stability constants * solvation energy * metal-ion complexation * theoretical calculations * DFT methods Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 4.794, year: 2013

  8. Objective measures of renal mass anatomic complexity predict rates of major complications following partial nephrectomy.

    Science.gov (United States)

    Simhan, Jay; Smaldone, Marc C; Tsai, Kevin J; Canter, Daniel J; Li, Tianyu; Kutikov, Alexander; Viterbo, Rosalia; Chen, David Y T; Greenberg, Richard E; Uzzo, Robert G

    2011-10-01

    The association between tumor complexity and postoperative complications after partial nephrectomy (PN) has not been well characterized. We evaluated whether increasing renal tumor complexity, quantitated by nephrometry score (NS), is associated with increased complication rates following PN using the Clavien-Dindo classification system (CCS). We queried our prospectively maintained kidney cancer database for patients undergoing PN from 2007 to 2010 for whom NS was available. All patients underwent PN. Tumors were categorized into low- (NS: 4-6), moderate- (NS: 7-9), and high-complexity (NS: 10-12) lesions. Complication rates within 30 d were graded (CCS: I-5), stratified as minor (CCS: I or 2) or major (CCS: 3-5), and compared between groups. A total of 390 patients (mean age: 58.0 ± 11.9 yr; 66.9% male) undergoing PN (44.6% open, 55.4% robotic) for low- (28%), moderate- (55.6%), and high-complexity (16.4%) tumors (mean tumor size: 3.74 ± 2.4 cm; median: 3.2 cm) from 2007 to 2010 were identified. Tumor size, estimated blood loss, and ischemia time all significantly differed (prenal tumors. Copyright © 2011 European Association of Urology. Published by Elsevier B.V. All rights reserved.

  9. Theoretical Predictions of Redox Potentials of Fischer-Type Chromium Anninocarbene Complexes

    Czech Academy of Sciences Publication Activity Database

    Kvapilová, Hana; Hoskovcová, Irena; Ludvík, Jiří; Záliš, Stanislav

    2014-01-01

    Roč. 33, č. 18 (2014), s. 4964-4972 ISSN 0276-7333 R&D Projects: GA MŠk LD14129; GA ČR GA13-04630S Institutional support: RVO:61388955 Keywords : standard hydrogen electrode * density functional theory * metal carbene complexes Subject RIV: CG - Electrochemistry Impact factor: 4.126, year: 2014

  10. Ab initio prediction of the rovibrational levels of the He-CO+ ionic complex

    Science.gov (United States)

    Mladenović, Mirjana; Lewerenz, Marius

    2013-08-01

    The intermolecular potential for the van der Waals complex of the carbon monoxide cation with helium is studied by means of the partially spin adapted coupled cluster RCCSD(T) method and the aug-cc-pVXZ family of basis sets. In the ground electronic state, correlated with the lowest electronic asymptote X 2Σ+ of the monomer CO+, the complex He(1 S)-CO+(2Σ+) has a nonlinear equilibrium structure with a Jacobi angle of about 46° and a binding energy of about 275 cm-1. For the complex He(1 S)-CO+(A 2Π) we find equilibrium Jacobi angles of 78° and 90° and electronic binding energies of about 160 cm-1 and 303 cm-1 for the A‧‧ and A‧ components, respectively, coalescing into the Π state at linearity. Two-dimensional intermolecular potential energy surfaces are constructed for the ground electronic state and used to compute rotation-vibration states up to J = 10 with the numerically exact discrete variable representation (DVR) technique. The He-CO+ complex is found to have 19 bound even-parity J = 0 states and 16 bound odd-parity J = 1 states and to exhibit strong angular-radial coupling and quasi-linear behaviour.

  11. Interdependence of clinical factors predicting cognition in children with tuberous sclerosis complex

    NARCIS (Netherlands)

    I.E. Overwater (Iris); Verhaar, B.J.H.; H.F. Lingsma (Hester); G.C.B. Bindels-de Heus (Karen); A.M.W. van den Ouweland (Ans); M.D. Nellist (Mark); L.W. ten Hoopen (Leontine); Y. Elgersma (Ype); H.A. Moll (Henriëtte); M.C.Y. de Wit (Marie Claire)

    2017-01-01

    textabstractCognitive development in patients with tuberous sclerosis complex is highly variable. Predictors in the infant years would be valuable to counsel parents and to support development. The aim of this study was to confirm factors that have been reported to be independently correlated with

  12. Current theoretical models fail to predict the topological complexity of the human genome

    Directory of Open Access Journals (Sweden)

    Javier eArsuaga

    2015-08-01

    Full Text Available Understanding the folding of the human genome is a key challenge of modern structural biology. The emergence of chromatin conformation capture assays ({it e.g.} Hi-C has revolutionized chromosome biology and provided new insights into the three dimensional structure of the genome. The experimental data are highly complex and need to be analyzed with quantitative tools. It has been argued that the data obtained from Hi-C assays are consistent with a fractal organization of the genome. A key characteristic textcolor{red}{of the fractal globule} is the lack of topological complexity (knotting or inter-linking. However, the absence of topological complexity contradicts results from polymer physics showing that the entanglement of long linear polymers in a confined volume increases rapidly with the length and with decreasing volume. textcolor{red}{{it In vivo} and {it in vitro} assays support this claim in some biological systems. We simulate knotted lattice polygons confined inside a sphere and demonstrate that their contact frequencies agree with the human Hi-C data.} We conclude that the topological complexity of the human genome cannot be inferred from current Hi-C data.

  13. Predictability of Harmonic Complexity Across 75 Years of Popular Music Hits

    DEFF Research Database (Denmark)

    Jensen, Karl Kristoffer; Hebert, David

    2015-01-01

    profiles, with strong predictability. From the 1940s is a sustained increase in JCC that nearly doubles, peaking in the 1980s, and gradually decreasing into the 21st century. Each decade was also deter- mined to correlate to a statistically distinctive harmonic profile. The find- ings presented here...

  14. PRODIGY : a web server for predicting the binding affinity of protein-protein complexes

    NARCIS (Netherlands)

    Xue, Li; Garcia Lopes Maia Rodrigues, João; Kastritis, Panagiotis L; Bonvin, Alexandre Mjj; Vangone, Anna

    2016-01-01

    Gaining insights into the structural determinants of protein-protein interactions holds the key for a deeper understanding of biological functions, diseases and development of therapeutics. An important aspect of this is the ability to accurately predict the binding strength for a given

  15. Predicting complex acute wound healing in patients from a wound expertise centre registry: a prognostic study

    NARCIS (Netherlands)

    Ubbink, Dirk T.; Lindeboom, Robert; Eskes, Anne M.; Brull, Huub; Legemate, Dink A.; Vermeulen, Hester

    2015-01-01

    It is important for caregivers and patients to know which wounds are at risk of prolonged wound healing to enable timely communication and treatment. Available prognostic models predict wound healing in chronic ulcers, but not in acute wounds, that is, originating after trauma or surgery. We

  16. Predicting complex acute wound healing in patients from a wound expertise centre registry : a prognostic study

    NARCIS (Netherlands)

    Ubbink, Dirk T; Lindeboom, Robert; Eskes, Anne M; Brull, Huub; Legemate, Dink A; Vermeulen, Hester

    2015-01-01

    It is important for caregivers and patients to know which wounds are at risk of prolonged wound healing to enable timely communication and treatment. Available prognostic models predict wound healing in chronic ulcers, but not in acute wounds, that is, originating after trauma or surgery. We

  17. Dynamic-landscape metapopulation models predict complex response of wildlife populations to climate and landscape change

    Science.gov (United States)

    Thomas W. Bonnot; Frank R. Thompson; Joshua J. Millspaugh

    2017-01-01

    The increasing need to predict how climate change will impact wildlife species has exposed limitations in how well current approaches model important biological processes at scales at which those processes interact with climate. We used a comprehensive approach that combined recent advances in landscape and population modeling into dynamic-landscape metapopulation...

  18. Simplified Method for Predicting a Functional Class of Proteins in Transcription Factor Complexes

    KAUST Repository

    Piatek, Marek J.; Schramm, Michael C.; Burra, Dharani Dhar; BinShbreen, Abdulaziz; Jankovic, Boris R.; Chowdhary, Rajesh; Archer, John A.C.; Bajic, Vladimir B.

    2013-01-01

    initiation. Such information is not fully available, since not all proteins that act as TFs or TcoFs are yet annotated as such, due to generally partial functional annotation of proteins. In this study we have developed a method to predict, using only

  19. Predicting Patterns of Grammatical Complexity across Language Exam Task Types and Proficiency Levels

    Science.gov (United States)

    Biber, Douglas; Gray, Bethany; Staples, Shelley

    2016-01-01

    In the present article, we explore the extent to which previous research on register variation can be used to predict spoken/written task-type variation as well as differences across score levels in the context of a major standardized language exam (TOEFL iBT). Specifically, we carry out two sets of linguistic analyses based on a large corpus of…

  20. Structural motifs of pre-nucleation clusters.

    Science.gov (United States)

    Zhang, Y; Türkmen, I R; Wassermann, B; Erko, A; Rühl, E

    2013-10-07

    Structural motifs of pre-nucleation clusters prepared in single, optically levitated supersaturated aqueous aerosol microparticles containing CaBr2 as a model system are reported. Cluster formation is identified by means of X-ray absorption in the Br K-edge regime. The salt concentration beyond the saturation point is varied by controlling the humidity in the ambient atmosphere surrounding the 15-30 μm microdroplets. This leads to the formation of metastable supersaturated liquid particles. Distinct spectral shifts in near-edge spectra as a function of salt concentration are observed, in which the energy position of the Br K-edge is red-shifted by up to 7.1 ± 0.4 eV if the dilute solution is compared to the solid. The K-edge positions of supersaturated solutions are found between these limits. The changes in electronic structure are rationalized in terms of the formation of pre-nucleation clusters. This assumption is verified by spectral simulations using first-principle density functional theory and molecular dynamics calculations, in which structural motifs are considered, explaining the experimental results. These consist of solvated CaBr2 moieties, rather than building blocks forming calcium bromide hexahydrates, the crystal system that is formed by drying aqueous CaBr2 solutions.

  1. POWRS: position-sensitive motif discovery.

    Directory of Open Access Journals (Sweden)

    Ian W Davis

    Full Text Available Transcription factors and the short, often degenerate DNA sequences they recognize are central regulators of gene expression, but their regulatory code is challenging to dissect experimentally. Thus, computational approaches have long been used to identify putative regulatory elements from the patterns in promoter sequences. Here we present a new algorithm "POWRS" (POsition-sensitive WoRd Set for identifying regulatory sequence motifs, specifically developed to address two common shortcomings of existing algorithms. First, POWRS uses the position-specific enrichment of regulatory elements near transcription start sites to significantly increase sensitivity, while providing new information about the preferred localization of those elements. Second, POWRS forgoes position weight matrices for a discrete motif representation that appears more resistant to over-generalization. We apply this algorithm to discover sequences related to constitutive, high-level gene expression in the model plant Arabidopsis thaliana, and then experimentally validate the importance of those elements by systematically mutating two endogenous promoters and measuring the effect on gene expression levels. This provides a foundation for future efforts to rationally engineer gene expression in plants, a problem of great importance in developing biotech crop varieties.BSD-licensed Python code at http://grassrootsbio.com/papers/powrs/.

  2. Parole, Sintagmatik, dan Paradigmatik Motif Batik Mega Mendung

    Directory of Open Access Journals (Sweden)

    Rudi - Nababan

    2012-04-01

    Full Text Available ABSTRACT   Discussing traditional batik is related a lot to the organization system of fine arts element ac- companying it, either the pattern of the motif or the technique of the making. In this case, the motif of Mega Mendung Cirebon certainly has patterns and rules which are traditionally different from the other motifs in other areas. Through  semiotics analysis especially with Saussure and Pierce concept, it can be traced that batik with Cirebon motif, in this case Mega Mendung motif, has parole and langue system, as unique fine arts language in batik, and structure of visual syntagmatic and paradigmatic. In the context of batik motif as fine arts language, it is surely related to sign system as symbol and icon.       Keywords: visual semiotic, Cirebon’s batik.

  3. Communication: Theoretical prediction of free-energy landscapes for complex self-assembly

    Energy Technology Data Exchange (ETDEWEB)

    Jacobs, William M.; Reinhardt, Aleks; Frenkel, Daan [Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW (United Kingdom)

    2015-01-14

    We present a technique for calculating free-energy profiles for the nucleation of multicomponent structures that contain as many species as building blocks. We find that a key factor is the topology of the graph describing the connectivity of the target assembly. By considering the designed interactions separately from weaker, incidental interactions, our approach yields predictions for the equilibrium yield and nucleation barriers. These predictions are in good agreement with corresponding Monte Carlo simulations. We show that a few fundamental properties of the connectivity graph determine the most prominent features of the assembly thermodynamics. Surprisingly, we find that polydispersity in the strengths of the designed interactions stabilizes intermediate structures and can be used to sculpt the free-energy landscape for self-assembly. Finally, we demonstrate that weak incidental interactions can preclude assembly at equilibrium due to the combinatorial possibilities for incorrect association.

  4. ECONOMIC AND MATHEMATICAL MODEL OF PREDICTION OF DEVIATION IN MOSCOW SUBURBAN RAILWAY COMPLEX

    Directory of Open Access Journals (Sweden)

    Dmitry I. Valdman

    2013-01-01

    Full Text Available The article deals with the theoretical aspects of mathematical modeling and forecasting. Additionally, it describes a mathematical model for forecasting the number of incidents, depending on the number of different types of planned works with one and the same subject in service facilities, validation of the model via substituting of the data and comparing the predicted values calculated by the model and the actual values for the same periods.

  5. Simple Mindreading Abilities Predict Complex Theory of Mind: Developmental Delay in Autism Spectrum Disorders

    Science.gov (United States)

    Pino, Maria Chiara; Mazza, Monica; Mariano, Melania; Peretti, Sara; Dimitriou, Dagmara; Masedu, Francesco; Valenti, Marco; Franco, Fabia

    2017-01-01

    Theory of mind (ToM) is impaired in individuals with autism spectrum disorders (ASD). The aims of this study were to: (i) examine the developmental trajectories of ToM abilities in two different mentalizing tasks in children with ASD compared to TD children; and (ii) to assess if a ToM simple test known as eyes-test could predict performance on…

  6. Prediction and measurement of complexation of radionuclide mixtures by α-isosaccharinic, gluconic and picolinic acids

    International Nuclear Information System (INIS)

    Nick Evans; Peter Warwick; Monica Felipe-Sotelo

    2012-01-01

    The purpose of this study was to investigate the effects of competition between cobalt, europium and strontium for isosaccharinate, gluconate and picolinate. Systems where results indicated that competitive effects were significant have been identified. Thermodynamic calculations were performed for each system for comparison with the experimental results. Some exceptions may be due to precipitation of some species, or presence of species not in databases, or formation of mixed-metal complexes, or sorption to the solid phase(s). In some of the experiments, the complexity of the systems studied caused difficulty in identifying consistent trends. By concentrating on the results for simpler systems (i.e. for solubilities in the presence and absence of organic complexants and with just one competing metal ion), the evidence for competition effects has been investigated. Evidence for solubility enhancement due to organic ligands was apparent in the data for the systems Co with gluconate and Eu with isosaccharinate and gluconate. Of these above cases, the systems in which the effects of the competing ion are consistent with competition were limited to the cases of Eu with isosaccharinate and Sr as the competing ion, and Eu with gluconate and either Co or Sr as the competing ion. (author)

  7. Predicting complex syntactic structure in real time: Processing of negative sentences in Russian.

    Science.gov (United States)

    Kazanina, Nina

    2017-11-01

    In Russian negative sentences the verb's direct object may appear either in the accusative case, which is licensed by the verb (as is common cross-linguistically), or in the genitive case, which is licensed by the negation (Russian-specific "genitive-of-negation" phenomenon). Such sentences were used to investigate whether case marking is employed for anticipating syntactic structure, and whether lexical heads other than the verb can be predicted on the basis of a case-marked noun phrase. Experiment 1, a completion task, confirmed that genitive-of-negation is part of Russian speakers' active grammatical repertoire. In Experiments 2 and 3, the genitive/accusative case manipulation on the preverbal object led to shorter reading times at the negation and verb in the genitive versus accusative condition. Furthermore, Experiment 3 manipulated linear order of the direct object and the negated verb in order to distinguish whether the abovementioned facilitatory effect was predictive or integrative in nature, and concluded that the parser actively predicts a verb and (otherwise optional) negation on the basis of a preceding genitive-marked object. Similarly to a head-final language, case-marking information on preverbal noun phrases (NPs) is used by the parser to enable incremental structure building in a free-word-order language such as Russian.

  8. The legal and ethical concerns that arise from using complex predictive analytics in health care.

    Science.gov (United States)

    Cohen, I Glenn; Amarasingham, Ruben; Shah, Anand; Xie, Bin; Lo, Bernard

    2014-07-01

    Predictive analytics, or the use of electronic algorithms to forecast future events in real time, makes it possible to harness the power of big data to improve the health of patients and lower the cost of health care. However, this opportunity raises policy, ethical, and legal challenges. In this article we analyze the major challenges to implementing predictive analytics in health care settings and make broad recommendations for overcoming challenges raised in the four phases of the life cycle of a predictive analytics model: acquiring data to build the model, building and validating it, testing it in real-world settings, and disseminating and using it more broadly. For instance, we recommend that model developers implement governance structures that include patients and other stakeholders starting in the earliest phases of development. In addition, developers should be allowed to use already collected patient data without explicit consent, provided that they comply with federal regulations regarding research on human subjects and the privacy of health information. Project HOPE—The People-to-People Health Foundation, Inc.

  9. First-principles structures for the close-packed and the 7/2 motif of collagen

    DEFF Research Database (Denmark)

    Jalkanen, Karl J.; Olsen, Kasper; Knapp-Mohammady, Michaela

    2012-01-01

    The newly proposed close-packed motif for collagen and the more established 7/2 structure are investigated and compared. First-principles semi-empirical wave function theory and Kohn-Sham density functional theory are applied in the study of these relatively large and complex structures. The stru......The newly proposed close-packed motif for collagen and the more established 7/2 structure are investigated and compared. First-principles semi-empirical wave function theory and Kohn-Sham density functional theory are applied in the study of these relatively large and complex structures...

  10. Computational prediction of binding affinity for CYP1A2-ligand complexes using empirical free energy calculations

    DEFF Research Database (Denmark)

    Poongavanam, Vasanthanathan; Olsen, Lars; Jørgensen, Flemming Steen

    2010-01-01

    , and methods based on statistical mechanics. In the present investigation, we started from an LIE model to predict the binding free energy of structurally diverse compounds of cytochrome P450 1A2 ligands, one of the important human metabolizing isoforms of the cytochrome P450 family. The data set includes both...... substrates and inhibitors. It appears that the electrostatic contribution to the binding free energy becomes negligible in this particular protein and a simple empirical model was derived, based on a training set of eight compounds. The root mean square error for the training set was 3.7 kJ/mol. Subsequent......Predicting binding affinities for receptor-ligand complexes is still one of the challenging processes in computational structure-based ligand design. Many computational methods have been developed to achieve this goal, such as docking and scoring methods, the linear interaction energy (LIE) method...

  11. Prediction of homoprotein and heteroprotein complexes by protein docking and template-based modeling: A CASP-CAPRI experiment

    KAUST Repository

    Lensink, Marc F.

    2016-04-28

    We present the results for CAPRI Round 30, the first joint CASP-CAPRI experiment, which brought together experts from the protein structure prediction and protein-protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014. The targets included mostly homodimers, a few homotetramers, and two heterodimers, and comprised protein chains that could readily be modeled using templates from the Protein Data Bank. On average 24 CAPRI groups and 7 CASP groups submitted docking predictions for each target, and 12 CAPRI groups per target participated in the CAPRI scoring experiment. In total more than 9500 models were assessed against the 3D structures of the corresponding target complexes. Results show that the prediction of homodimer assemblies by homology modeling techniques and docking calculations is quite successful for targets featuring large enough subunit interfaces to represent stable associations. Targets with ambiguous or inaccurate oligomeric state assignments, often featuring crystal contact-sized interfaces, represented a confounding factor. For those, a much poorer prediction performance was achieved, while nonetheless often providing helpful clues on the correct oligomeric state of the protein. The prediction performance was very poor for genuine tetrameric targets, where the inaccuracy of the homology-built subunit models and the smaller pair-wise interfaces severely limited the ability to derive the correct assembly mode. Our analysis also shows that docking procedures tend to perform better than standard homology modeling techniques and that highly accurate models of the protein components are not always required to identify their association modes with acceptable accuracy. © 2016 Wiley Periodicals, Inc.

  12. Prediction of homoprotein and heteroprotein complexes by protein docking and template-based modeling: A CASP-CAPRI experiment

    KAUST Repository

    Lensink, Marc F.; Velankar, Sameer; Kryshtafovych, Andriy; Huang, Shen-You; Schneidman-Duhovny, Dina; Sali, Andrej; Segura, Joan; Fernandez-Fuentes, Narcis; Viswanath, Shruthi; Elber, Ron; Grudinin, Sergei; Popov, Petr; Neveu, Emilie; Lee, Hasup; Baek, Minkyung; Park, Sangwoo; Heo, Lim; Rie Lee, Gyu; Seok, Chaok; Qin, Sanbo; Zhou, Huan-Xiang; Ritchie, David W.; Maigret, Bernard; Devignes, Marie-Dominique; Ghoorah, Anisah; Torchala, Mieczyslaw; Chaleil, Raphaë l A.G.; Bates, Paul A.; Ben-Zeev, Efrat; Eisenstein, Miriam; Negi, Surendra S.; Weng, Zhiping; Vreven, Thom; Pierce, Brian G.; Borrman, Tyler M.; Yu, Jinchao; Ochsenbein, Franç oise; Guerois, Raphaë l; Vangone, Anna; Rodrigues, Joã o P.G.L.M.; van Zundert, Gydo; Nellen, Mehdi; Xue, Li; Karaca, Ezgi; Melquiond, Adrien S.J.; Visscher, Koen; Kastritis, Panagiotis L.; Bonvin, Alexandre M.J.J.; Xu, Xianjin; Qiu, Liming; Yan, Chengfei; Li, Jilong; Ma, Zhiwei; Cheng, Jianlin; Zou, Xiaoqin; Shen, Yang; Peterson, Lenna X.; Kim, Hyung-Rae; Roy, Amit; Han, Xusi; Esquivel-Rodriguez, Juan; Kihara, Daisuke; Yu, Xiaofeng; Bruce, Neil J.; Fuller, Jonathan C.; Wade, Rebecca C.; Anishchenko, Ivan; Kundrotas, Petras J.; Vakser, Ilya A.; Imai, Kenichiro; Yamada, Kazunori; Oda, Toshiyuki; Nakamura, Tsukasa; Tomii, Kentaro; Pallara, Chiara; Romero-Durana, Miguel; Jimé nez-Garcí a, Brian; Moal, Iain H.; Fé rnandez-Recio, Juan; Joung, Jong Young; Kim, Jong Yun; Joo, Keehyoung; Lee, Jooyoung; Kozakov, Dima; Vajda, Sandor; Mottarella, Scott; Hall, David R.; Beglov, Dmitri; Mamonov, Artem; Xia, Bing; Bohnuud, Tanggis; Del Carpio, Carlos A.; Ichiishi, Eichiro; Marze, Nicholas; Kuroda, Daisuke; Roy Burman, Shourya S.; Gray, Jeffrey J.; Chermak, Edrisse; Cavallo, Luigi; Oliva, Romina; Tovchigrechko, Andrey; Wodak, Shoshana J.

    2016-01-01

    We present the results for CAPRI Round 30, the first joint CASP-CAPRI experiment, which brought together experts from the protein structure prediction and protein-protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014. The targets included mostly homodimers, a few homotetramers, and two heterodimers, and comprised protein chains that could readily be modeled using templates from the Protein Data Bank. On average 24 CAPRI groups and 7 CASP groups submitted docking predictions for each target, and 12 CAPRI groups per target participated in the CAPRI scoring experiment. In total more than 9500 models were assessed against the 3D structures of the corresponding target complexes. Results show that the prediction of homodimer assemblies by homology modeling techniques and docking calculations is quite successful for targets featuring large enough subunit interfaces to represent stable associations. Targets with ambiguous or inaccurate oligomeric state assignments, often featuring crystal contact-sized interfaces, represented a confounding factor. For those, a much poorer prediction performance was achieved, while nonetheless often providing helpful clues on the correct oligomeric state of the protein. The prediction performance was very poor for genuine tetrameric targets, where the inaccuracy of the homology-built subunit models and the smaller pair-wise interfaces severely limited the ability to derive the correct assembly mode. Our analysis also shows that docking procedures tend to perform better than standard homology modeling techniques and that highly accurate models of the protein components are not always required to identify their association modes with acceptable accuracy. © 2016 Wiley Periodicals, Inc.

  13. Predicting complex traits using a diffusion kernel on genetic markers with an application to dairy cattle and wheat data

    Science.gov (United States)

    2013-01-01

    Background Arguably, genotypes and phenotypes may be linked in functional forms that are not well addressed by the linear additive models that are standard in quantitative genetics. Therefore, developing statistical learning models for predicting phenotypic values from all available molecular information that are capable of capturing complex genetic network architectures is of great importance. Bayesian kernel ridge regression is a non-parametric prediction model proposed for this purpose. Its essence is to create a spatial distance-based relationship matrix called a kernel. Although the set of all single nucleotide polymorphism genotype configurations on which a model is built is finite, past research has mainly used a Gaussian kernel. Results We sought to investigate the performance of a diffusion kernel, which was specifically developed to model discrete marker inputs, using Holstein cattle and wheat data. This kernel can be viewed as a discretization of the Gaussian kernel. The predictive ability of the diffusion kernel was similar to that of non-spatial distance-based additive genomic relationship kernels in the Holstein data, but outperformed the latter in the wheat data. However, the difference in performance between the diffusion and Gaussian kernels was negligible. Conclusions It is concluded that the ability of a diffusion kernel to capture the total genetic variance is not better than that of a Gaussian kernel, at least for these data. Although the diffusion kernel as a choice of basis function may have potential for use in whole-genome prediction, our results imply that embedding genetic markers into a non-Euclidean metric space has very small impact on prediction. Our results suggest that use of the black box Gaussian kernel is justified, given its connection to the diffusion kernel and its similar predictive performance. PMID:23763755

  14. Numerical Prediction of Elastic Springback in An Automotive Complex Structural Part

    International Nuclear Information System (INIS)

    Fratini, Livan; Ingarao, Giuseppe; Micari, Fabrizio

    2007-01-01

    The occurrence of elastic springback phenomena in sheet metal processing operations determines a relevant issue in the automotive industry. The routing and production of 3D complex parts for automotive applications is characterized by springback phenomena affecting the final geometry of the components both after the stamping operations and the trimming ones. In the present paper the full routing of a automotive structural part is considered and the springback phenomena occurring after forming and trimming are investigated through FE analyses utilizing an explicit implicit approach. In particular a sensitivity analysis on process parameter influencing springback occurrence is developed: blank holder force, draw bead penetration and blank shape

  15. Hydration energies and specific influence of oxo complexes and high coordination numbers on the predicted chemistry of superheavy elements

    International Nuclear Information System (INIS)

    Jorgensen, C.K.; Penneman, R.A.

    1975-01-01

    On the basis of an analysis of the known ionization energies of gaseous ions and aqua ions of the 3d, 4f, and 6d transition groups and the radius effects, the chemistry of the superheavy elements is predicted. The formation of aqua ion and oxo complexes in the elements with Z below 121 is considered. It is probable that the series from 123 to 140 constitute a close analogy to the lanthanides with Th-like chemistry. Above Z = 140 the elements will probably displace a transition group behavior. A brief comment is made on the analytical aspects to be expected. (U.S.)

  16. A Conceptual Framework for Predicting Error in Complex Human-Machine Environments

    Science.gov (United States)

    Freed, Michael; Remington, Roger; Null, Cynthia H. (Technical Monitor)

    1998-01-01

    We present a Goals, Operators, Methods, and Selection Rules-Model Human Processor (GOMS-MHP) style model-based approach to the problem of predicting human habit capture errors. Habit captures occur when the model fails to allocate limited cognitive resources to retrieve task-relevant information from memory. Lacking the unretrieved information, decision mechanisms act in accordance with implicit default assumptions, resulting in error when relied upon assumptions prove incorrect. The model helps interface designers identify situations in which such failures are especially likely.

  17. Cost Prediction via Quantitative Analysis of Complexity in U.S. Navy Shipbuilding

    Science.gov (United States)

    2014-06-01

    determined that a suitable case study needed to meet several requirements: • Class longevity. A long history of actual (vice predicted, parametric...AEGIS program has a long history dating back to December 24th, 1969 when RCA was awarded the first R&D contract to develop the AEGIS program as shown in...this effort stem from items purchased at retail stores such as Target® or Ikea ® where the end consumer constructs the final product at home via a

  18. Prediction of Antimicrobial Peptides Based on Sequence Alignment and Support Vector Machine-Pairwise Algorithm Utilizing LZ-Complexity

    Directory of Open Access Journals (Sweden)

    Xin Yi Ng

    2015-01-01

    Full Text Available This study concerns an attempt to establish a new method for predicting antimicrobial peptides (AMPs which are important to the immune system. Recently, researchers are interested in designing alternative drugs based on AMPs because they have found that a large number of bacterial strains have become resistant to available antibiotics. However, researchers have encountered obstacles in the AMPs designing process as experiments to extract AMPs from protein sequences are costly and require a long set-up time. Therefore, a computational tool for AMPs prediction is needed to resolve this problem. In this study, an integrated algorithm is newly introduced to predict AMPs by integrating sequence alignment and support vector machine- (SVM- LZ complexity pairwise algorithm. It was observed that, when all sequences in the training set are used, the sensitivity of the proposed algorithm is 95.28% in jackknife test and 87.59% in independent test, while the sensitivity obtained for jackknife test and independent test is 88.74% and 78.70%, respectively, when only the sequences that has less than 70% similarity are used. Applying the proposed algorithm may allow researchers to effectively predict AMPs from unknown protein peptide sequences with higher sensitivity.

  19. Evaluation of Different Topographic Corrections for Landsat TM Data by Prediction of Foliage Projective Cover (FPC in Topographically Complex Landscapes

    Directory of Open Access Journals (Sweden)

    Sisira Ediriweera

    2013-12-01

    Full Text Available The reflected radiance in topographically complex areas is severely affected by variations in topography; thus, topographic correction is considered a necessary pre-processing step when retrieving biophysical variables from these images. We assessed the performance of five topographic corrections: (i C correction (C, (ii Minnaert, (iii Sun Canopy Sensor (SCS, (iv SCS + C and (v the Processing Scheme for Standardised Surface Reflectance (PSSSR on the Landsat-5 Thematic Mapper (TM reflectance in the context of prediction of Foliage Projective Cover (FPC in hilly landscapes in north-eastern Australia. The performance of topographic corrections on the TM reflectance was assessed by (i visual comparison and (ii statistically comparing TM predicted FPC with ground measured FPC and LiDAR (Light Detection and Ranging-derived FPC estimates. In the majority of cases, the PSSSR method performed best in terms of eliminating topographic effects, providing the best relationship and lowest residual error when comparing ground measured FPC and LiDAR FPC with TM predicted FPC. The Minnaert, C and SCS + C showed the poorest performance. Finally, the use of TM surface reflectance, which includes atmospheric correction and broad Bidirectional Reflectance Distribution Function (BRDF effects, seemed to account for most topographic variation when predicting biophysical variables, such as FPC.

  20. Application of Semiempirical Methods to Transition Metal Complexes: Fast Results but Hard-to-Predict Accuracy.

    KAUST Repository

    Minenkov, Yury

    2018-05-22

    A series of semiempirical PM6* and PM7 methods has been tested in reproducing of relative conformational energies of 27 realistic-size complexes of 16 different transition metals (TMs). An analysis of relative energies derived from single-point energy evaluations on density functional theory (DFT) optimized conformers revealed pronounced deviations between semiempirical and DFT methods indicating fundamental difference in potential energy surfaces (PES). To identify the origin of the deviation, we compared fully optimized PM7 and respective DFT conformers. For many complexes, differences in PM7 and DFT conformational energies have been confirmed often manifesting themselves in false coordination of some atoms (H, O) to TMs and chemical transformations/distortion of coordination center geometry in PM7 structures. Despite geometry optimization with fixed coordination center geometry leads to some improvements in conformational energies, the resulting accuracy is still too low to recommend explored semiempirical methods for out-of-the-box conformational search/sampling: careful testing is always needed.

  1. The complexity and ambivalence of immigration attitudes: ambivalent stereotypes predict conflicting attitudes toward immigration policies.

    Science.gov (United States)

    Reyna, Christine; Dobria, Ovidiu; Wetherell, Geoffrey

    2013-07-01

    Americans' conflicted attitudes toward immigrants and immigration has stymied immigration reform for decades. In this article, we explore the nuanced nature of stereotypes about immigrants and how they relate to ambivalent attitudes toward immigrant groups and the disparate array of immigration policies that affect them. Using item response theory and multiple regression analysis, we identified and related stereotypes of different immigrant groups to group-based and policy attitudes. Results demonstrate that ambivalent stereotypes mapped onto ambivalent group-based and immigration policy attitudes. Specifically, stereotypes that portray groups in positive or sympathetic ways predicted positive attitudes toward the group and more supportive attitudes toward policies that facilitate their immigration to the United States. Conversely, negative qualities predicted negative attitudes toward the same group and support for policies that prevent the group from immigrating. Results are discussed in light of current theory related to stereotype content, complementarity of stereotypes, and broader implications for immigration attitudes and policy. PsycINFO Database Record (c) 2013 APA, all rights reserved.

  2. Using Deep Learning to Predict Complex Systems: A Case Study in Wind Farm Generation

    Directory of Open Access Journals (Sweden)

    J. M. Torres

    2018-01-01

    Full Text Available Making every component of an electrical system work in unison is being made more challenging by the increasing number of renewable energies used, the electrical output of which is difficult to determine beforehand. In Spain, the daily electricity market opens with a 12-hour lead time, where the supply and demand expected for the following 24 hours are presented. When estimating the generation, energy sources like nuclear are highly stable, while peaking power plants can be run as necessary. Renewable energies, however, which should eventually replace peakers insofar as possible, are reliant on meteorological conditions. In this paper we propose using different deep-learning techniques and architectures to solve the problem of predicting wind generation in order to participate in the daily market, by making predictions 12 and 36 hours in advance. We develop and compare various estimators based on feedforward, convolutional, and recurrent neural networks. These estimators were trained and validated with data from a wind farm located on the island of Tenerife. We show that the best candidates for each type are more precise than the reference estimator and the polynomial regression currently used at the wind farm. We also conduct a sensitivity analysis to determine which estimator type is most robust to perturbations. An analysis of our findings shows that the most accurate and robust estimators are those based on feedforward neural networks with a SELU activation function and convolutional neural networks.

  3. A Common Structural Motif in the Binding of Virulence Factors to Bacterial Secretion Chaperones

    International Nuclear Information System (INIS)

    Lilic, M.; Vujanac, M.; Stebbins, C.

    2006-01-01

    Salmonella invasion protein A (SipA) is translocated into host cells by a type III secretion system (T3SS) and comprises two regions: one domain binds its cognate type III secretion chaperone, InvB, in the bacterium to facilitate translocation, while a second domain functions in the host cell, contributing to bacterial uptake by polymerizing actin. We present here the crystal structures of the SipA chaperone binding domain (CBD) alone and in complex with InvB. The SipA CBD is found to consist of a nonglobular polypeptide as well as a large globular domain, both of which are necessary for binding to InvB. We also identify a structural motif that may direct virulence factors to their cognate chaperones in a diverse range of pathogenic bacteria. Disruption of this structural motif leads to a destabilization of several chaperone-substrate complexes from different species, as well as an impairment of secretion in Salmonella

  4. Rekayasa Pengembangan Desain Motif Batik Khas Melayu

    Directory of Open Access Journals (Sweden)

    Eustasia Sri Murwati

    2016-04-01

    Full Text Available ABSTRAKPengembangan desain batik melalui rancang bangun perekayasaan desain menurut ragam hias Melayu meliputi pengembangan motif dan proses, termasuk pemilihan komposisi warna. Proses yang sering dilakukan yaitu proses celup, penghilangan lilin dan celup warna tumpangan atau proses colet, celup, penghilangan lilin atau celup kemudian penghilangan lilin yang disebut Batik Kelengan. Setiap pulau di Indonesia mempunyai ciri khas budaya dan kesenian yang dikenal dengan corak/ragam hias khas daerah, juga ornamen yang diminati oleh masyarakat dari daerah tersebut atau dari daerah lain. Kondisi demikian mendorong pertumbuhan industri kerajinan yang memanfaatkan unsur–unsur seni. Adapun motif yang diperoleh adalah: Ayam Berlaga, Bungo Matahari, Kuntum Bersanding, Lancang Kuning, Encong Kerinci, Durian Pecah, Bungo Bintang, Bungo Pauh Kecil, Riang-riang, Bungo Nagaro. Pengembangan desain tersebut dipilih 3 produk terbaik yang dinilai oleh 5 penilai yang ahli di bidang desain batik, yaitu motif Durian Pecah, Ayam Berlaga, dan Bungo Matahari. Rancang bangun diversifikasi desain dengan memanfaatkan unsur–unsur seni dan ketrampilan etnis Melayu yaitu pemilihan ragam hias dan motif batik Melayu untuk diterapkan ke bahan sandang dengan komposisi warna yang menarik, sehingga produk memenuhi selera konsumen. Memperbaiki keberagaman batik dengan meningkatkan desain produk antara lain menuangkan ragam hias Melayu ke dalam proses batik yang menggunakan berbagai macam warna sehingga komposisi warna memadai. Diperoleh hasil produk batik dengan ragam hias Melayu yang berkualitas dan komposisi warna yang sesuai dengan karakter ragam hias Melayu. Rancang bangun desain produk untuk mendapatkan formulasi desain serta kelayakan prosesnya dengan penekanan pada teknologi akrab lingkungan dilaksanakan dengan alternatif pendekatan yaitu penciptaan desain bentuk baru.Kata kunci: desain, batik, rancang bangun, ragam hias, MelayuABSTRACTDevelopment of batik design through

  5. Transnationalism as a motif in family stories.

    Science.gov (United States)

    Stone, Elizabeth; Gomez, Erica; Hotzoglou, Despina; Lipnitsky, Jane Y

    2005-12-01

    Family stories have long been recognized as a vehicle for assessing components of a family's emotional and social life, including the degree to which an immigrant family has been willing to assimilate. Transnationalism, defined as living in one or more cultures and maintaining connections to both, is now increasingly common. A qualitative study of family stories in the family of those who appear completely "American" suggests that an affiliation with one's home country is nevertheless detectable in the stories via motifs such as (1) positively connotated home remedies, (2) continuing denigration of home country "enemies," (3) extensive knowledge of the home country history and politics, (4) praise of endogamy and negative assessment of exogamy, (5) superiority of home country to America, and (6) beauty of home country. Furthermore, an awareness of which model--assimilationist or transnational--governs a family's experience may help clarify a clinician's understanding of a family's strengths, vulnerabilities, and mode of framing their cultural experiences.

  6. Promzea: a pipeline for discovery of co-regulatory motifs in maize and other plant species and its application to the anthocyanin and phlobaphene biosynthetic pathways and the Maize Development Atlas.

    Science.gov (United States)

    Liseron-Monfils, Christophe; Lewis, Tim; Ashlock, Daniel; McNicholas, Paul D; Fauteux, François; Strömvik, Martina; Raizada, Manish N

    2013-03-15

    The discovery of genetic networks and cis-acting DNA motifs underlying their regulation is a major objective of transcriptome studies. The recent release of the maize genome (Zea mays L.) has facilitated in silico searches for regulatory motifs. Several algorithms exist to predict cis-acting elements, but none have been adapted for maize. A benchmark data set was used to evaluate the accuracy of three motif discovery programs: BioProspector, Weeder and MEME. Analysis showed that each motif discovery tool had limited accuracy and appeared to retrieve a distinct set of motifs. Therefore, using the benchmark, statistical filters were optimized to reduce the false discovery ratio, and then remaining motifs from all programs were combined to improve motif prediction. These principles were integrated into a user-friendly pipeline for motif discovery in maize called Promzea, available at http://www.promzea.org and on the Discovery Environment of the iPlant Collaborative website. Promzea was subsequently expanded to include rice and Arabidopsis. Within Promzea, a user enters cDNA sequences or gene IDs; corresponding upstream sequences are retrieved from the maize genome. Predicted motifs are filtered, combined and ranked. Promzea searches the chosen plant genome for genes containing each candidate motif, providing the user with the gene list and corresponding gene annotations. Promzea was validated in silico using a benchmark data set: the Promzea pipeline showed a 22% increase in nucleotide sensitivity compared to the best standalone program tool, Weeder, with equivalent nucleotide specificity. Promzea was also validated by its ability to retrieve the experimentally defined binding sites of transcription factors that regulate the maize anthocyanin and phlobaphene biosynthetic pathways. Promzea predicted additional promoter motifs, and genome-wide motif searches by Promzea identified 127 non-anthocyanin/phlobaphene genes that each contained all five predicted promoter

  7. Motif decomposition of the phosphotyrosine proteome reveals a new N-terminal binding motif for SHIP2

    DEFF Research Database (Denmark)

    Miller, Martin Lee; Hanke, S.; Hinsby, A. M.

    2008-01-01

    set of 481 unique phosphotyrosine (Tyr(P)) peptides by sequence similarity to known ligands of the Src homology 2 (SH2) and the phosphotyrosine binding (PTB) domains. From 20 clusters we extracted 16 known and four new interaction motifs. Using quantitative mass spectrometry we pulled down Tyr......(P)-specific binding partners for peptides corresponding to the extracted motifs. We confirmed numerous previously known interaction motifs and found 15 new interactions mediated by phosphosites not previously known to bind SH2 or PTB. Remarkably, a novel hydrophobic N-terminal motif ((L/V/I)(L/V/I)pY) was identified...

  8. Predicting functional impairment in brain tumor surgery: the Big Five and the Milan Complexity Scale.

    Science.gov (United States)

    Ferroli, Paolo; Broggi, Morgan; Schiavolin, Silvia; Acerbi, Francesco; Bettamio, Valentina; Caldiroli, Dario; Cusin, Alberto; La Corte, Emanuele; Leonardi, Matilde; Raggi, Alberto; Schiariti, Marco; Visintini, Sergio; Franzini, Angelo; Broggi, Giovanni

    2015-12-01

    OBJECT The Milan Complexity Scale-a new practical grading scale designed to estimate the risk of neurological clinical worsening after performing surgery for tumor removal-is presented. METHODS A retrospective study was conducted on all elective consecutive surgical procedures for tumor resection between January 2012 and December 2014 at the Second Division of Neurosurgery at Fondazione IRCCS Istituto Neurologico Carlo Besta of Milan. A prospective database dedicated to reporting complications and all clinical and radiological data was retrospectively reviewed. The Karnofsky Performance Scale (KPS) was used to classify each patient's health status. Complications were divided into major and minor and recorded based on etiology and required treatment. A logistic regression model was used to identify possible predictors of clinical worsening after surgery in terms of changes between the preoperative and discharge KPS scores. Statistically significant predictors were rated based on their odds ratios in order to build an ad hoc complexity scale. For each patient, a corresponding total score was calculated, and ANOVA was performed to compare the mean total scores between the improved/unchanged and worsened patients. Relative risk (RR) and chi-square statistics were employed to provide the risk of worsening after surgery for each total score. RESULTS The case series was composed of 746 patients (53.2% female; mean age 51.3 ± 17.1). The most common tumors were meningiomas (28.6%) and glioblastomas (24.1%). The mortality rate was 0.94%, the major complication rate was 9.1%, and the minor complication rate was 32.6%. Of 746 patients, 523 (70.1%) patients improved or remained unchanged, and 223 (29.9%) patients worsened. The following factors were found to be statistically significant predictors of the change in KPS scores: tumor size larger than 4 cm, cranial nerve manipulation, major brain vessel manipulation, posterior fossa location, and eloquent area involvement

  9. Colour and luminance contrasts predict the human detection of natural stimuli in complex visual environments.

    Science.gov (United States)

    White, Thomas E; Rojas, Bibiana; Mappes, Johanna; Rautiala, Petri; Kemp, Darrell J

    2017-09-01

    Much of what we know about human colour perception has come from psychophysical studies conducted in tightly-controlled laboratory settings. An enduring challenge, however, lies in extrapolating this knowledge to the noisy conditions that characterize our actual visual experience. Here we combine statistical models of visual perception with empirical data to explore how chromatic (hue/saturation) and achromatic (luminant) information underpins the detection and classification of stimuli in a complex forest environment. The data best support a simple linear model of stimulus detection as an additive function of both luminance and saturation contrast. The strength of each predictor is modest yet consistent across gross variation in viewing conditions, which accords with expectation based upon general primate psychophysics. Our findings implicate simple visual cues in the guidance of perception amidst natural noise, and highlight the potential for informing human vision via a fusion between psychophysical modelling and real-world behaviour. © 2017 The Author(s).

  10. Simple Mindreading Abilities Predict Complex Theory of Mind: Developmental Delay in Autism Spectrum Disorders.

    Science.gov (United States)

    Pino, Maria Chiara; Mazza, Monica; Mariano, Melania; Peretti, Sara; Dimitriou, Dagmara; Masedu, Francesco; Valenti, Marco; Franco, Fabia

    2017-09-01

    Theory of mind (ToM) is impaired in individuals with autism spectrum disorders (ASD). The aims of this study were to: (i) examine the developmental trajectories of ToM abilities in two different mentalizing tasks in children with ASD compared to TD children; and (ii) to assess if a ToM simple test known as eyes-test could predict performance on the more advanced ToM task, i.e. comic strip test. Based on a sample of 37 children with ASD and 55 TD children, our results revealed slower development at varying rates in all ToM measures in children with ASD, with delayed onset compared to TD children. These results could stimulate new treatments for social abilities, which would lessen the social deficit in ASD.

  11. DNA motif alignment by evolving a population of Markov chains.

    Science.gov (United States)

    Bi, Chengpeng

    2009-01-30

    Deciphering cis-regulatory elements or de novo motif-finding in genomes still remains elusive although much algorithmic effort has been expended. The Markov chain Monte Carlo (MCMC) method such as Gibbs motif samplers has been widely employed to solve the de novo motif-finding problem through sequence local alignment. Nonetheless, the MCMC-based motif samplers still suffer from local maxima like EM. Therefore, as a prerequisite for finding good local alignments, these motif algorithms are often independently run a multitude of times, but without information exchange between different chains. Hence it would be worth a new algorithm design enabling such information exchange. This paper presents a novel motif-finding algorithm by evolving a population of Markov chains with information exchange (PMC), each of which is initialized as a random alignment and run by the Metropolis-Hastings sampler (MHS). It is progressively updated through a series of local alignments stochastically sampled. Explicitly, the PMC motif algorithm performs stochastic sampling as specified by a population-based proposal distribution rather than individual ones, and adaptively evolves the population as a whole towards a global maximum. The alignment information exchange is accomplished by taking advantage of the pooled motif site distributions. A distinct method for running multiple independent Markov chains (IMC) without information exchange, or dubbed as the IMC motif algorithm, is also devised to compare with its PMC counterpart. Experimental studies demonstrate that the performance could be improved if pooled information were used to run a population of motif samplers. The new PMC algorithm was able to improve the convergence and outperformed other popular algorithms tested using simulated and biological motif sequences.

  12. Is it possible to predict limb viability in complex Gustilo IIIB and IIIC tibial fractures? A comparison of two predictive indices.

    LENUS (Irish Health Repository)

    O'Sullivan, S T

    2012-02-03

    The patient with severe lower limb trauma presents a management dilemma; whether to amputate primarily or to attempt limb salvage. In recent years, many predictive indices have been published which purport to identify limbs which are non-viable. We retrospectively applied two recently described indices, the Mangled Extremity Severity Score (MESS) and the Limb Salvage Index (LSI), to 54 limbs in 50 patients with either Gustilo IIIB or IIIC complex tibial fractures. There were 22 amputations (40.7 per cent) in the series. The mean MESS score in the limb salvage group was 3.8 (range 2-10), and the mean MESS score in the amputation group was 7.7 (range 4-13) (P < 0.0001). The mean LSI score in the limb salvage group was 3.6 (range 3-8), and the mean LSI score in the amputation group was 6.9 (P < 0.01). However, in the group with MESS scores > 7 (which recommends amputation), there were three limbs which were salvaged with acceptable functional outcome. Similarly, in those with LSI scores > 6 (which recommends amputation), there were seven limbs successfully salvaged. A MESS > 7 offered a greater relative risk of amputation (9.2) than a LSI score > 6 (5.3). We found both indices of use in predicting limb salvage and functional outcome. However, neither is sufficiently accurate to be considered absolutely reliable in clinical practice.

  13. Feedback loops and reciprocal regulation: recurring motifs in the systems biology of the cell cycle

    OpenAIRE

    Ferrell, James E.

    2013-01-01

    The study of eukaryotic cell cycle regulation over the last several decades has led to a remarkably detailed understanding of the complex regulatory system that drives this fundamental process. This allows us to now look for recurring motifs in the regulatory system. Among these are negative feedback loops, which underpin checkpoints and generate cell cycle oscillations; positive feedback loops, which promote oscillations and make cell cycle transitions switch-like and unidirectional; and rec...

  14. IMPACT OF DIFFERENT TOPOGRAPHIC CORRECTIONS ON PREDICTION ACCURACY OF FOLIAGE PROJECTIVE COVER (FPC IN A TOPOGRAPHICALLY COMPLEX TERRAIN

    Directory of Open Access Journals (Sweden)

    S. Ediriweera

    2012-07-01

    Full Text Available Quantitative retrieval of land surface biological parameters (e.g. foliage projective cover [FPC] and Leaf Area Index is crucial for forest management, ecosystem modelling, and global change monitoring applications. Currently, remote sensing is a widely adopted method for rapid estimation of surface biological parameters in a landscape scale. Topographic correction is a necessary pre-processing step in the remote sensing application for topographically complex terrain. Selection of a suitable topographic correction method on remotely sensed spectral information is still an unresolved problem. The purpose of this study is to assess the impact of topographic corrections on the prediction of FPC in hilly terrain using an established regression model. Five established topographic corrections [C, Minnaert, SCS, SCS+C and processing scheme for standardised surface reflectance (PSSSR] were evaluated on Landsat TM5 acquired under low and high sun angles in closed canopied subtropical rainforest and eucalyptus dominated open canopied forest, north-eastern Australia. The effectiveness of methods at normalizing topographic influence, preserving biophysical spectral information, and internal data variability were assessed by statistical analysis and by comparing field collected FPC data. The results of statistical analyses show that SCS+C and PSSSR perform significantly better than other corrections, which were on less overcorrected areas of faintly illuminated slopes. However, the best relationship between FPC and Landsat spectral responses was obtained with the PSSSR by producing the least residual error. The SCS correction method was poor for correction of topographic effect in predicting FPC in topographically complex terrain.

  15. A structural model of the E. coli PhoB Dimer in the transcription initiation complex

    Directory of Open Access Journals (Sweden)

    Tung Chang-Shung

    2012-03-01

    Full Text Available Abstract Background There exist > 78,000 proteins and/or nucleic acids structures that were determined experimentally. Only a small portion of these structures corresponds to those of protein complexes. While homology modeling is able to exploit knowledge-based potentials of side-chain rotomers and backbone motifs to infer structures for new proteins, no such general method exists to extend our understanding of protein interaction motifs to novel protein complexes. Results We use a Motif Binding Geometries (MBG approach, to infer the structure of a protein complex from the database of complexes of homologous proteins taken from other contexts (such as the helix-turn-helix motif binding double stranded DNA, and demonstrate its utility on one of the more important regulatory complexes in biology, that of the RNA polymerase initiating transcription under conditions of phosphate starvation. The modeled PhoB/RNAP/σ-factor/DNA complex is stereo-chemically reasonable, has sufficient interfacial Solvent Excluded Surface Areas (SESAs to provide adequate binding strength, is physically meaningful for transcription regulation, and is consistent with a variety of known experimental constraints. Conclusions Based on a straightforward and easy to comprehend concept, "proteins and protein domains that fold similarly could interact similarly", a structural model of the PhoB dimer in the transcription initiation complex has been developed. This approach could be extended to enable structural modeling and prediction of other bio-molecular complexes. Just as models of individual proteins provide insight into molecular recognition, catalytic mechanism, and substrate specificity, models of protein complexes will provide understanding into the combinatorial rules of cellular regulation and signaling.

  16. Assessing local structure motifs using order parameters for motif recognition, interstitial identification, and diffusion path characterization

    Science.gov (United States)

    Zimmermann, Nils E. R.; Horton, Matthew K.; Jain, Anubhav; Haranczyk, Maciej

    2017-11-01

    Structure-property relationships form the basis of many design rules in materials science, including synthesizability and long-term stability of catalysts, control of electrical and optoelectronic behavior in semiconductors as well as the capacity of and transport properties in cathode materials for rechargeable batteries. The immediate atomic environments (i.e., the first coordination shells) of a few atomic sites are often a key factor in achieving a desired property. Some of the most frequently encountered coordination patterns are tetrahedra, octahedra, body and face-centered cubic as well as hexagonal closed packed-like environments. Here, we showcase the usefulness of local order parameters to identify these basic structural motifs in inorganic solid materials by developing classification criteria. We introduce a systematic testing framework, the Einstein crystal test rig, that probes the response of order parameters to distortions in perfect motifs to validate our approach. Subsequently, we highlight three important application cases. First, we map basic crystal structure information of a large materials database in an intuitive manner by screening the Materials Project (MP) database (61,422 compounds) for element-specific motif distributions. Second, we use the structure-motif recognition capabilities to automatically find interstitials in metals, semiconductor, and insulator materials. Our Interstitialcy Finding Tool (InFiT) facilitates high-throughput screenings of defect properties. Third, the order parameters are reliable and compact quantitative structure descriptors for characterizing diffusion hops of intercalants as our example of magnesium in MnO2-spinel indicates. Finally, the tools developed in our work are readily and freely available as software implementations in the pymatgen library, and we expect them to be further applied to machine-learning approaches for emerging applications in materials science.

  17. Assessing Local Structure Motifs Using Order Parameters for Motif Recognition, Interstitial Identification, and Diffusion Path Characterization

    Directory of Open Access Journals (Sweden)

    Nils E. R. Zimmermann

    2017-11-01

    Full Text Available Structure–property relationships form the basis of many design rules in materials science, including synthesizability and long-term stability of catalysts, control of electrical and optoelectronic behavior in semiconductors, as well as the capacity of and transport properties in cathode materials for rechargeable batteries. The immediate atomic environments (i.e., the first coordination shells of a few atomic sites are often a key factor in achieving a desired property. Some of the most frequently encountered coordination patterns are tetrahedra, octahedra, body and face-centered cubic as well as hexagonal close packed-like environments. Here, we showcase the usefulness of local order parameters to identify these basic structural motifs in inorganic solid materials by developing classification criteria. We introduce a systematic testing framework, the Einstein crystal test rig, that probes the response of order parameters to distortions in perfect motifs to validate our approach. Subsequently, we highlight three important application cases. First, we map basic crystal structure information of a large materials database in an intuitive manner by screening the Materials Project (MP database (61,422 compounds for element-specific motif distributions. Second, we use the structure-motif recognition capabilities to automatically find interstitials in metals, semiconductor, and insulator materials. Our Interstitialcy Finding Tool (InFiT facilitates high-throughput screenings of defect properties. Third, the order parameters are reliable and compact quantitative structure descriptors for characterizing diffusion hops of intercalants as our example of magnesium in MnO2-spinel indicates. Finally, the tools developed in our work are readily and freely available as software implementations in the pymatgen library, and we expect them to be further applied to machine-learning approaches for emerging applications in materials science.

  18. Comprehensive prediction in 78 human cell lines reveals rigidity and compactness of transcription factor dimers

    Science.gov (United States)

    Jankowski, Aleksander; Szczurek, Ewa; Jauch, Ralf; Tiuryn, Jerzy; Prabhakar, Shyam

    2013-01-01

    The binding of transcription factors (TFs) to their specific motifs in genomic regulatory regions is commonly studied in isolation. However, in order to elucidate the mechanisms of transcriptional regulation, it is essential to determine which TFs bind DNA cooperatively as dimers and to infer the precise nature of these interactions. So far, only a small number of such dimeric complexes are known. Here, we present an algorithm for predicting cell-type–specific TF–TF dimerization on DNA on a large scale, using DNase I hypersensitivity data from 78 human cell lines. We represented the universe of possible TF complexes by their corresponding motif complexes, and analyzed their occurrence at cell-type–specific DNase I hypersensitive sites. Based on ∼1.4 billion tests for motif complex enrichment, we predicted 603 highly significant cell-type–specific TF dimers, the vast majority of which are novel. Our predictions included 76% (19/25) of the known dimeric complexes and showed significant overlap with an experimental database of protein–protein interactions. They were also independently supported by evolutionary conservation, as well as quantitative variation in DNase I digestion patterns. Notably, the known and predicted TF dimers were almost always highly compact and rigidly spaced, suggesting that TFs dimerize in close proximity to their partners, which results in strict constraints on the structure of the DNA-bound complex. Overall, our results indicate that chromatin openness profiles are highly predictive of cell-type–specific TF–TF interactions. Moreover, cooperative TF dimerization seems to be a widespread phenomenon, with multiple TF complexes predicted in most cell types. PMID:23554463

  19. Crystallization and preliminary X-ray diffraction analysis of motif N from Saccharomyces cerevisiae Dbf4

    International Nuclear Information System (INIS)

    Matthews, Lindsay A.; Duong, Andrew; Prasad, Ajai A.; Duncker, Bernard P.; Guarné, Alba

    2009-01-01

    To understand the role of the Cdc7–Dbf4 complex in checkpoint responses, a fragment of Saccharomyces cerevisiae Dbf4 encompassing motif N was isolated, overproduced and crystallized. The Cdc7–Dbf4 complex plays an instrumental role in the initiation of DNA replication and is a target of replication-checkpoint responses in Saccharomyces cerevisiae. Cdc7 is a conserved serine/threonine kinase whose activity depends on association with its regulatory subunit, Dbf4. A conserved sequence near the N-terminus of Dbf4 (motif N) is necessary for the interaction of Cdc7–Dbf4 with the checkpoint kinase Rad53. To understand the role of the Cdc7–Dbf4 complex in checkpoint responses, a fragment of Saccharomyces cerevisiae Dbf4 encompassing motif N was isolated, overproduced and crystallized. A complete native data set was collected at 100 K from crystals that diffracted X-rays to 2.75 Å resolution and structure determination is currently under way

  20. The effects of sampling bias and model complexity on the predictive performance of MaxEnt species distribution models.

    Science.gov (United States)

    Syfert, Mindy M; Smith, Matthew J; Coomes, David A

    2013-01-01

    Species distribution models (SDMs) trained on presence-only data are frequently used in ecological research and conservation planning. However, users of SDM software are faced with a variety of options, and it is not always obvious how selecting one option over another will affect model performance. Working with MaxEnt software and with tree fern presence data from New Zealand, we assessed whether (a) choosing to correct for geographical sampling bias and (b) using complex environmental response curves have strong effects on goodness of fit. SDMs were trained on tree fern data, obtained from an online biodiversity data portal, with two sources that differed in size and geographical sampling bias: a small, widely-distributed set of herbarium specimens and a large, spatially clustered set of ecological survey records. We attempted to correct for geographical sampling bias by incorporating sampling bias grids in the SDMs, created from all georeferenced vascular plants in the datasets, and explored model complexity issues by fitting a wide variety of environmental response curves (known as "feature types" in MaxEnt). In each case, goodness of fit was assessed by comparing predicted range maps with tree fern presences and absences using an independent national dataset to validate the SDMs. We found that correcting for geographical sampling bias led to major improvements in goodness of fit, but did not entirely resolve the problem: predictions made with clustered ecological data were inferior to those made with the herbarium dataset, even after sampling bias correction. We also found that the choice of feature type had negligible effects on predictive performance, indicating that simple feature types may be sufficient once sampling bias is accounted for. Our study emphasizes the importance of reducing geographical sampling bias, where possible, in datasets used to train SDMs, and the effectiveness and essentialness of sampling bias correction within MaxEnt.

  1. Probing structural changes of self assembled i-motif DNA

    KAUST Repository

    Lee, Iljoon; Patil, Sachin; Fhayli, Karim; Alsaiari, Shahad K.; Khashab, Niveen M.

    2015-01-01

    We report an i-motif structural probing system based on Thioflavin T (ThT) as a fluorescent sensor. This probe can discriminate the structural changes of RET and Rb i-motif sequences according to pH change. This journal is

  2. RNA recognition motif (RRM)-containing proteins in Bombyx mori

    African Journals Online (AJOL)

    STORAGESEVER

    2009-03-20

    Mar 20, 2009 ... Recognition Motif (RRM), sometimes referred to as. RNP1, is one of the first identified domains for RNA interaction. RRM is very common ..... Apart from the RRM motif, eIF3-S9 has a Trp-Asp. (WD) repeat domain, Poly (A) ...

  3. BlockLogo: Visualization of peptide and sequence motif conservation

    DEFF Research Database (Denmark)

    Olsen, Lars Rønn; Kudahl, Ulrich Johan; Simon, Christian

    2013-01-01

    BlockLogo is a web-server application for the visualization of protein and nucleotide fragments, continuous protein sequence motifs, and discontinuous sequence motifs using calculation of block entropy from multiple sequence alignments. The user input consists of a multiple sequence alignment, se...

  4. Fingerprint motifs of phytases | Fan | African Journal of Biotechnology

    African Journals Online (AJOL)

    Among the total of potential 173 phytases gained in 11 plant genomes through MAST, PAPhys are the major phytases, and HAPhys are the minor, and other phytase groups are not found in planta. Keywords: Phytase, fingerprint motif, multiple EM for motif elicitation (MEME), MAST African Journal of Biotechnology Vol.

  5. Predicting availability functions in time-dependent complex systems with SAEDES simulation algorithms

    International Nuclear Information System (INIS)

    Faulin, Javier; Juan, Angel A.; Serrat, Carles; Bargueno, Vicente

    2008-01-01

    In this paper, we propose the use of discrete-event simulation (DES) as an efficient methodology to obtain estimates of both survival and availability functions in time-dependent real systems-such as telecommunication networks or distributed computer systems. We discuss the use of DES in reliability and availability studies, not only as an alternative to the use of analytical and probabilistic methods, but also as a complementary way to: (i) achieve a better understanding of the system internal behavior and (ii) find out the relevance of each component under reliability/availability considerations. Specifically, this paper describes a general methodology and two DES algorithms, called SAEDES, which can be used to analyze a wide range of time-dependent complex systems, including those presenting multiple states, dependencies among failure/repair times or non-perfect maintenance policies. These algorithms can provide valuable information, specially during the design stages, where different scenarios can be compared in order to select a system design offering adequate reliability and availability levels. Two case studies are discussed, using a C/C++ implementation of the SAEDES algorithms, to show some potential applications of our approach

  6. Prediction of the dynamic response of complex transmission line systems for unsteady pressure measurements

    International Nuclear Information System (INIS)

    Antonini, C; Persico, G; Rowe, A L

    2008-01-01

    Among the measurement and control systems of gas turbine engines, a recent new issue is the possibility of performing unsteady pressure measurements to detect flow anomalies in an engine or to evaluate loads on aerodynamic surfaces. A possible answer to this demand could be extending the use of well known and widely used transmission line systems, which have been applied so far to steady monitoring, to unsteady measurements thanks to proper dynamic modeling and compensation. Despite the huge number of models existing in the literature, a novel method has been developed, which is at the same time easy-to-handle, flexible and capable of reproducing the actual physics of the problem. Furthermore, the new model is able to deal with arbitrary complex networks of lines and cavities, and thus its applicability is not limited to series-connected systems. The main objectives of this paper are to show the derivation of the model, its validation against experimental tests and example of its applicability

  7. Predicting availability functions in time-dependent complex systems with SAEDES simulation algorithms

    Energy Technology Data Exchange (ETDEWEB)

    Faulin, Javier [Department of Statistics and Operations Research, Los Magnolios Building, First Floor, Campus Arrosadia, Public University of Navarre, 31006 Pamplona, Navarre (Spain)], E-mail: javier.faulin@unavarra.es; Juan, Angel A. [Department of Applied Mathematics I, Av. Doctor Maranon 44-50, Technical University of Catalonia, 08028 Barcelona (Spain)], E-mail: angel.alejandro.juan@upc.edu; Serrat, Carles [Department of Applied Mathematics I, Av. Doctor Maranon 44-50, Technical University of Catalonia, 08028 Barcelona (Spain)], E-mail: carles.serrat@upc.edu; Bargueno, Vicente [Department of Applied Mathematics I, ETS Ingenieros Industriales, Universidad Nacional de Educacion a Distancia, 28080 Madrid (Spain)], E-mail: vbargueno@ind.uned.es

    2008-11-15

    In this paper, we propose the use of discrete-event simulation (DES) as an efficient methodology to obtain estimates of both survival and availability functions in time-dependent real systems-such as telecommunication networks or distributed computer systems. We discuss the use of DES in reliability and availability studies, not only as an alternative to the use of analytical and probabilistic methods, but also as a complementary way to: (i) achieve a better understanding of the system internal behavior and (ii) find out the relevance of each component under reliability/availability considerations. Specifically, this paper describes a general methodology and two DES algorithms, called SAEDES, which can be used to analyze a wide range of time-dependent complex systems, including those presenting multiple states, dependencies among failure/repair times or non-perfect maintenance policies. These algorithms can provide valuable information, specially during the design stages, where different scenarios can be compared in order to select a system design offering adequate reliability and availability levels. Two case studies are discussed, using a C/C++ implementation of the SAEDES algorithms, to show some potential applications of our approach.

  8. Complex population response of dorsal putamen neurons predicts the ability to learn.

    Science.gov (United States)

    Laquitaine, Steeve; Piron, Camille; Abellanas, David; Loewenstein, Yonatan; Boraud, Thomas

    2013-01-01

    Day-to-day variability in performance is a common experience. We investigated its neural correlate by studying learning behavior of monkeys in a two-alternative forced choice task, the two-armed bandit task. We found substantial session-to-session variability in the monkeys' learning behavior. Recording the activity of single dorsal putamen neurons we uncovered a dual function of this structure. It has been previously shown that a population of neurons in the DLP exhibits firing activity sensitive to the reward value of chosen actions. Here, we identify putative medium spiny neurons in the dorsal putamen that are cue-selective and whose activity builds up with learning. Remarkably we show that session-to-session changes in the size of this population and in the intensity with which this population encodes cue-selectivity is correlated with session-to-session changes in the ability to learn the task. Moreover, at the population level, dorsal putamen activity in the very beginning of the session is correlated with the performance at the end of the session, thus predicting whether the monkey will have a "good" or "bad" learning day. These results provide important insights on the neural basis of inter-temporal performance variability.

  9. T cell receptor zeta allows stable expression of receptors containing the CD3gamma leucine-based receptor-sorting motif

    DEFF Research Database (Denmark)

    Dietrich, J; Geisler, C

    1998-01-01

    The leucine-based motif in the T cell receptor (TCR) subunit CD3gamma constitutes a strong internalization signal. In fully assembled TCR this motif is inactive unless phosphorylated. In contrast, the motif is constitutively active in CD4/CD3gamma and Tac/CD3gamma chimeras independently of phosph......The leucine-based motif in the T cell receptor (TCR) subunit CD3gamma constitutes a strong internalization signal. In fully assembled TCR this motif is inactive unless phosphorylated. In contrast, the motif is constitutively active in CD4/CD3gamma and Tac/CD3gamma chimeras independently...... of phosphorylation and leads to rapid internalization and sorting of these chimeras to lysosomal degradation. Because the TCRzeta chain rescues incomplete TCR complexes from lysosomal degradation and allows stable surface expression of fully assembled TCR, we addressed the question whether TCRzeta has the potential...... to mask the CD3gamma leucine-based motif. By studying CD4/CD3gamma and CD16/CD3gamma chimeras, we found that CD16/CD3gamma chimeras associated with TCRzeta. The CD16/CD3gamma-TCRzeta complexes were stably expressed at the cell surface and had a low spontaneous internalization rate, indicating...

  10. A novel complex model of hemodialysis adequacy: Predictive value and relationship with malnutrition inflammation score

    Directory of Open Access Journals (Sweden)

    Vlatković Vlastimir

    2017-01-01

    Full Text Available Target dialysis dose to ensure the best patient outcome is still a matter of debate. Traditional models have a number of limitations and do not comprehensively reflect all factors involved. In this study we present a new complex model of dialysis adequacy, the hemodialysis adequacy score (HAS, and evaluate its prognostic value, as well as its relationship with the malnutrition-inflammation score (MIS. The components of HAS included paradigms of the 6 major factors known to influence the outcome of hemodialysis (HD patients: the modified Karnofsky index (KI, the Charlson comorbidity index (CCI, Kt/V and URR measures of dialysis dose, body mass index (BMI and serum albumin level, serum levels of hemoglobin and ferritin, intact parathyroid hormone (iPTH and calciumphosphorus solubility product. The score was evaluated in a 24-month prospective study on 147 HD patients. Odds ratio analysis showed that hospitalized patients had twice the chance to have HAS >13 compared to those who were not hospitalized during the study period (OR=2.152, CI 95% (1.0024- 4.619. Mortality rate was significantly higher in patients with a HAS >13 at the 12-month follow-up (χ2=16.416, p 13 had significantly higher probability of death (log-rank Cox- Mantel=17.920, df=1, p <0.00023. The HAS directly and significantly correlated with the MIS at all measurements (p <0.0001. Results confirmed that the HAS is a useful tool to assess dialysis adequacy with a good prognostic value. The cutoff level for the HAS at 13 points was associated with an unfavorable outcome.

  11. Complex proximal humerus fractures: Hertel's criteria reliability to predict head necrosis.

    Science.gov (United States)

    Campochiaro, G; Rebuzzi, M; Baudi, P; Catani, F

    2015-09-01

    The risk of post-traumatic humeral head avascular necrosis (AVN), regardless of the treatment, has a high reported incidence. In 2004, Hertel et al. stated that the most relevant predictors of ischemia after intracapsular fracture treated with osteosynthesis are the calcar length, medial hinge integrity and some specific fracture types. Based on Hertel's model, the purpose of this study is to evaluate both its reliability and weaknesses in our series of 267 fractures, assessing how the anatomical configuration of fracture, the quality of reduction and its maintenance were predictive of osteonecrosis development, and so to suggest a treatment choice algorithm. A retrospective study, level of evidence IV, was conducted to duly assess the radiographic features of 267 fractures treated from 2004 to 2010 following Hertel's criteria treated with open reduction and internal fixation by angular stability plates and screws. The average age was 65.2 years. The average follow-up was 28.3 ± 17.0 months. The percentage of AVN, the quality and maintenance of reduction obtained during surgery were evaluated. The AVN incidence was 3.7 %. No significant correlation with gender, age and fracture type was found. At the last follow-up X-ray, only 30 % presented all Hertel's good predictors in the AVN group, 4.7 % in the non-AVN group (p AVN group, it was poor in 50 %; while in the non-AVN group, it was poor in 3.4 % (p AVN were symptomatic, and three needed a second surgery. Hertel's criteria are important in the surgical planning, but they are not sufficient: an accurate evaluation of the calcar area fracture in three planes is required. All fractures involving calcar area should be studied with CT.

  12. Rtt107/Esc4 binds silent chromatin and DNA repair proteins using different BRCT motifs

    Directory of Open Access Journals (Sweden)

    Jockusch Rebecca A

    2006-11-01

    Full Text Available Abstract Background By screening a plasmid library for proteins that could cause silencing when targeted to the HMR locus in Saccharomyces cerevisiae, we previously reported the identification of Rtt107/Esc4 based on its ability to establish silent chromatin. In this study we aimed to determine the mechanism of Rtt107/Esc4 targeted silencing and also learn more about its biological functions. Results Targeted silencing by Rtt107/Esc4 was dependent on the SIR genes, which encode obligatory structural and enzymatic components of yeast silent chromatin. Based on its sequence, Rtt107/Esc4 was predicted to contain six BRCT motifs. This motif, originally identified in the human breast tumor suppressor gene BRCA1, is a protein interaction domain. The targeted silencing activity of Rtt107/Esc4 resided within the C-terminal two BRCT motifs, and this region of the protein bound to Sir3 in two-hybrid tests. Deletion of RTT107/ESC4 caused sensitivity to the DNA damaging agent MMS as well as to hydroxyurea. A two-hybrid screen showed that the N-terminal BRCT motifs of Rtt107/Esc4 bound to Slx4, a protein previously shown to be involved in DNA repair and required for viability in a strain lacking the DNA helicase Sgs1. Like SLX genes, RTT107ESC4 interacted genetically with SGS1; esc4Δ sgs1Δ mutants were viable, but exhibited a slow-growth phenotype and also a synergistic DNA repair defect. Conclusion Rtt107/Esc4 binds to the silencing protein Sir3 and the DNA repair protein Slx4 via different BRCT motifs, thus providing a bridge linking silent chromatin to DNA repair enzymes.

  13. Mitochondrial and Y chromosome haplotype motifs as diagnostic markers of Jewish ancestry: a reconsideration.

    Directory of Open Access Journals (Sweden)

    Sergio eTofanelli

    2014-11-01

    Full Text Available Several authors have proposed haplotype motifs based on site variants at the mitochondrial genome (mtDNA and the non-recombining portion of the Y chromosome (NRY to trace the genealogies of Jewish people. Here, we analyzed their main approaches and test the feasibility of adopting motifs as ancestry markers through construction of a large database of mtDNA and NRY haplotypes from public genetic genealogical repositories. We verified the reliability of Jewish ancestry prediction based on the Cohen and Levite Modal Haplotypes in their classical 6 STR marker format or in the extended 12 STR format, as well as four founder mtDNA lineages (HVS-I segments accounting for about 40% of the current population of Ashkenazi Jews. For this purpose we compared haplotype composition in individuals of self-reported Jewish ancestry with the rest of European, African or Middle Eastern samples, to test for non-random association of ethno-geographic groups and haplotypes. Overall, NRY and mtDNA based motifs, previously reported to differentiate between groups, were found to be more represented in Jewish compared to non-Jewish groups. However, this seems to stem from common ancestors of Jewish lineages being rather recent respect to ancestors of non-Jewish lineages with the same haplotype signatures. Moreover, the polyphyly of haplotypes which contain the proposed motifs and the misuse of constant mutation rates heavily affected previous attempts to correctly dating the origin of common ancestries. Accordingly, our results stress the limitations of using the above haplotype motifs as reliable Jewish ancestry predictors and show its inadequacy for forensic or genealogical purposes.

  14. Identification of group specific motifs in Beta-lactamase family of proteins

    Directory of Open Access Journals (Sweden)

    Saxena Akansha

    2009-12-01

    Full Text Available Abstract Background Beta-lactamases are one of the most serious threats to public health. In order to combat this threat we need to study the molecular and functional diversity of these enzymes and identify signatures specific to these enzymes. These signatures will enable us to develop inhibitors and diagnostic probes specific to lactamases. The existing classification of beta-lactamases was developed nearly 30 years ago when few lactamases were available. DLact database contain more than 2000 beta-lactamase, which can be used to study the molecular diversity and to identify signatures specific to this family. Methods A set of 2020 beta-lactamase proteins available in the DLact database http://59.160.102.202/DLact were classified using graph-based clustering of Best Bi-Directional Hits. Non-redundant (> 90 percent identical protein sequences from each group were aligned using T-Coffee and annotated using information available in literature. Motifs specific to each group were predicted using PRATT program. Results The graph-based classification of beta-lactamase proteins resulted in the formation of six groups (Four major groups containing 191, 726, 774 and 73 proteins while two minor groups containing 50 and 8 proteins. Based on the information available in literature, we found that each of the four major groups correspond to the four classes proposed by Ambler. The two minor groups were novel and do not contain molecular signatures of beta-lactamase proteins reported in literature. The group-specific motifs showed high sensitivity (> 70% and very high specificity (> 90%. The motifs from three groups (corresponding to class A, C and D had a high level of conservation at DNA as well as protein level whereas the motifs from the fourth group (corresponding to class B showed conservation at only protein level. Conclusion The graph-based classification of beta-lactamase proteins corresponds with the classification proposed by Ambler, thus there is

  15. Identification of amino acid residues in protein SRP72 required for binding to a kinked 5e motif of the human signal recognition particle RNA

    Directory of Open Access Journals (Sweden)

    Zwieb Christian

    2010-11-01

    Full Text Available Abstract Background Human cells depend critically on the signal recognition particle (SRP for the sorting and delivery of their proteins. The SRP is a ribonucleoprotein complex which binds to signal sequences of secretory polypeptides as they emerge from the ribosome. Among the six proteins of the eukaryotic SRP, the largest protein, SRP72, is essential for protein targeting and possesses a poorly characterized RNA binding domain. Results We delineated the minimal region of SRP72 capable of forming a stable complex with an SRP RNA fragment. The region encompassed residues 545 to 585 of the full-length human SRP72 and contained a lysine-rich cluster (KKKKKKKKGK at postions 552 to 561 as well as a conserved Pfam motif with the sequence PDPXRWLPXXER at positions 572 to 583. We demonstrated by site-directed mutagenesis that both regions participated in the formation of a complex with the RNA. In agreement with biochemical data and results from chymotryptic digestion experiments, molecular modeling of SRP72 implied that the invariant W577 was located inside the predicted structure of an RNA binding domain. The 11-nucleotide 5e motif contained within the SRP RNA fragment was shown by comparative electrophoresis on native polyacrylamide gels to conform to an RNA kink-turn. The model of the complex suggested that the conserved A240 of the K-turn, previously identified as being essential for the binding to SRP72, could protrude into a groove of the SRP72 RNA binding domain, similar but not identical to how other K-turn recognizing proteins interact with RNA. Conclusions The results from the presented experiments provided insights into the molecular details of a functionally important and structurally interesting RNA-protein interaction. A model for how a ligand binding pocket of SRP72 can accommodate a new RNA K-turn in the 5e region of the eukaryotic SRP RNA is proposed.

  16. Identification of amino acid residues in protein SRP72 required for binding to a kinked 5e motif of the human signal recognition particle RNA.

    Science.gov (United States)

    Iakhiaeva, Elena; Iakhiaev, Alexei; Zwieb, Christian

    2010-11-13

    Human cells depend critically on the signal recognition particle (SRP) for the sorting and delivery of their proteins. The SRP is a ribonucleoprotein complex which binds to signal sequences of secretory polypeptides as they emerge from the ribosome. Among the six proteins of the eukaryotic SRP, the largest protein, SRP72, is essential for protein targeting and possesses a poorly characterized RNA binding domain. We delineated the minimal region of SRP72 capable of forming a stable complex with an SRP RNA fragment. The region encompassed residues 545 to 585 of the full-length human SRP72 and contained a lysine-rich cluster (KKKKKKKKGK) at postions 552 to 561 as well as a conserved Pfam motif with the sequence PDPXRWLPXXER at positions 572 to 583. We demonstrated by site-directed mutagenesis that both regions participated in the formation of a complex with the RNA. In agreement with biochemical data and results from chymotryptic digestion experiments, molecular modeling of SRP72 implied that the invariant W577 was located inside the predicted structure of an RNA binding domain. The 11-nucleotide 5e motif contained within the SRP RNA fragment was shown by comparative electrophoresis on native polyacrylamide gels to conform to an RNA kink-turn. The model of the complex suggested that the conserved A240 of the K-turn, previously identified as being essential for the binding to SRP72, could protrude into a groove of the SRP72 RNA binding domain, similar but not identical to how other K-turn recognizing proteins interact with RNA. The results from the presented experiments provided insights into the molecular details of a functionally important and structurally interesting RNA-protein interaction. A model for how a ligand binding pocket of SRP72 can accommodate a new RNA K-turn in the 5e region of the eukaryotic SRP RNA is proposed.

  17. Matrix Metalloproteinase-9/Neutrophil Gelatinase-Associated Lipocalin Complex Activity in Human Glioma Samples Predicts Tumor Presence and Clinical Prognosis

    Directory of Open Access Journals (Sweden)

    Ming-Fa Liu

    2015-01-01

    Full Text Available Matrix metalloproteinase-9/neutrophil gelatinase-associated lipocalin (MMP-9/NGAL complex activity is elevated in brain tumors and may serve as a molecular marker for brain tumors. However, the relationship between MMP-9/NGAL activity in brain tumors and patient prognosis and treatment response remains unclear. Here, we compared the clinical characteristics of glioma patients with the MMP-9/NGAL activity measured in their respective tumor and urine samples. Using gelatin zymography assays, we found that MMP-9/NGAL activity was significantly increased in tumor tissues (TT and preoperative urine samples (Preop-1d urine. Activity was reduced by seven days after surgery (Postop-1w urine and elevated again in cases of tumor recurrence. The MMP-9/NGAL status correlated well with MRI-based tumor assessments. These findings suggest that MMP-9/NGAL activity could be a novel marker to detect gliomas and predict the clinical outcome of patients.

  18. Predicting Complexation Thermodynamic Parameters of β-Cyclodextrin with Chiral Guests by Using Swarm Intelligence and Support Vector Machines

    Directory of Open Access Journals (Sweden)

    Luckhana Lawtrakul

    2009-05-01

    Full Text Available The Particle Swarm Optimization (PSO and Support Vector Machines (SVMs approaches are used for predicting the thermodynamic parameters for the 1:1 inclusion complexation of chiral guests with β-cyclodextrin. A PSO is adopted for descriptor selection in the quantitative structure-property relationships (QSPR of a dataset of 74 chiral guests due to its simplicity, speed, and consistency. The modified PSO is then combined with SVMs for its good approximating properties, to generate a QSPR model with the selected features. Linear, polynomial, and Gaussian radial basis functions are used as kernels in SVMs. All models have demonstrated an impressive performance with R2 higher than 0.8.

  19. Predicting peptides binding to MHC class II molecules using multi-objective evolutionary algorithms

    Directory of Open Access Journals (Sweden)

    Feng Lin

    2007-11-01

    Full Text Available Abstract Background Peptides binding to Major Histocompatibility Complex (MHC class II molecules are crucial for initiation and regulation of immune responses. Predicting peptides that bind to a specific MHC molecule plays an important role in determining potential candidates for vaccines. The binding groove in class II MHC is open at both ends, allowing peptides longer than 9-mer to bind. Finding the consensus motif facilitating the binding of peptides to a MHC class II molecule is difficult because of different lengths of binding peptides and varying location of 9-mer binding core. The level of difficulty increases when the molecule is promiscuous and binds to a large number of low affinity peptides. In this paper, we propose two approaches using multi-objective evolutionary algorithms (MOEA for predicting peptides binding to MHC class II molecules. One uses the information from both binders and non-binders for self-discovery of motifs. The other, in addition, uses information from experimentally determined motifs for guided-discovery of motifs. Results The proposed methods are intended for finding peptides binding to MHC class II I-Ag7 molecule – a promiscuous binder to a large number of low affinity peptides. Cross-validation results across experiments on two motifs derived for I-Ag7 datasets demonstrate better generalization abilities and accuracies of the present method over earlier approaches. Further, the proposed method was validated and compared on two publicly available benchmark datasets: (1 an ensemble of qualitative HLA-DRB1*0401 peptide data obtained from five different sources, and (2 quantitative peptide data obtained for sixteen different alleles comprising of three mouse alleles and thirteen HLA alleles. The proposed method outperformed earlier methods on most datasets, indicating that it is well suited for finding peptides binding to MHC class II molecules. Conclusion We present two MOEA-based algorithms for finding motifs

  20. Triadic motifs in the dependence networks of virtual societies

    Science.gov (United States)

    Xie, Wen-Jie; Li, Ming-Xia; Jiang, Zhi-Qiang; Zhou, Wei-Xing

    2014-06-01

    In friendship networks, individuals have different numbers of friends, and the closeness or intimacy between an individual and her friends is heterogeneous. Using a statistical filtering method to identify relationships about who depends on whom, we construct dependence networks (which are directed) from weighted friendship networks of avatars in more than two hundred virtual societies of a massively multiplayer online role-playing game (MMORPG). We investigate the evolution of triadic motifs in dependence networks. Several metrics show that the virtual societies evolved through a transient stage in the first two to three weeks and reached a relatively stable stage. We find that the unidirectional loop motif (M9) is underrepresented and does not appear, open motifs are also underrepresented, while other close motifs are overrepresented. We also find that, for most motifs, the overall level difference of the three avatars in the same motif is significantly lower than average, whereas the sum of ranks is only slightly larger than average. Our findings show that avatars' social status plays an important role in the formation of triadic motifs.

  1. Triadic motifs in the dependence networks of virtual societies.

    Science.gov (United States)

    Xie, Wen-Jie; Li, Ming-Xia; Jiang, Zhi-Qiang; Zhou, Wei-Xing

    2014-06-10

    In friendship networks, individuals have different numbers of friends, and the closeness or intimacy between an individual and her friends is heterogeneous. Using a statistical filtering method to identify relationships about who depends on whom, we construct dependence networks (which are directed) from weighted friendship networks of avatars in more than two hundred virtual societies of a massively multiplayer online role-playing game (MMORPG). We investigate the evolution of triadic motifs in dependence networks. Several metrics show that the virtual societies evolved through a transient stage in the first two to three weeks and reached a relatively stable stage. We find that the unidirectional loop motif (M9) is underrepresented and does not appear, open motifs are also underrepresented, while other close motifs are overrepresented. We also find that, for most motifs, the overall level difference of the three avatars in the same motif is significantly lower than average, whereas the sum of ranks is only slightly larger than average. Our findings show that avatars' social status plays an important role in the formation of triadic motifs.

  2. A speedup technique for (l, d-motif finding algorithms

    Directory of Open Access Journals (Sweden)

    Dinh Hieu

    2011-03-01

    Full Text Available Abstract Background The discovery of patterns in DNA, RNA, and protein sequences has led to the solution of many vital biological problems. For instance, the identification of patterns in nucleic acid sequences has resulted in the determination of open reading frames, identification of promoter elements of genes, identification of intron/exon splicing sites, identification of SH RNAs, location of RNA degradation signals, identification of alternative splicing sites, etc. In protein sequences, patterns have proven to be extremely helpful in domain identification, location of protease cleavage sites, identification of signal peptides, protein interactions, determination of protein degradation elements, identification of protein trafficking elements, etc. Motifs are important patterns that are helpful in finding transcriptional regulatory elements, transcription factor binding sites, functional genomics, drug design, etc. As a result, numerous papers have been written to solve the motif search problem. Results Three versions of the motif search problem have been proposed in the literature: Simple Motif Search (SMS, (l, d-motif search (or Planted Motif Search (PMS, and Edit-distance-based Motif Search (EMS. In this paper we focus on PMS. Two kinds of algorithms can be found in the literature for solving the PMS problem: exact and approximate. An exact algorithm identifies the motifs always and an approximate algorithm may fail to identify some or all of the motifs. The exact version of PMS problem has been shown to be NP-hard. Exact algorithms proposed in the literature for PMS take time that is exponential in some of the underlying parameters. In this paper we propose a generic technique that can be used to speedup PMS algorithms. Conclusions We present a speedup technique that can be used on any PMS algorithm. We have tested our speedup technique on a number of algorithms. These experimental results show that our speedup technique is indeed very

  3. Dynamic Failure Properties of the Porcine Medial Collateral Ligament-Bone Complex for Predicting Injury in Automotive Collisions

    Science.gov (United States)

    Peck, Louis; Billiar, Kristen; Ray, Malcolm

    2010-01-01

    The goal of this study was to model the dynamic failure properties of ligaments and their attachment sites to facilitate the development of more realistic dynamic finite element models of the human lower extremities for use in automotive collision simulations. Porcine medial collateral ligaments were chosen as a test model due to their similarities in size and geometry with human ligaments. Each porcine medial collateral ligament-bone complex (n = 12) was held in a custom test fixture placed in a drop tower to apply an axial impulsive impact load, applying strain rates ranging from 0.005 s-1 to 145 s-1. The data from the impact tests were analyzed using nonlinear regression to construct model equations for predicting the failure load of ligament-bone complexes subjected to specific strain rates as calculated from finite element knee, thigh, and hip impact simulations. The majority of the ligaments tested failed by tibial avulsion (75%) while the remaining ligaments failed via mid-substance tearing. The failure load ranged from 384 N to 1184 N and was found to increase with the applied strain rate and the product of ligament length and cross-sectional area. The findings of this study indicate the force required to rupture the porcine MCL increases with the applied bone-to-bone strain rate in the range expected from high speed frontal automotive collisions. PMID:20461229

  4. Amphipathic motifs in BAR domains are essential for membrane curvature sensing

    DEFF Research Database (Denmark)

    Bhatia, Vikram K; Madsen, Kenneth L; Bolinger, Pierre-Yves

    2009-01-01

    BAR (Bin/Amphiphysin/Rvs) domains and amphipathic alpha-helices (AHs) are believed to be sensors of membrane curvature thus facilitating the assembly of protein complexes on curved membranes. Here, we used quantitative fluorescence microscopy to compare the binding of both motifs on single...... nanosized liposomes of different diameters and therefore membrane curvature. Characterization of members of the three BAR domain families showed surprisingly that the crescent-shaped BAR dimer with its positively charged concave face is not able to sense membrane curvature. Mutagenesis on BAR domains showed...... that membrane curvature sensing critically depends on the N-terminal AH and furthermore that BAR domains sense membrane curvature through hydrophobic insertion in lipid packing defects and not through electrostatics. Consequently, amphipathic motifs, such as AHs, that are often associated with BAR domains...

  5. Spectral Barcoding of Quantum Dots: Deciphering Structural Motifs from the Excitonic Spectra

    International Nuclear Information System (INIS)

    Mlinar, V.; Zunger, A.

    2009-01-01

    Self-assembled semiconductor quantum dots (QDs) show in high-resolution single-dot spectra a multitude of sharp lines, resembling a barcode, due to various neutral and charged exciton complexes. Here we propose the 'spectral barcoding' method that deciphers structural motifs of dots by using such barcode as input to an artificial-intelligence learning system. Thus, we invert the common practice of deducing spectra from structure by deducing structure from spectra. This approach (i) lays the foundation for building a much needed structure-spectra understanding for large nanostructures and (ii) can guide future design of desired optical features of QDs by controlling during growth only those structural motifs that decide given optical features.

  6. Characterization of a Smad motif similar to Drosophila mad in the mouse Msx 1 promoter.

    Science.gov (United States)

    Alvarez Martinez, Cristina E; Binato, Renata; Gonzalez, Sayonara; Pereira, Monica; Robert, Benoit; Abdelhay, Eliana

    2002-03-01

    Mouse Msx 1 gene, orthologous of the Drosophila msh, is involved in several developmental processes. BMP family members are major proteins in the regulation of Msx 1 expression. BMP signaling activates Smad 1/5/8 proteins, which associate to Smad 4 before translocating to the nucleus. Analysis of Msx 1 promoter revealed the presence of three elements similar to the consensus established for Mad, the Smad 1 Drosophila counterpart. Notably, such an element was identified in an enhancer important for Msx 1 regulation. Gel shift analysis demonstrated that proteins from 13.5 dpc embryo associate to this enhancer. Remarkably, supershift assays showed that Smad proteins are present in the complex. Purified Smad 1 and 4 also bind to this fragment. We demonstrate that functional binding sites in this enhancer are confined to the Mad motif and flanking region. Our data suggest that this Mad motif may be functional in response to BMP signaling. ©2002 Elsevier Science (USA).

  7. Super-transient scaling in time-delay autonomous Boolean network motifs

    Energy Technology Data Exchange (ETDEWEB)

    D' Huys, Otti, E-mail: otti.dhuys@phy.duke.edu; Haynes, Nicholas D. [Department of Physics, Duke University, Durham, North Carolina 27708 (United States); Lohmann, Johannes [Department of Physics, Duke University, Durham, North Carolina 27708 (United States); Institut für Theoretische Physik, Technische Universität Berlin, Hardenbergstraße 36, 10623 Berlin (Germany); Gauthier, Daniel J. [Department of Physics, Duke University, Durham, North Carolina 27708 (United States); Department of Physics, The Ohio State University, Columbus, Ohio 43210 (United States)

    2016-09-15

    Autonomous Boolean networks are commonly used to model the dynamics of gene regulatory networks and allow for the prediction of stable dynamical attractors. However, most models do not account for time delays along the network links and noise, which are crucial features of real biological systems. Concentrating on two paradigmatic motifs, the toggle switch and the repressilator, we develop an experimental testbed that explicitly includes both inter-node time delays and noise using digital logic elements on field-programmable gate arrays. We observe transients that last millions to billions of characteristic time scales and scale exponentially with the amount of time delays between nodes, a phenomenon known as super-transient scaling. We develop a hybrid model that includes time delays along network links and allows for stochastic variation in the delays. Using this model, we explain the observed super-transient scaling of both motifs and recreate the experimentally measured transient distributions.

  8. A Study on the Motif Pattern of Dark-Cloud Cover in the Securities

    Directory of Open Access Journals (Sweden)

    Long Jing

    2017-01-01

    Full Text Available Morphological analysis is the analysis and mining of the graphics formed of the securities price changes. Investors need to forecast the trend of future before buying and selling points, which can avoid great loss. Therefore, the analysis of motif pattern of K-line in the form of futures investment technology analysis is very significant. Based on the thoughts of short-term trend clustering, this paper proposes a method of detecting the motif pattern of Dark-Cloud Cover in stock time series by analysing stock historic data and K-line shape, in order to predict the stock market trends. And we prove the effectiveness and practicality of the method by a series of experimental analysis.

  9. Dystroglycan versatility in cell adhesion: a tale of multiple motifs

    Directory of Open Access Journals (Sweden)

    Winder Steve J

    2010-02-01

    Full Text Available Abstract Dystroglycan is a ubiquitously expressed heterodimeric adhesion receptor. The extracellular α-subunit makes connections with a number of laminin G domain ligands including laminins, agrin and perlecan in the extracellular matrix and the transmembrane β-subunit makes connections to the actin filament network via cytoskeletal linkers including dystrophin, utrophin, ezrin and plectin, depending on context. Originally discovered as part of the dystrophin glycoprotein complex of skeletal muscle, dystroglycan is an important adhesion molecule and signalling scaffold in a multitude of cell types and tissues and is involved in several diseases. Dystroglycan has emerged as a multifunctional adhesion platform with many interacting partners associating with its short unstructured cytoplasmic domain. Two particular hotspots are the cytoplasmic juxtamembrane region and at the very carboxy terminus of dystroglycan. Regions which between them have several overlapping functions: in the juxtamembrane region; a nuclear localisation signal, ezrin/radixin/moesin protein, rapsyn and ERK MAP Kinase binding function, and at the C terminus a regulatory tyrosine governing WW, SH2 and SH3 domain interactions. We will discuss the binding partners for these motifs and how their interactions and regulation can modulate the involvement of dystroglycan in a range of different adhesion structures and functions depending on context. Thus dystroglycan presents as a multifunctional scaffold involved in adhesion and adhesion-mediated signalling with its functions under exquisite spatio-temporal regulation.

  10. Peptomics, identification of novel cationic Arabidopsis peptides with conserved sequence motifs

    DEFF Research Database (Denmark)

    Olsen, Addie Nina; Mundy, John; Skriver, Karen

    2002-01-01

    Arabidopsis family of 34 genes. The predicted peptides are characterized by a conserved C-terminal sequence motif and additional primary structure conservation in a core region. The majority of these genes had not previously been annotated. A subset of the predicted peptides show high overall sequence...... similarity to Rapid Alkalinization Factor (RALF), a peptide isolated from tobacco. We therefore refer to this peptide family as RALFL for RALF-Like. RT-PCR analysis confirmed that several of the Arabidopsis genes are expressed and that their expression patterns vary. The identification of a large gene family...

  11. Design of potent inhibitors of human RAD51 recombinase based on BRC motifs of BRCA2 protein: modeling and experimental validation of a chimera peptide.

    KAUST Repository

    Nomme, Julian; Renodon-Corniè re, Axelle; Asanomi, Yuya; Sakaguchi, Kazuyasu; Stasiak, Alicja Z; Stasiak, Andrzej; Norden, Bengt; Tran, Vinh; Takahashi, Masayuki

    2010-01-01

    We have previously shown that a 28-amino acid peptide derived from the BRC4 motif of BRCA2 tumor suppressor inhibits selectively human RAD51 recombinase (HsRad51). With the aim of designing better inhibitors for cancer treatment, we combined an in silico docking approach with in vitro biochemical testing to construct a highly efficient chimera peptide from eight existing human BRC motifs. We built a molecular model of all BRC motifs complexed with HsRad51 based on the crystal structure of the BRC4 motif-HsRad51 complex, computed the interaction energy of each residue in each BRC motif, and selected the best amino acid residue at each binding position. This analysis enabled us to propose four amino acid substitutions in the BRC4 motif. Three of these increased the inhibitory effect in vitro, and this effect was found to be additive. We thus obtained a peptide that is about 10 times more efficient in inhibiting HsRad51-ssDNA complex formation than the original peptide.

  12. Design of potent inhibitors of human RAD51 recombinase based on BRC motifs of BRCA2 protein: modeling and experimental validation of a chimera peptide.

    KAUST Repository

    Nomme, Julian

    2010-08-01

    We have previously shown that a 28-amino acid peptide derived from the BRC4 motif of BRCA2 tumor suppressor inhibits selectively human RAD51 recombinase (HsRad51). With the aim of designing better inhibitors for cancer treatment, we combined an in silico docking approach with in vitro biochemical testing to construct a highly efficient chimera peptide from eight existing human BRC motifs. We built a molecular model of all BRC motifs complexed with HsRad51 based on the crystal structure of the BRC4 motif-HsRad51 complex, computed the interaction energy of each residue in each BRC motif, and selected the best amino acid residue at each binding position. This analysis enabled us to propose four amino acid substitutions in the BRC4 motif. Three of these increased the inhibitory effect in vitro, and this effect was found to be additive. We thus obtained a peptide that is about 10 times more efficient in inhibiting HsRad51-ssDNA complex formation than the original peptide.

  13. Advancement Flap for Treatment of Complex Cryptoglandular Anal Fistula: Prediction of Therapy Success or Failure Using Anamnestic and Clinical Parameters.

    Science.gov (United States)

    Boenicke, Lars; Karsten, Eduard; Zirngibl, Hubert; Ambe, Peter

    2017-09-01

    Multiple new procedures for treatment of complex anal fistula have been described in the past decades, but an ideal single technique has yet not been identified. Factors that predict the outcome are required to identify the best procedure for each individual patient. The aim of this study was to find those predictors for advancement flap at midterm follow-up. From 2012 to 2015 in a tertiary university clinic, all patients who underwent advancement flap for treatment of complex cryptoglandular fistula were prospectively enrolled. Pre- and postoperatively standardized anamnestic and clinical examinations were performed. Predictive factors for therapy failure were identified using univariate and multivariate analysis. Out of 65 patients, 61 (93%) completed all examinations and were included in the study. Therapy failure after a mean follow-up period of 25 months occurred in total n = 11 patients (18%). There was no significant disturbance of continence among the entire study cohort as shown by the incontinence score (preop 0.34 ± 0.91 pts., postop 0.37 ± 0.97 pts.; p = 0.59). Univariate analysis for risk factors for therapy failure revealed age (p = 0.004), history of surgical abscess drainage (p = 0.04), BMI (p = 0.002), suprasphincteric fistula (p = 0.019) and horseshoe abscess (p = 0.036) as independent parameters for therapy failure. During multivariate analysis, only history of surgical abscess drainage (OR = 8.09, p = 0.048, 95% CI 0.98-64.96), suprasphincteric fistula (OR = 6.83, p = 0.032, 95% CI 1.17-6.83) and BMI (OR = 1.23, p = 0.017, 95% CI 1.03-1.46) were independent parameters for therapy failure. Advancement flap for treatment of complex fistula is effective and has low risk of disturbed continence. BMI, suprasphincteric fistula and history of surgical abscess drainage are predictors for therapy failure.

  14. A Repeating Sulfated Galactan Motif Resuscitates Dormant Micrococcus luteus Bacteria.

    Science.gov (United States)

    Böttcher, Thomas; Szamosvári, Dávid; Clardy, Jon

    2018-07-01

    Only a small fraction of bacteria can autonomously initiate growth on agar plates. Nongrowing bacteria typically enter a metabolically inactive dormant state and require specific chemical trigger factors or signals to exit this state and to resume growth. Micrococcus luteus has become a model organism for this important yet poorly understood phenomenon. Only a few resuscitation signals have been described to date, and all of them are produced endogenously by bacterial species. We report the discovery of a novel type of resuscitation signal that allows M. luteus to grow on agar but not agarose plates. Fractionation of the agar polysaccharide complex and sulfation of agarose allowed us to identify the signal as highly sulfated saccharides found in agar or carrageenans. Purification of hydrolyzed κ-carrageenan ultimately led to the identification of the signal as a small fragment of a large linear polysaccharide, i.e., an oligosaccharide of five or more sugars with a repeating disaccharide motif containing d-galactose-4-sulfate (G4S) 1,4-linked to 3,6-anhydro-α-d-galactose (DA), G4S-(DA-G4S) n ≥2 IMPORTANCE Most environmental bacteria cannot initiate growth on agar plates, but they can flourish on the same plates once growth is initiated. While there are a number of names for and manifestations of this phenomenon, the underlying cause appears to be the requirement for a molecular signal indicating safe growing conditions. Micrococcus luteus has become a model organism for studying this growth initiation process, often called resuscitation, because of its apparent connection with the persistent or dormant form of Mycobacterium tuberculosis , an important human pathogen. In this report, we identify a highly sulfated saccharide from agar or carrageenans that robustly resuscitates dormant M. luteus on agarose plates. We identified and characterized the signal as a small repeating disaccharide motif. Our results indicate that signals inherent in or absent from the

  15. Prefrontal and parietal activity is modulated by the rule complexity of inductive reasoning and can be predicted by a cognitive model.

    Science.gov (United States)

    Jia, Xiuqin; Liang, Peipeng; Shi, Lin; Wang, Defeng; Li, Kuncheng

    2015-01-01

    In neuroimaging studies, increased task complexity can lead to increased activation in task-specific regions or to activation of additional regions. How the brain adapts to increased rule complexity during inductive reasoning remains unclear. In the current study, three types of problems were created: simple rule induction (i.e., SI, with rule complexity of 1), complex rule induction (i.e., CI, with rule complexity of 2), and perceptual control. Our findings revealed that increased activations accompany increased rule complexity in the right dorsal lateral prefrontal cortex (DLPFC) and medial posterior parietal cortex (precuneus). A cognitive model predicted both the behavioral and brain imaging results. The current findings suggest that neural activity in frontal and parietal regions is modulated by rule complexity, which may shed light on the neural mechanisms of inductive reasoning. Copyright © 2014. Published by Elsevier Ltd.

  16. Targeting functional motifs of a protein family

    Science.gov (United States)

    Bhadola, Pradeep; Deo, Nivedita

    2016-10-01

    The structural organization of a protein family is investigated by devising a method based on the random matrix theory (RMT), which uses the physiochemical properties of the amino acid with multiple sequence alignment. A graphical method to represent protein sequences using physiochemical properties is devised that gives a fast, easy, and informative way of comparing the evolutionary distances between protein sequences. A correlation matrix associated with each property is calculated, where the noise reduction and information filtering is done using RMT involving an ensemble of Wishart matrices. The analysis of the eigenvalue statistics of the correlation matrix for the β -lactamase family shows the universal features as observed in the Gaussian orthogonal ensemble (GOE). The property-based approach captures the short- as well as the long-range correlation (approximately following GOE) between the eigenvalues, whereas the previous approach (treating amino acids as characters) gives the usual short-range correlations, while the long-range correlations are the same as that of an uncorrelated series. The distribution of the eigenvector components for the eigenvalues outside the bulk (RMT bound) deviates significantly from RMT observations and contains important information about the system. The information content of each eigenvector of the correlation matrix is quantified by introducing an entropic estimate, which shows that for the β -lactamase family the smallest eigenvectors (low eigenmodes) are highly localized as well as informative. These small eigenvectors when processed gives clusters involving positions that have well-defined biological and structural importance matching with experiments. The approach is crucial for the recognition of structural motifs as shown in β -lactamase (and other families) and selectively identifies the important positions for targets to deactivate (activate) the enzymatic actions.

  17. ROMANIAN FOLKLORE MOTIFS IN FASHION DESIGN

    Directory of Open Access Journals (Sweden)

    MOCENCO Alexandra

    2014-05-01

    Full Text Available The traditional Romanian costume such as the entire popular art (architecture, woodcarvins, pottery etc. was born and lasted in our country since ancient times. Closely related to human existence, the traditional costume reflected over the years as reflected nowadays, the mentality and artistic conception of the people. Today the traditional Romanian costume became an inspiration source to the wholesale fashion production industry designers, both Romanian and international. Although the contemporary designers are working in accordance with a vision, using a wide area of styles, methods and current technology, they usually return to traditional techniques and ethnic folklore motifs, which converts and resize them, integrating them in their contemporary space. Adrian Oianu is a very appreciated Romanian designer who launched two collections inspired by his native’s country traditional costumes: “Suflecata pan’ la brau” (“Turned up ‘til the belt” and “Bucurie” (“Joy”. Dorin Negrau had as inspiration for his “Lost” collection the traditional costume from the Bihor region. Yves Saint Laurent had a collection inspired by the Romanian traditional flax blouses called “La blouse roumaine”. The paper presents the traditional Romanian values throw fashion collections. The research activity will create innovative concepts to support the garment industry in order to develop their own brand and to bring the design activities in Romania at an international level. The research was conducted during the initial stage of a project, financed through national founds, consisting in a documentary study on ethnographic characteristics of the popular costume from different regions of the country.

  18. Prediction of Increasing Production Activities using Combination of Query Aggregation on Complex Events Processing and Neural Network

    Directory of Open Access Journals (Sweden)

    Achmad Arwan

    2016-07-01

    from training process, the system will issue a signal to increase production, otherwise system will keep monitor the events. Experiment result shows that the accuracy of this method is 77% for 39 series of event streams.Keywords: complex event processing, event, neural networks, process, production increase prediction.

  19. Review article: The mountain motif in the plot of Matthew

    Directory of Open Access Journals (Sweden)

    Gert J. Volschenk

    2010-09-01

    Full Text Available This article reviewed T.L. Donaldson’s book, Jesus on the mountain: A study in Matthean theology, published in 1985 by JSOT Press, Sheffield, and focused on the mountain motif in the structure and plot of the Gospel of Matthew, in addition to the work of Donaldson on the mountain motif as a literary motif and as theological symbol. The mountain is a primary theological setting for Jesus’ ministry and thus is an important setting, serving as one of the literary devices by which Matthew structured and progressed his narrative. The Zion theological and eschatological significance and Second Temple Judaism serve as the historical and theological background for the mountain motif. The last mountain setting (Mt 28:16–20 is the culmination of the three theological themes in the plot of Matthew, namely Christology, ecclesiology and salvation history.

  20. Methods and statistics for combining motif match scores.

    Science.gov (United States)

    Bailey, T L; Gribskov, M

    1998-01-01

    Position-specific scoring matrices are useful for representing and searching for protein sequence motifs. A sequence family can often be described by a group of one or more motifs, and an effective search must combine the scores for matching a sequence to each of the motifs in the group. We describe three methods for combining match scores and estimating the statistical significance of the combined scores and evaluate the search quality (classification accuracy) and the accuracy of the estimate of statistical significance of each. The three methods are: 1) sum of scores, 2) sum of reduced variates, 3) product of score p-values. We show that method 3) is superior to the other two methods in both regards, and that combining motif scores indeed gives better search accuracy. The MAST sequence homology search algorithm utilizing the product of p-values scoring method is available for interactive use and downloading at URL http:/(/)www.sdsc.edu/MEME.

  1. DNA regulatory motif selection based on support vector machine ...

    African Journals Online (AJOL)

    ... machine (SVM) and its application in microarray experiment of Kashin-Beck disease. ... speed and amount of the corresponding mRNA in gene replication process. ... and revealed that some motifs may be related to the immune reactions.

  2. Comparing the Suitability of Autodock, Gold and Glide for the Docking and Predicting the Possible Targets of Ru(II-Based Complexes as Anticancer Agents

    Directory of Open Access Journals (Sweden)

    Adebayo A. Adeniyi

    2013-03-01

    Full Text Available In cancer chemotherapy, metal-based complexes have been recognized as the most promising means of inhibiting cancer growth due to the successful application of cis-platin and its derivatives above many of the existing organic anticancer agents. The limitations in their rational design can be traced to the complexity of the mechanism of their operations, lack of proper knowledge of their targets and lack of force fields in docking packages to appropriately define the metal centre of the organometallic complexes. In this paper, some of the promising anticancer complexes of Ru(II such as the rapta-based complexes formulated as [Ru(η6-p-cymeneL2(pta] and those with unusual ligands are considered. CatB and kinases which have been experimentally confirmed as possible targets of the complexes are also predicted by the three methods as one of the most targeted receptors while TopII and HDAC7 are predicted by two and one of the methods as best targets. The interesting features of the binding of the complexes show that some of the complexes preferentially target specific macromolecules than the others, which is an indication of their specificity and possibility of their therapeutic combination without severe side effects that may come from competition for the same target. Also, introduction of unusual ligands is found to significantly improve the activities of most of the complexes studied. Strong correlations are observed for the predicted binding sites and the orientation of the complexes within the binding site by the three methods of docking. However there are disparities in the ranking of the complexes by the three method of docking, especially that of Glide.

  3. Characterizing Motif Dynamics of Electric Brain Activity Using Symbolic Analysis

    Directory of Open Access Journals (Sweden)

    Massimiliano Zanin

    2014-10-01

    Full Text Available Motifs are small recurring circuits of interactions which constitute the backbone of networked systems. Characterizing motif dynamics is therefore key to understanding the functioning of such systems. Here we propose a method to define and quantify the temporal variability and time scales of electroencephalogram (EEG motifs of resting brain activity. Given a triplet of EEG sensors, links between them are calculated by means of linear correlation; each pattern of links (i.e., each motif is then associated to a symbol, and its appearance frequency is analyzed by means of Shannon entropy. Our results show that each motif becomes observable with different coupling thresholds and evolves at its own time scale, with fronto-temporal sensors emerging at high thresholds and changing at fast time scales, and parietal ones at low thresholds and changing at slower rates. Finally, while motif dynamics differed across individuals, for each subject, it showed robustness across experimental conditions, indicating that it could represent an individual dynamical signature.

  4. Discovering Motifs in Biological Sequences Using the Micron Automata Processor.

    Science.gov (United States)

    Roy, Indranil; Aluru, Srinivas

    2016-01-01

    Finding approximately conserved sequences, called motifs, across multiple DNA or protein sequences is an important problem in computational biology. In this paper, we consider the (l, d) motif search problem of identifying one or more motifs of length l present in at least q of the n given sequences, with each occurrence differing from the motif in at most d substitutions. The problem is known to be NP-complete, and the largest solved instance reported to date is (26,11). We propose a novel algorithm for the (l,d) motif search problem using streaming execution over a large set of non-deterministic finite automata (NFA). This solution is designed to take advantage of the micron automata processor, a new technology close to deployment that can simultaneously execute multiple NFA in parallel. We demonstrate the capability for solving much larger instances of the (l, d) motif search problem using the resources available within a single automata processor board, by estimating run-times for problem instances (39,18) and (40,17). The paper serves as a useful guide to solving problems using this new accelerator technology.

  5. PISMA: A Visual Representation of Motif Distribution in DNA Sequences

    Directory of Open Access Journals (Sweden)

    Rogelio Alcántara-Silva

    2017-03-01

    Full Text Available Background: Because the graphical presentation and analysis of motif distribution can provide insights for experimental hypothesis, PISMA aims at identifying motifs on DNA sequences, counting and showing them graphically. The motif length ranges from 2 to 10 bases, and the DNA sequences range up to 10 kb. The motif distribution is shown as a bar-code–like, as a gene-map–like, and as a transcript scheme. Results: We obtained graphical schemes of the CpG site distribution from 91 human papillomavirus genomes. Also, we present 2 analyses: one of DNA motifs associated with either methylation-resistant or methylation-sensitive CpG islands and another analysis of motifs associated with exosome RNA secretion. Availability and Implementation: PISMA is developed in Java; it is executable in any type of hardware and in diverse operating systems. PISMA is freely available to noncommercial users. The English version and the User Manual are provided in Supplementary Files 1 and 2, and a Spanish version is available at www.biomedicas.unam.mx/wp-content/software/pisma.zip and www.biomedicas.unam.mx/wp-content/pdf/manual/pisma.pdf .

  6. Accurate prediction of complex free surface flow around a high speed craft using a single-phase level set method

    Science.gov (United States)

    Broglia, Riccardo; Durante, Danilo

    2017-11-01

    This paper focuses on the analysis of a challenging free surface flow problem involving a surface vessel moving at high speeds, or planing. The investigation is performed using a general purpose high Reynolds free surface solver developed at CNR-INSEAN. The methodology is based on a second order finite volume discretization of the unsteady Reynolds-averaged Navier-Stokes equations (Di Mascio et al. in A second order Godunov—type scheme for naval hydrodynamics, Kluwer Academic/Plenum Publishers, Dordrecht, pp 253-261, 2001; Proceedings of 16th international offshore and polar engineering conference, San Francisco, CA, USA, 2006; J Mar Sci Technol 14:19-29, 2009); air/water interface dynamics is accurately modeled by a non standard level set approach (Di Mascio et al. in Comput Fluids 36(5):868-886, 2007a), known as the single-phase level set method. In this algorithm the governing equations are solved only in the water phase, whereas the numerical domain in the air phase is used for a suitable extension of the fluid dynamic variables. The level set function is used to track the free surface evolution; dynamic boundary conditions are enforced directly on the interface. This approach allows to accurately predict the evolution of the free surface even in the presence of violent breaking waves phenomena, maintaining the interface sharp, without any need to smear out the fluid properties across the two phases. This paper is aimed at the prediction of the complex free-surface flow field generated by a deep-V planing boat at medium and high Froude numbers (from 0.6 up to 1.2). In the present work, the planing hull is treated as a two-degree-of-freedom rigid object. Flow field is characterized by the presence of thin water sheets, several energetic breaking waves and plungings. The computational results include convergence of the trim angle, sinkage and resistance under grid refinement; high-quality experimental data are used for the purposes of validation, allowing to

  7. Faster exact Markovian probability functions for motif occurrences: a DFA-only approach.

    Science.gov (United States)

    Ribeca, Paolo; Raineri, Emanuele

    2008-12-15

    The computation of the statistical properties of motif occurrences has an obviously relevant application: patterns that are significantly over- or under-represented in genomes or proteins are interesting candidates for biological roles. However, the problem is computationally hard; as a result, virtually all the existing motif finders use fast but approximate scoring functions, in spite of the fact that they have been shown to produce systematically incorrect results. A few interesting exact approaches are known, but they are very slow and hence not practical in the case of realistic sequences. We give an exact solution, solely based on deterministic finite-state automata (DFA), to the problem of finding the whole relevant part of the probability distribution function of a simple-word motif in a homogeneous (biological) sequence. Out of that, the z-value can always be computed, while the P-value can be obtained either when it is not too extreme with respect to the number of floating-point digits available in the implementation, or when the number of pattern occurrences is moderately low. In particular, the time complexity of the algorithms for Markov models of moderate order (0 manage to obtain an algorithm which is both easily interpretable and efficient. This approach can be used for exact statistical studies of very long genomes and protein sequences, as we illustrate with some examples on the scale of the human genome.

  8. A Comparison Study for DNA Motif Modeling on Protein Binding Microarray

    KAUST Repository

    Wong, Ka-Chun; Li, Yue; Peng, Chengbin; Wong, Hau-San

    2015-01-01

    Transcription Factor Binding Sites (TFBSs) are relatively short (5-15 bp) and degenerate. Identifying them is a computationally challenging task. In particular, Protein Binding Microarray (PBM) is a high-throughput platform that can measure the DNA binding preference of a protein in a comprehensive and unbiased manner; for instance, a typical PBM experiment can measure binding signal intensities of a protein to all possible DNA k-mers (k=810). Since proteins can often bind to DNA with different binding intensities, one of the major challenges is to build motif models which can fully capture the quantitative binding affinity data. To learn DNA motif models from the non-convex objective function landscape, several optimization methods are compared and applied to the PBM motif model building problem. In particular, representative methods from different optimization paradigms have been chosen for modeling performance comparison on hundreds of PBM datasets. The results suggest that the multimodal optimization methods are very effective for capturing the binding preference information from PBM data. In particular, we observe a general performance improvement using di-nucleotide modeling over mono-nucleotide modeling. In addition, the models learned by the best-performing method are applied to two independent applications: PBM probe rotation testing and ChIP-Seq peak sequence prediction, demonstrating its biological applicability.

  9. A Comparison Study for DNA Motif Modeling on Protein Binding Microarray

    KAUST Repository

    Wong, Ka-Chun

    2015-06-11

    Transcription Factor Binding Sites (TFBSs) are relatively short (5-15 bp) and degenerate. Identifying them is a computationally challenging task. In particular, Protein Binding Microarray (PBM) is a high-throughput platform that can measure the DNA binding preference of a protein in a comprehensive and unbiased manner; for instance, a typical PBM experiment can measure binding signal intensities of a protein to all possible DNA k-mers (k=810). Since proteins can often bind to DNA with different binding intensities, one of the major challenges is to build motif models which can fully capture the quantitative binding affinity data. To learn DNA motif models from the non-convex objective function landscape, several optimization methods are compared and applied to the PBM motif model building problem. In particular, representative methods from different optimization paradigms have been chosen for modeling performance comparison on hundreds of PBM datasets. The results suggest that the multimodal optimization methods are very effective for capturing the binding preference information from PBM data. In particular, we observe a general performance improvement using di-nucleotide modeling over mono-nucleotide modeling. In addition, the models learned by the best-performing method are applied to two independent applications: PBM probe rotation testing and ChIP-Seq peak sequence prediction, demonstrating its biological applicability.

  10. Decadal predictions of Southern Ocean sea ice : testing different initialization methods with an Earth-system Model of Intermediate Complexity

    Science.gov (United States)

    Zunz, Violette; Goosse, Hugues; Dubinkina, Svetlana

    2013-04-01

    The sea ice extent in th