The roles of tertiary amine structure, background organic matter and chloramine species on NDMA formation.

Science.gov (United States)

Selbes, Meric; Kim, Daekyun; Ates, Nuray; Karanfil, Tanju

2013-02-01

N-nitrosodimethylamine (NDMA), a probable human carcinogen, is a disinfection by-product that has been detected in chloraminated and chlorinated drinking waters and wastewaters. Formation mechanisms and precursors of NDMA are still not well understood. The main objectives of this study were to systematically investigate (i) the effect of tertiary amine structure, (ii) the effect of background natural organic matter (NOM), and (iii) the roles of mono vs. dichloramine species on the NDMA formation. Dimethylamine (DMA) and 20 different tertiary aliphatic and aromatic amines were carefully examined based on their functional groups attached to the basic DMA structure. The wide range (0.02-83.9%) of observed NDMA yields indicated the importance of the structure of tertiary amines, and both stability and electron distribution of the leaving group of tertiary amines on NDMA formation. DMA associated with branched alkyl groups or benzyl like structures having only one carbon between the ring and DMA structure consistently gave higher NDMA yields. Compounds with electron withdrawing groups (EWG) reacted preferentially with monochloramine, whereas compounds with electron donating group (EDG) showed tendency to react with dichloramine to form NDMA. When the selected amines were present in NOM solutions, NDMA formation increased for compounds with EWG while decreased for compounds with EDG. This impact was attributed to the competitions between NOM and amines for chloramine species. The results provided additional information to the commonly accepted mechanism for NDMA formation including chloramine species reacting with tertiary amines and the role of the leaving group on overall NDMA conversion. Copyright © 2012 Elsevier Ltd. All rights reserved.

Ab-initio conformational epitope structure prediction using genetic algorithm and SVM for vaccine design.

Science.gov (United States)

Moghram, Basem Ameen; Nabil, Emad; Badr, Amr

2018-01-01

T-cell epitope structure identification is a significant challenging immunoinformatic problem within epitope-based vaccine design. Epitopes or antigenic peptides are a set of amino acids that bind with the Major Histocompatibility Complex (MHC) molecules. The aim of this process is presented by Antigen Presenting Cells to be inspected by T-cells. MHC-molecule-binding epitopes are responsible for triggering the immune response to antigens. The epitope's three-dimensional (3D) molecular structure (i.e., tertiary structure) reflects its proper function. Therefore, the identification of MHC class-II epitopes structure is a significant step towards epitope-based vaccine design and understanding of the immune system. In this paper, we propose a new technique using a Genetic Algorithm for Predicting the Epitope Structure (GAPES), to predict the structure of MHC class-II epitopes based on their sequence. The proposed Elitist-based genetic algorithm for predicting the epitope's tertiary structure is based on Ab-Initio Empirical Conformational Energy Program for Peptides (ECEPP) Force Field Model. The developed secondary structure prediction technique relies on Ramachandran Plot. We used two alignment algorithms: the ROSS alignment and TM-Score alignment. We applied four different alignment approaches to calculate the similarity scores of the dataset under test. We utilized the support vector machine (SVM) classifier as an evaluation of the prediction performance. The prediction accuracy and the Area Under Receiver Operating Characteristic (ROC) Curve (AUC) were calculated as measures of performance. The calculations are performed on twelve similarity-reduced datasets of the Immune Epitope Data Base (IEDB) and a large dataset of peptide-binding affinities to HLA-DRB1*0101. The results showed that GAPES was reliable and very accurate. We achieved an average prediction accuracy of 93.50% and an average AUC of 0.974 in the IEDB dataset. Also, we achieved an accuracy of 95

Automated and fast building of three-dimensional RNA structures.

Science.gov (United States)

Zhao, Yunjie; Huang, Yangyu; Gong, Zhou; Wang, Yanjie; Man, Jianfen; Xiao, Yi

2012-01-01

Building tertiary structures of non-coding RNA is required to understand their functions and design new molecules. Current algorithms of RNA tertiary structure prediction give satisfactory accuracy only for small size and simple topology and many of them need manual manipulation. Here, we present an automated and fast program, 3dRNA, for RNA tertiary structure prediction with reasonable accuracy for RNAs of larger size and complex topology.

Parallel protein secondary structure prediction based on neural networks.

Science.gov (United States)

Zhong, Wei; Altun, Gulsah; Tian, Xinmin; Harrison, Robert; Tai, Phang C; Pan, Yi

2004-01-01

Protein secondary structure prediction has a fundamental influence on today's bioinformatics research. In this work, binary and tertiary classifiers of protein secondary structure prediction are implemented on Denoeux belief neural network (DBNN) architecture. Hydrophobicity matrix, orthogonal matrix, BLOSUM62 and PSSM (position specific scoring matrix) are experimented separately as the encoding schemes for DBNN. The experimental results contribute to the design of new encoding schemes. New binary classifier for Helix versus not Helix ( approximately H) for DBNN produces prediction accuracy of 87% when PSSM is used for the input profile. The performance of DBNN binary classifier is comparable to other best prediction methods. The good test results for binary classifiers open a new approach for protein structure prediction with neural networks. Due to the time consuming task of training the neural networks, Pthread and OpenMP are employed to parallelize DBNN in the hyperthreading enabled Intel architecture. Speedup for 16 Pthreads is 4.9 and speedup for 16 OpenMP threads is 4 in the 4 processors shared memory architecture. Both speedup performance of OpenMP and Pthread is superior to that of other research. With the new parallel training algorithm, thousands of amino acids can be processed in reasonable amount of time. Our research also shows that hyperthreading technology for Intel architecture is efficient for parallel biological algorithms.

Tertiary lymphoid structures in cancer and beyond.

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Dieu-Nosjean, Marie-Caroline; Goc, Jérémy; Giraldo, Nicolas A; Sautès-Fridman, Catherine; Fridman, Wolf Herman

2014-11-01

Tertiary lymphoid structures (TLS) are ectopic lymphoid formations found in inflamed, infected, or tumoral tissues. They exhibit all the characteristics of structures in the lymph nodes (LN) associated with the generation of an adaptive immune response, including a T cell zone with mature dendritic cells (DC), a germinal center with follicular dendritic cells (FDC) and proliferating B cells, and high endothelial venules (HEV). In this review, we discuss evidence for the roles of TLS in chronic infection, autoimmunity, and cancer, and address the question of whether TLS present beneficial or deleterious effects in these contexts. We examine the relationship between TLS in tumors and patient prognosis, and discuss the potential role of TLS in building and/or maintaining local immune responses and how this understanding may guide therapeutic interventions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Dynamic response of tertiary systems in structures subjected to base excitation

International Nuclear Information System (INIS)

Hernried, A.G.; Kai-sing Lau

1988-01-01

The dynamic response of very lightweight equipment (tertiary subsystem) attached to light equipment (secondary subsystem) which in turn is attached to a heavier structure (primary subsystem) that is subjected to ground shock or earthquake excitation is investigated. Both the single-degree-of-freedom and multi-degree-of-freedom subsystem models are considered. The systems are damped as well as undamped, completely detuned (all natural frequencies of the subsystems well spaced), singly tuned (one natural frequency of each subsystem equal or close to one another), or multiply tuned (more than one natural frequency of the subsystems close to each other). Efficient techniques for the determination of the tertiary subsystem response that avoid a computationally intensive numerical integration of the combined system equations are presented. (author)

Optimal neural networks for protein-structure prediction

International Nuclear Information System (INIS)

Head-Gordon, T.; Stillinger, F.H.

1993-01-01

The successful application of neural-network algorithms for prediction of protein structure is stymied by three problem areas: the sparsity of the database of known protein structures, poorly devised network architectures which make the input-output mapping opaque, and a global optimization problem in the multiple-minima space of the network variables. We present a simplified polypeptide model residing in two dimensions with only two amino-acid types, A and B, which allows the determination of the global energy structure for all possible sequences of pentamer, hexamer, and heptamer lengths. This model simplicity allows us to compile a complete structural database and to devise neural networks that reproduce the tertiary structure of all sequences with absolute accuracy and with the smallest number of network variables. These optimal networks reveal that the three problem areas are convoluted, but that thoughtful network designs can actually deconvolute these detrimental traits to provide network algorithms that genuinely impact on the ability of the network to generalize or learn the desired mappings. Furthermore, the two-dimensional polypeptide model shows sufficient chemical complexity so that transfer of neural-network technology to more realistic three-dimensional proteins is evident

Base pair probability estimates improve the prediction accuracy of RNA non-canonical base pairs.

Directory of Open Access Journals (Sweden)

Michael F Sloma

2017-11-01

Full Text Available Prediction of RNA tertiary structure from sequence is an important problem, but generating accurate structure models for even short sequences remains difficult. Predictions of RNA tertiary structure tend to be least accurate in loop regions, where non-canonical pairs are important for determining the details of structure. Non-canonical pairs can be predicted using a knowledge-based model of structure that scores nucleotide cyclic motifs, or NCMs. In this work, a partition function algorithm is introduced that allows the estimation of base pairing probabilities for both canonical and non-canonical interactions. Pairs that are predicted to be probable are more likely to be found in the true structure than pairs of lower probability. Pair probability estimates can be further improved by predicting the structure conserved across multiple homologous sequences using the TurboFold algorithm. These pairing probabilities, used in concert with prior knowledge of the canonical secondary structure, allow accurate inference of non-canonical pairs, an important step towards accurate prediction of the full tertiary structure. Software to predict non-canonical base pairs and pairing probabilities is now provided as part of the RNAstructure software package.

Base pair probability estimates improve the prediction accuracy of RNA non-canonical base pairs.

Science.gov (United States)

Sloma, Michael F; Mathews, David H

2017-11-01

Prediction of RNA tertiary structure from sequence is an important problem, but generating accurate structure models for even short sequences remains difficult. Predictions of RNA tertiary structure tend to be least accurate in loop regions, where non-canonical pairs are important for determining the details of structure. Non-canonical pairs can be predicted using a knowledge-based model of structure that scores nucleotide cyclic motifs, or NCMs. In this work, a partition function algorithm is introduced that allows the estimation of base pairing probabilities for both canonical and non-canonical interactions. Pairs that are predicted to be probable are more likely to be found in the true structure than pairs of lower probability. Pair probability estimates can be further improved by predicting the structure conserved across multiple homologous sequences using the TurboFold algorithm. These pairing probabilities, used in concert with prior knowledge of the canonical secondary structure, allow accurate inference of non-canonical pairs, an important step towards accurate prediction of the full tertiary structure. Software to predict non-canonical base pairs and pairing probabilities is now provided as part of the RNAstructure software package.

Stereoinversion of tertiary alcohols to tertiary-alkyl isonitriles and amines.

Science.gov (United States)

Pronin, Sergey V; Reiher, Christopher A; Shenvi, Ryan A

2013-09-12

The SN2 reaction (bimolecular nucleophilic substitution) is a well-known chemical transformation that can be used to join two smaller molecules together into a larger molecule or to exchange one functional group for another. The SN2 reaction proceeds in a very predictable manner: substitution occurs with inversion of stereochemistry, resulting from the 'backside attack' of the electrophilic carbon by the nucleophile. A significant limitation of the SN2 reaction is its intolerance for tertiary carbon atoms: whereas primary and secondary alcohols are viable precursor substrates, tertiary alcohols and their derivatives usually either fail to react or produce stereochemical mixtures of products. Here we report the stereochemical inversion of chiral tertiary alcohols with a nitrogenous nucleophile facilitated by a Lewis-acid-catalysed solvolysis. The method is chemoselective against secondary and primary alcohols, thereby complementing the selectivity of the SN2 reaction. Furthermore, this method for carbon-nitrogen bond formation mimics a putative biosynthetic step in the synthesis of marine terpenoids and enables their preparation from the corresponding terrestrial terpenes. We expect that the general attributes of the methodology will allow chiral tertiary alcohols to be considered viable substrates for stereoinversion reactions.

A Deep Learning Network Approach to ab initio Protein Secondary Structure Prediction.

Science.gov (United States)

Spencer, Matt; Eickholt, Jesse; Jianlin Cheng

2015-01-01

Ab initio protein secondary structure (SS) predictions are utilized to generate tertiary structure predictions, which are increasingly demanded due to the rapid discovery of proteins. Although recent developments have slightly exceeded previous methods of SS prediction, accuracy has stagnated around 80 percent and many wonder if prediction cannot be advanced beyond this ceiling. Disciplines that have traditionally employed neural networks are experimenting with novel deep learning techniques in attempts to stimulate progress. Since neural networks have historically played an important role in SS prediction, we wanted to determine whether deep learning could contribute to the advancement of this field as well. We developed an SS predictor that makes use of the position-specific scoring matrix generated by PSI-BLAST and deep learning network architectures, which we call DNSS. Graphical processing units and CUDA software optimize the deep network architecture and efficiently train the deep networks. Optimal parameters for the training process were determined, and a workflow comprising three separately trained deep networks was constructed in order to make refined predictions. This deep learning network approach was used to predict SS for a fully independent test dataset of 198 proteins, achieving a Q3 accuracy of 80.7 percent and a Sov accuracy of 74.2 percent.

Depression and catastrophizing predict suicidal ideation in tertiary care patients with interstitial cystitis/bladder pain syndrome

DEFF Research Database (Denmark)

Tripp, Dean A; Nickel, J Curtis; Krsmanovic, Adrijana

2016-01-01

is the first to implicate multiple psychosocial risk factors over and above IC/BPS-specific symptoms and patient pain experience in SI in women with IC/BPS. Depression in particular is uniquely important in predicting suicidality. These results support a multidisciplinary, proactive approach to IC......Introduction: We sought to evaluate psychosocial factors as predictors of suicidal ideation (SI) in a tertiary care outpatient sample of women suffering from interstitial cystitis/bladder pain syndrome (IC/BPS). Methods: The patients are women managed at tertiary care centres (n=190). Controls were...... of psychosocial variables on patient SI. Results: Compared to 6% in healthy controls, 23% of patients endorsed SI in the past two weeks. Correlations between SI, depression, and catastrophizing across controls and cases show that for controls, SI is associated with greater pain (0.31; pdepression only...

Prediction of Protein Structural Class Based on Gapped-Dipeptides and a Recursive Feature Selection Approach

Directory of Open Access Journals (Sweden)

Taigang Liu

2015-12-01

Full Text Available The prior knowledge of protein structural class may offer useful clues on understanding its functionality as well as its tertiary structure. Though various significant efforts have been made to find a fast and effective computational approach to address this problem, it is still a challenging topic in the field of bioinformatics. The position-specific score matrix (PSSM profile has been shown to provide a useful source of information for improving the prediction performance of protein structural class. However, this information has not been adequately explored. To this end, in this study, we present a feature extraction technique which is based on gapped-dipeptides composition computed directly from PSSM. Then, a careful feature selection technique is performed based on support vector machine-recursive feature elimination (SVM-RFE. These optimal features are selected to construct a final predictor. The results of jackknife tests on four working datasets show that our method obtains satisfactory prediction accuracies by extracting features solely based on PSSM and could serve as a very promising tool to predict protein structural class.

PCI-SS: MISO dynamic nonlinear protein secondary structure prediction

Directory of Open Access Journals (Sweden)

Aboul-Magd Mohammed O

2009-07-01

protein sequence data and also to encode the resulting structure prediction in a machine-readable format. To our knowledge, this represents the only publicly available SOAP-interface for a protein secondary structure prediction service with published WSDL interface definition. Conclusion Relative to the 9 contemporary methods included in the comparison cascaded PCI classifiers perform well, however PCI finds greatest application as a consensus classifier. When PCI is used to combine a sequence-to-structure PCI-based classifier with the current leading ANN-based method, PSIPRED, the overall error rate (Q3 is maintained while the rate of occurrence of a particularly detrimental error is reduced by up to 25%. This improvement in BAD score, combined with the machine-readable SOAP web service interface makes PCI-SS particularly useful for inclusion in a tertiary structure prediction pipeline.

Measuring case-mix complexity of tertiary care hospitals using DRGs.

Science.gov (United States)

Park, Hayoung; Shin, Youngsoo

2004-02-01

The objectives of the study were to develop a model that measures and evaluates case-mix complexity of tertiary care hospitals, and to examine the characteristics of such a model. Physician panels defined three classes of case complexity and assigned disease categories represented by Adjacent Diagnosis Related Groups (ADRGs) to one of three case complexity classes. Three types of scores, indicating proportions of inpatients in each case complexity class standardized by the proportions at the national level, were defined to measure the case-mix complexity of a hospital. Discharge information for about 10% of inpatient episodes at 85 hospitals with bed size larger than 400 and their input structure and research and education activity were used to evaluate the case-mix complexity model. Results show its power to predict hospitals with the expected functions of tertiary care hospitals, i.e. resource intensive care, expensive input structure, and high levels of research and education activities.

Fast protein tertiary structure retrieval based on global surface shape similarity.

Science.gov (United States)

Sael, Lee; Li, Bin; La, David; Fang, Yi; Ramani, Karthik; Rustamov, Raif; Kihara, Daisuke

2008-09-01

Characterization and identification of similar tertiary structure of proteins provides rich information for investigating function and evolution. The importance of structure similarity searches is increasing as structure databases continue to expand, partly due to the structural genomics projects. A crucial drawback of conventional protein structure comparison methods, which compare structures by their main-chain orientation or the spatial arrangement of secondary structure, is that a database search is too slow to be done in real-time. Here we introduce a global surface shape representation by three-dimensional (3D) Zernike descriptors, which represent a protein structure compactly as a series expansion of 3D functions. With this simplified representation, the search speed against a few thousand structures takes less than a minute. To investigate the agreement between surface representation defined by 3D Zernike descriptor and conventional main-chain based representation, a benchmark was performed against a protein classification generated by the combinatorial extension algorithm. Despite the different representation, 3D Zernike descriptor retrieved proteins of the same conformation defined by combinatorial extension in 89.6% of the cases within the top five closest structures. The real-time protein structure search by 3D Zernike descriptor will open up new possibility of large-scale global and local protein surface shape comparison. 2008 Wiley-Liss, Inc.

Structural prediction in aphasia

Directory of Open Access Journals (Sweden)

Tessa Warren

2015-05-01

Full Text Available There is considerable evidence that young healthy comprehenders predict the structure of upcoming material, and that their processing is facilitated when they encounter material matching those predictions (e.g., Staub & Clifton, 2006; Yoshida, Dickey & Sturt, 2013. However, less is known about structural prediction in aphasia. There is evidence that lexical prediction may be spared in aphasia (Dickey et al., 2014; Love & Webb, 1977; cf. Mack et al, 2013. However, predictive mechanisms supporting facilitated lexical access may not necessarily support structural facilitation. Given that many people with aphasia (PWA exhibit syntactic deficits (e.g. Goodglass, 1993, PWA with such impairments may not engage in structural prediction. However, recent evidence suggests that some PWA may indeed predict upcoming structure (Hanne, Burchert, De Bleser, & Vashishth, 2015. Hanne et al. tracked the eyes of PWA (n=8 with sentence-comprehension deficits while they listened to reversible subject-verb-object (SVO and object-verb-subject (OVS sentences in German, in a sentence-picture matching task. Hanne et al. manipulated case and number marking to disambiguate the sentences’ structure. Gazes to an OVS or SVO picture during the unfolding of a sentence were assumed to indicate prediction of the structure congruent with that picture. According to this measure, the PWA’s structural prediction was impaired compared to controls, but they did successfully predict upcoming structure when morphosyntactic cues were strong and unambiguous. Hanne et al.’s visual-world evidence is suggestive, but their forced-choice sentence-picture matching task places tight constraints on possible structural predictions. Clearer evidence of structural prediction would come from paradigms where the content of upcoming material is not as constrained. The current study used self-paced reading study to examine structural prediction among PWA in less constrained contexts. PWA (n=17 who

Electrostatics, structure prediction, and the energy landscapes for protein folding and binding.

Science.gov (United States)

Tsai, Min-Yeh; Zheng, Weihua; Balamurugan, D; Schafer, Nicholas P; Kim, Bobby L; Cheung, Margaret S; Wolynes, Peter G

2016-01-01

While being long in range and therefore weakly specific, electrostatic interactions are able to modulate the stability and folding landscapes of some proteins. The relevance of electrostatic forces for steering the docking of proteins to each other is widely acknowledged, however, the role of electrostatics in establishing specifically funneled landscapes and their relevance for protein structure prediction are still not clear. By introducing Debye-Hückel potentials that mimic long-range electrostatic forces into the Associative memory, Water mediated, Structure, and Energy Model (AWSEM), a transferable protein model capable of predicting tertiary structures, we assess the effects of electrostatics on the landscapes of thirteen monomeric proteins and four dimers. For the monomers, we find that adding electrostatic interactions does not improve structure prediction. Simulations of ribosomal protein S6 show, however, that folding stability depends monotonically on electrostatic strength. The trend in predicted melting temperatures of the S6 variants agrees with experimental observations. Electrostatic effects can play a range of roles in binding. The binding of the protein complex KIX-pKID is largely assisted by electrostatic interactions, which provide direct charge-charge stabilization of the native state and contribute to the funneling of the binding landscape. In contrast, for several other proteins, including the DNA-binding protein FIS, electrostatics causes frustration in the DNA-binding region, which favors its binding with DNA but not with its protein partner. This study highlights the importance of long-range electrostatics in functional responses to problems where proteins interact with their charged partners, such as DNA, RNA, as well as membranes. © 2015 The Protein Society.

CNNH_PSS: protein 8-class secondary structure prediction by convolutional neural network with highway.

Science.gov (United States)

Zhou, Jiyun; Wang, Hongpeng; Zhao, Zhishan; Xu, Ruifeng; Lu, Qin

2018-05-08

Protein secondary structure is the three dimensional form of local segments of proteins and its prediction is an important problem in protein tertiary structure prediction. Developing computational approaches for protein secondary structure prediction is becoming increasingly urgent. We present a novel deep learning based model, referred to as CNNH_PSS, by using multi-scale CNN with highway. In CNNH_PSS, any two neighbor convolutional layers have a highway to deliver information from current layer to the output of the next one to keep local contexts. As lower layers extract local context while higher layers extract long-range interdependencies, the highways between neighbor layers allow CNNH_PSS to have ability to extract both local contexts and long-range interdependencies. We evaluate CNNH_PSS on two commonly used datasets: CB6133 and CB513. CNNH_PSS outperforms the multi-scale CNN without highway by at least 0.010 Q8 accuracy and also performs better than CNF, DeepCNF and SSpro8, which cannot extract long-range interdependencies, by at least 0.020 Q8 accuracy, demonstrating that both local contexts and long-range interdependencies are indeed useful for prediction. Furthermore, CNNH_PSS also performs better than GSM and DCRNN which need extra complex model to extract long-range interdependencies. It demonstrates that CNNH_PSS not only cost less computer resource, but also achieves better predicting performance. CNNH_PSS have ability to extracts both local contexts and long-range interdependencies by combing multi-scale CNN and highway network. The evaluations on common datasets and comparisons with state-of-the-art methods indicate that CNNH_PSS is an useful and efficient tool for protein secondary structure prediction.

Do health complaints in adolescence negatively predict the chance of entering tertiary education in young adulthood?

Science.gov (United States)

Låftman, Sara B; Magnusson, Charlotta

2017-12-01

Self-reported psychological and psychosomatic health complaints, such as nervousness, sadness, headache and stomach-ache, are common among adolescents, particularly among girls, and studies suggest that the prevalence has risen among adolescent girls during the last few decades. However, only a limited number of studies have investigated the potential long-term consequences of such health complaints. The aim of the current study was to assess whether psychological and psychosomatic health complaints in adolescence predict the chance of entering tertiary education in young adulthood among women and men. The data used are from the Swedish Young-LNU, which is based on a nationally representative sample with self-reported survey information from adolescents aged 10-18 years in 2000 and from the same individuals at ages 20-28 in 2010 ( n=783). Information was also collected from parents and from official registers. Linear probability models showed that self-reported psychological complaints in adolescence were associated with a lower chance of having entered tertiary education 10 years later. This association was accounted for by differences in grade point average (GPA), suggesting that GPA may mediate the association between psychological complaints and later education. The pattern was similar for both genders. Furthermore, among men, psychosomatic complaints in adolescence were significantly associated with a lower likelihood of having entered tertiary education 10 years later when adjusting for GPA and social class in adolescence. A similar but non-significant tendency was found among women. The findings suggest that health complaints in adolescence may have long-term consequences in terms of lower educational attainment.

Formation mechanism of NDMA from ranitidine, trimethylamine, and other tertiary amines during chloramination: a computational study.

Science.gov (United States)

Liu, Yong Dong; Selbes, Meric; Zeng, Chengchu; Zhong, Rugang; Karanfil, Tanju

2014-01-01

Chloramination of drinking waters has been associated with N-nitrosodimethylamine (NDMA) formation as a disinfection byproduct. NDMA is classified as a probable carcinogen and thus its formation during chloramination has recently become the focus of considerable research interest. In this study, the formation mechanisms of NDMA from ranitidine and trimethylamine (TMA), as models of tertiary amines, during chloramination were investigated by using density functional theory (DFT). A new four-step formation pathway of NDMA was proposed involving nucleophilic substitution by chloramine, oxidation, and dehydration followed by nitrosation. The results suggested that nitrosation reaction is the rate-limiting step and determines the NDMA yield for tertiary amines. When 45 other tertiary amines were examined, the proposed mechanism was found to be more applicable to aromatic tertiary amines, and there may be still some additional factors or pathways that need to be considered for aliphatic tertiary amines. The heterolytic ONN(Me)2-R(+) bond dissociation energy to release NDMA and carbocation R(+) was found to be a criterion for evaluating the reactivity of aromatic tertiary amines. A structure-activity study indicates that tertiary amines with benzyl, aromatic heterocyclic ring, and diene-substituted methenyl adjacent to the DMA moiety are potentially significant NDMA precursors. The findings of this study are helpful for understanding NDMA formation mechanism and predicting NDMA yield of a precursor.

Linguistic Structure Prediction

CERN Document Server

Smith, Noah A

2011-01-01

A major part of natural language processing now depends on the use of text data to build linguistic analyzers. We consider statistical, computational approaches to modeling linguistic structure. We seek to unify across many approaches and many kinds of linguistic structures. Assuming a basic understanding of natural language processing and/or machine learning, we seek to bridge the gap between the two fields. Approaches to decoding (i.e., carrying out linguistic structure prediction) and supervised and unsupervised learning of models that predict discrete structures as outputs are the focus. W

ConStruct: Improved construction of RNA consensus structures

Directory of Open Access Journals (Sweden)

Steger Gerhard

2008-04-01

Full Text Available Abstract Background Aligning homologous non-coding RNAs (ncRNAs correctly in terms of sequence and structure is an unresolved problem, due to both mathematical complexity and imperfect scoring functions. High quality alignments, however, are a prerequisite for most consensus structure prediction approaches, homology searches, and tools for phylogeny inference. Automatically created ncRNA alignments often need manual corrections, yet this manual refinement is tedious and error-prone. Results We present an extended version of CONSTRUCT, a semi-automatic, graphical tool suitable for creating RNA alignments correct in terms of both consensus sequence and consensus structure. To this purpose CONSTRUCT combines sequence alignment, thermodynamic data and various measures of covariation. One important feature is that the user is guided during the alignment correction step by a consensus dotplot, which displays all thermodynamically optimal base pairs and the corresponding covariation. Once the initial alignment is corrected, optimal and suboptimal secondary structures as well as tertiary interaction can be predicted. We demonstrate CONSTRUCT's ability to guide the user in correcting an initial alignment, and show an example for optimal secondary consensus structure prediction on very hard to align SECIS elements. Moreover we use CONSTRUCT to predict tertiary interactions from sequences of the internal ribosome entry site of CrP-like viruses. In addition we show that alignments specifically designed for benchmarking can be easily be optimized using CONSTRUCT, although they share very little sequence identity. Conclusion CONSTRUCT's graphical interface allows for an easy alignment correction based on and guided by predicted and known structural constraints. It combines several algorithms for prediction of secondary consensus structure and even tertiary interactions. The CONSTRUCT package can be downloaded from the URL listed in the Availability and

Improving search for low energy protein structures with an iterative niche genetic algorithm

DEFF Research Database (Denmark)

Helles, Glennie

2010-01-01

In attempts to predict the tertiary structure of proteins we use almost exclusively metaheuristics. However, despite known differences in performance of metaheuristics for different problems, the effect of the choice of metaheuristic has received precious little attention in this field. Particula......In attempts to predict the tertiary structure of proteins we use almost exclusively metaheuristics. However, despite known differences in performance of metaheuristics for different problems, the effect of the choice of metaheuristic has received precious little attention in this field...

Tertiary classes–after Chern-Simons theory

Indian Academy of Sciences (India)

J.N. Iyer Institute of Mathematical Sciences Chennai, India

2013-11-08

Nov 8, 2013 ... Euler characteristic class. In early twentieth century, the notion of local product structure, i.e. fiber spaces and their generalizations appeared, in the study of topological spaces (with additional structures). J.N. Iyer. IMSc, Chennai. Tertiary classes–after Chern-Simons theory ...

Factors predicting quality of work life among nurses in tertiary-level hospitals, Bangladesh.

Science.gov (United States)

Akter, N; Akkadechanunt, T; Chontawan, R; Klunklin, A

2018-06-01

This study examined the level of quality of work life and predictability of years of education, monthly income, years of experience, job stress, organizational commitment and work environment on quality of work life among nurses in tertiary-level hospitals in the People's Republic of Bangladesh. There is an acute shortage of nurses worldwide including Bangladesh. Quality of work life is important for quality of patient care and nurse retention. Nurses in Bangladesh are fighting to provide quality care for emerging health problems for the achievement of sustainable development goals. We collected data from 288 randomly selected registered nurses, from six tertiary-level hospitals. All nurses were requested to fill questionnaire consisted of Demographic Data Sheet, Quality of Nursing Work Life Survey, Expanded Nursing Stress Scale, Questionnaire of Organizational Commitment and Practice Environment Scale of the Nursing Work Index. Data were analysed by descriptive statistics and multiple regression. The quality of work life as perceived by nurses in Bangladesh was at moderate level. Monthly income was found as the best predictor followed by work environment, organizational commitment and job stress. A higher monthly income helps nurses to fulfil their personal needs; positive work environment helps to provide quality care to the patients. Quality of work life and predictors measured by self-report only may not reflect the original picture of the quality of work life among nurses. Findings provide information for nursing and health policymakers to develop policies to improve quality of work life among nurses that can contribute to quality of nursing care. This includes the working environment, commitment to the organization and measures to reduce job stress. © 2017 International Council of Nurses.

Neural Networks for protein Structure Prediction

DEFF Research Database (Denmark)

Bohr, Henrik

1998-01-01

This is a review about neural network applications in bioinformatics. Especially the applications to protein structure prediction, e.g. prediction of secondary structures, prediction of surface structure, fold class recognition and prediction of the 3-dimensional structure of protein backbones...

[Decomposition model of energy-related carbon emissions in tertiary industry for China].

Science.gov (United States)

Lu, Yuan-Qing; Shi, Jun

2012-07-01

Tertiary industry has been developed in recent years. And it is very important to find the factors influenced the energy-related carbon emissions in tertiary industry. A decomposition model of energy-related carbon emissions for China is set up by adopting logarithmic mean weight Divisia method based on the identity of carbon emissions. The model is adopted to analyze the influence of energy structure, energy efficiency, tertiary industry structure and economic output to energy-related carbon emissions in China from 2000 to 2009. Results show that the contribution rate of economic output and energy structure to energy-related carbon emissions increases year by year. Either is the contribution rate of energy efficiency or the tertiary industry restraining to energy-related carbon emissions. However, the restrain effect is weakening.

Calcium-induced tertiary structure modifications of endo-B-1,3-glucanase form Pyrococcus furiosus in 7.9 M guanidinium chloride

NARCIS (Netherlands)

Chiaraluce, R.; Gianese, G.; Angelaccio, S.; Florio, R.; Lieshout, van J.F.T.; Oost, van der J.; Consalvi, V.

2005-01-01

The family 16 endo-b-1,3 glucanase from the extremophilic archaeon Pyrococcus furiosus is a laminarinase, which in 7.9 M GdmCl (guanidinium chloride) maintains a significant amount of tertiary structure without any change of secondary structure. The addition of calcium to the enzyme in 7.9 M GdmCl

Three-residue turns in alpha/beta-peptides and their application in the design of tertiary structures.

Science.gov (United States)

Sharma, Gangavaram V M; Nagendar, Pendem; Ramakrishna, Kallaganti V S; Chandramouli, Nagula; Choudhary, Madavi; Kunwar, Ajit C

2008-06-02

A new three-residue turn was serendipitously discovered in alpha/beta hybrid peptides derived from alternating C-linked carbo-beta-amino acids (beta-Caa) and L-Ala residues. The three-residue beta-alpha-beta turn at the C termini, nucleated by a helix at the N termini, resulted in helix-turn (HT) supersecondary structures in these peptides. The turn in the HT motif is stabilized by two H bonds-CO(i-2)-NH(i), with a seven-membered pseudoring (gamma turn) in the backward direction, and NH(i-2)-CO(i), with a 13-membered pseudoring in the forward direction (i being the last residue)--at the C termini. The study was extended to generalize the new three-residue turn (beta-alpha-beta) by using different alpha- and beta-amino acids. Furthermore, the HT motifs were efficiently converted, by an extension with helical oligomers at the C termini, into peptides with novel helix-turn-helix (HTH) tertiary structures. However, this resulted in the destabilization of the beta-alpha-beta turn with the concomitant nucleation of another three-residue turn, alpha-beta-beta, which is stabilized by 11- and 15-membered bifurcated H bonds. Extensive NMR spectroscopic studies were carried out to delineate the secondary and tertiary structures in these peptides, which are further supported by molecular dynamics (MD) investigations.

A folding algorithm for extended RNA secondary structures.

Science.gov (United States)

Höner zu Siederdissen, Christian; Bernhart, Stephan H; Stadler, Peter F; Hofacker, Ivo L

2011-07-01

RNA secondary structure contains many non-canonical base pairs of different pair families. Successful prediction of these structural features leads to improved secondary structures with applications in tertiary structure prediction and simultaneous folding and alignment. We present a theoretical model capturing both RNA pair families and extended secondary structure motifs with shared nucleotides using 2-diagrams. We accompany this model with a number of programs for parameter optimization and structure prediction. All sources (optimization routines, RNA folding, RNA evaluation, extended secondary structure visualization) are published under the GPLv3 and available at www.tbi.univie.ac.at/software/rnawolf/.

Prediction of molecular crystal structures

International Nuclear Information System (INIS)

Beyer, Theresa

2001-01-01

The ab initio prediction of molecular crystal structures is a scientific challenge. Reliability of first-principle prediction calculations would show a fundamental understanding of crystallisation. Crystal structure prediction is also of considerable practical importance as different crystalline arrangements of the same molecule in the solid state (polymorphs)are likely to have different physical properties. A method of crystal structure prediction based on lattice energy minimisation has been developed in this work. The choice of the intermolecular potential and of the molecular model is crucial for the results of such studies and both of these criteria have been investigated. An empirical atom-atom repulsion-dispersion potential for carboxylic acids has been derived and applied in a crystal structure prediction study of formic, benzoic and the polymorphic system of tetrolic acid. As many experimental crystal structure determinations at different temperatures are available for the polymorphic system of paracetamol (acetaminophen), the influence of the variations of the molecular model on the crystal structure lattice energy minima, has also been studied. The general problem of prediction methods based on the assumption that the experimental thermodynamically stable polymorph corresponds to the global lattice energy minimum, is that more hypothetical low lattice energy structures are found within a few kJ mol -1 of the global minimum than are likely to be experimentally observed polymorphs. This is illustrated by the results for molecule I, 3-oxabicyclo(3.2.0)hepta-1,4-diene, studied for the first international blindtest for small organic crystal structures organised by the Cambridge Crystallographic Data Centre (CCDC) in May 1999. To reduce the number of predicted polymorphs, additional factors to thermodynamic criteria have to be considered. Therefore the elastic constants and vapour growth morphologies have been calculated for the lowest lattice energy

Prediction of molecular crystal structures

Energy Technology Data Exchange (ETDEWEB)

Beyer, Theresa

2001-07-01

The ab initio prediction of molecular crystal structures is a scientific challenge. Reliability of first-principle prediction calculations would show a fundamental understanding of crystallisation. Crystal structure prediction is also of considerable practical importance as different crystalline arrangements of the same molecule in the solid state (polymorphs)are likely to have different physical properties. A method of crystal structure prediction based on lattice energy minimisation has been developed in this work. The choice of the intermolecular potential and of the molecular model is crucial for the results of such studies and both of these criteria have been investigated. An empirical atom-atom repulsion-dispersion potential for carboxylic acids has been derived and applied in a crystal structure prediction study of formic, benzoic and the polymorphic system of tetrolic acid. As many experimental crystal structure determinations at different temperatures are available for the polymorphic system of paracetamol (acetaminophen), the influence of the variations of the molecular model on the crystal structure lattice energy minima, has also been studied. The general problem of prediction methods based on the assumption that the experimental thermodynamically stable polymorph corresponds to the global lattice energy minimum, is that more hypothetical low lattice energy structures are found within a few kJ mol{sup -1} of the global minimum than are likely to be experimentally observed polymorphs. This is illustrated by the results for molecule I, 3-oxabicyclo(3.2.0)hepta-1,4-diene, studied for the first international blindtest for small organic crystal structures organised by the Cambridge Crystallographic Data Centre (CCDC) in May 1999. To reduce the number of predicted polymorphs, additional factors to thermodynamic criteria have to be considered. Therefore the elastic constants and vapour growth morphologies have been calculated for the lowest lattice energy

SECTORAL ANALYSIS: GROWTH ACCOUNTING OF TERTIARY INDUSTRIES

Directory of Open Access Journals (Sweden)

Yahya Z. ALSHEHHI

2017-08-01

Full Text Available The tertiary sector is one of the modern styles of economic systems in view of the share it occupies in the field of production as well as employment occupied share. Hence, just like other lands, the UAE, witnessed an economic structural change similar to developed and developing nations, where the tertiary industries contributed 55.4% in 2015 to total country’s income. The empirical study aimed to analyze the contribution portion of growth in the tertiary industries through using the growth accounting framework in time-series from 1990 to 2015. The empirical study found that most of the industries contributed significantly to the growth of the tertiary sector. The contribution shares of growth due to labor and capital varied among industries. The main observed results show that there was a vice versa relationship between TFP performance and the size of labor, where the TFP positively corresponded with the decline in the size of labor specifically from 2010-2015.

Prediction of RNA secondary structures: from theory to models and real molecules

International Nuclear Information System (INIS)

Schuster, Peter

2006-01-01

empirical parameters can be determined and by principal deficiencies, for example by the lack of energy contributions resulting from tertiary interactions. In addition, native structures may be determined by folding kinetics rather than by thermodynamics. We address the first problem by considering base pair probabilities or base pairing entropies, which are derived from the partition function of conformations. A high base pair probability corresponding to a low pairing entropy is taken as an indicator of a high reliability of prediction. Pseudoknots are discussed as an example of a tertiary interaction that is highly important for RNA function. Moreover, pseudoknot formation is readily incorporated into structure prediction algorithms. Some examples of experimental data on RNA secondary structures that are readily explained using the landscape concept are presented. They deal with (i) properties of RNA molecules with random sequences, (ii) RNA molecules from restricted alphabets, (iii) existence of neutral networks, (iv) shape space covering, (v) riboswitches and (vi) evolution of non-coding RNAs as an example of evolution restricted to neutral networks

Hydrogen bond indices and tertiary structure of yeast tRNA sup(Phe)

International Nuclear Information System (INIS)

Giambiagi, M.S. de; Giambiagi, M.; Esquivel, D.M.S.

1982-01-01

The rigidity and stability of the tertiary structure of yeast tRNA sup(Phe) is related to a bond index employed in an IEHT calculation. The index permits a quantitative estimate of the electronic cloud along the hydrogen bond, having thus an appealing physical meaning. The results indicate that Hoogsteen-type bonds have, as expected, greater electronic population than Watson-Crick type ones. Other non-Watson-Crick pairings, the wobble pair and G 15 -C 48 , exhibit high values of the index for the NH...O bond. In the triples, the electronic density of the hydrogen bridges does not weaken, comparing it with the one of the pairs involved. Contour density maps are shown and dipolar moments of pairs and triples are qualitatively discussed. (Author) [pt

RNA-SSPT: RNA Secondary Structure Prediction Tools.

Science.gov (United States)

Ahmad, Freed; Mahboob, Shahid; Gulzar, Tahsin; Din, Salah U; Hanif, Tanzeela; Ahmad, Hifza; Afzal, Muhammad

2013-01-01

The prediction of RNA structure is useful for understanding evolution for both in silico and in vitro studies. Physical methods like NMR studies to predict RNA secondary structure are expensive and difficult. Computational RNA secondary structure prediction is easier. Comparative sequence analysis provides the best solution. But secondary structure prediction of a single RNA sequence is challenging. RNA-SSPT is a tool that computationally predicts secondary structure of a single RNA sequence. Most of the RNA secondary structure prediction tools do not allow pseudoknots in the structure or are unable to locate them. Nussinov dynamic programming algorithm has been implemented in RNA-SSPT. The current studies shows only energetically most favorable secondary structure is required and the algorithm modification is also available that produces base pairs to lower the total free energy of the secondary structure. For visualization of RNA secondary structure, NAVIEW in C language is used and modified in C# for tool requirement. RNA-SSPT is built in C# using Dot Net 2.0 in Microsoft Visual Studio 2005 Professional edition. The accuracy of RNA-SSPT is tested in terms of Sensitivity and Positive Predicted Value. It is a tool which serves both secondary structure prediction and secondary structure visualization purposes.

Evaluation of the suitability of free-energy minimization using nearest-neighbor energy parameters for RNA secondary structure prediction

Directory of Open Access Journals (Sweden)

Cobaugh Christian W

2004-08-01

Full Text Available Abstract Background A detailed understanding of an RNA's correct secondary and tertiary structure is crucial to understanding its function and mechanism in the cell. Free energy minimization with energy parameters based on the nearest-neighbor model and comparative analysis are the primary methods for predicting an RNA's secondary structure from its sequence. Version 3.1 of Mfold has been available since 1999. This version contains an expanded sequence dependence of energy parameters and the ability to incorporate coaxial stacking into free energy calculations. We test Mfold 3.1 by performing the largest and most phylogenetically diverse comparison of rRNA and tRNA structures predicted by comparative analysis and Mfold, and we use the results of our tests on 16S and 23S rRNA sequences to assess the improvement between Mfold 2.3 and Mfold 3.1. Results The average prediction accuracy for a 16S or 23S rRNA sequence with Mfold 3.1 is 41%, while the prediction accuracies for the majority of 16S and 23S rRNA structures tested are between 20% and 60%, with some having less than 20% prediction accuracy. The average prediction accuracy was 71% for 5S rRNA and 69% for tRNA. The majority of the 5S rRNA and tRNA sequences have prediction accuracies greater than 60%. The prediction accuracy of 16S rRNA base-pairs decreases exponentially as the number of nucleotides intervening between the 5' and 3' halves of the base-pair increases. Conclusion Our analysis indicates that the current set of nearest-neighbor energy parameters in conjunction with the Mfold folding algorithm are unable to consistently and reliably predict an RNA's correct secondary structure. For 16S or 23S rRNA structure prediction, Mfold 3.1 offers little improvement over Mfold 2.3. However, the nearest-neighbor energy parameters do work well for shorter RNA sequences such as tRNA or 5S rRNA, or for larger rRNAs when the contact distance between the base-pairs is less than 100 nucleotides.

Epitope-Targeting of Tertiary Protein Structure Enables Target-Guided Synthesis of a Potent in Cell Inhibitor of Botulinum Neurotoxin**

OpenAIRE

Farrow, Blake; Wong, Michelle; Malette, Jacquie; Lai, Bert; Deyle, Kaycie M.; Das, Samir; Nag, Arundhati; Agnew, Heather D.; Heath, James R.

2015-01-01

Botulinum neurotoxin (BoNT) serotype A is the most lethal known toxin and has an occluded structure, which prevents direct inhibition of its active site before it enters the cytosol. Target-guided synthesis by in situ click chemistry is combined with synthetic epitope targeting to exploit the tertiary structure of the BoNT protein as a landscape for assembling a competitive inhibitor. A substrate-mimicking peptide macrocycle is used as a direct inhibitor of BoNT. An epitope-targeting in situ ...

Predicting RNA Structure Using Mutual Information

DEFF Research Database (Denmark)

Freyhult, E.; Moulton, V.; Gardner, P. P.

2005-01-01

, to display and predict conserved RNA secondary structure (including pseudoknots) from an alignment. Results: We show that MIfold can be used to predict simple pseudoknots, and that the performance can be adjusted to make it either more sensitive or more selective. We also demonstrate that the overall...... package. Conclusion: MIfold provides a useful supplementary tool to programs such as RNA Structure Logo, RNAalifold and COVE, and should be useful for automatically generating structural predictions for databases such as Rfam. Availability: MIfold is freely available from http......Background: With the ever-increasing number of sequenced RNAs and the establishment of new RNA databases, such as the Comparative RNA Web Site and Rfam, there is a growing need for accurately and automatically predicting RNA structures from multiple alignments. Since RNA secondary structure...

The IntFOLD server: an integrated web resource for protein fold recognition, 3D model quality assessment, intrinsic disorder prediction, domain prediction and ligand binding site prediction.

Science.gov (United States)

Roche, Daniel B; Buenavista, Maria T; Tetchner, Stuart J; McGuffin, Liam J

2011-07-01

The IntFOLD server is a novel independent server that integrates several cutting edge methods for the prediction of structure and function from sequence. Our guiding principles behind the server development were as follows: (i) to provide a simple unified resource that makes our prediction software accessible to all and (ii) to produce integrated output for predictions that can be easily interpreted. The output for predictions is presented as a simple table that summarizes all results graphically via plots and annotated 3D models. The raw machine readable data files for each set of predictions are also provided for developers, which comply with the Critical Assessment of Methods for Protein Structure Prediction (CASP) data standards. The server comprises an integrated suite of five novel methods: nFOLD4, for tertiary structure prediction; ModFOLD 3.0, for model quality assessment; DISOclust 2.0, for disorder prediction; DomFOLD 2.0 for domain prediction; and FunFOLD 1.0, for ligand binding site prediction. Predictions from the IntFOLD server were found to be competitive in several categories in the recent CASP9 experiment. The IntFOLD server is available at the following web site: http://www.reading.ac.uk/bioinf/IntFOLD/.

Predictive value of Borrelia burgdorferi IgG antibody levels in patients referred to a tertiary Lyme centre.

Science.gov (United States)

Zwerink, M; Zomer, T P; van Kooten, B; Blaauw, G; van Bemmel, T; van Hees, B C; Vermeeren, Y M; Landman, G W

2018-03-01

A two-step testing strategy is recommended in serological testing for Lyme borreliosis; positive and indeterminate enzyme-linked immunosorbent assay (ELISA) results are confirmed with immunoblots. Several ELISAs quantify the concentration of antibodies tested, however, no recommendation exists for an upper cut-off value at which an IgG ELISA is sufficient and the immunoblot can be omitted. The study objective was to determine at which IgG antibody level an immunoblot does not have any additional predictive value compared to ELISA results. Data of adult patients who visited a tertiary Lyme centre between 2008 and 2014 were analysed. Both an ELISA (Enzygnost Lyme link VlsE IgG) and immunoblot (recomLine blot Borrelia) were performed. Clinical data were extracted from the patient's digital medical record. Positive predictive values (PPVs) for either previous or active infection with Borrelia burgdorferi s.l. were calculated for different cut-off ELISA IgG antibody levels where the immunoblot was regarded as reference test. In total, 1454 patients were included. According to the two-step test strategy, 486 (33%), 69 (5%) and 899 (62%) patients had positive, indeterminate and negative Borrelia IgG serology, respectively. At IgG levels of 500 IU/ml and higher, all immunoblots were positive, resulting in a 100% PPV (95% CI: 97.0-100). At IgG levels of 200 IU/ml and higher, the PPV was 99.3% (95% CI: 97.4-99.8). In conclusion, at IgG levels of 200 IU/ml and higher, an ELISA was sufficient to detect antibodies to Borrelia burgdorferi s.l. At those IgG levels, a confirmatory immunoblot may be omitted in patients referred to a tertiary Lyme centre. Before these results can be implemented in routine diagnosis of Lyme borreliosis, confirmation of the results is necessary in other patient populations and using other quantitative ELISAs and immunoblots. Copyright © 2017 Elsevier GmbH. All rights reserved.

Improving the accuracy of protein secondary structure prediction using structural alignment

Directory of Open Access Journals (Sweden)

Gallin Warren J

2006-06-01

Full Text Available Abstract Background The accuracy of protein secondary structure prediction has steadily improved over the past 30 years. Now many secondary structure prediction methods routinely achieve an accuracy (Q3 of about 75%. We believe this accuracy could be further improved by including structure (as opposed to sequence database comparisons as part of the prediction process. Indeed, given the large size of the Protein Data Bank (>35,000 sequences, the probability of a newly identified sequence having a structural homologue is actually quite high. Results We have developed a method that performs structure-based sequence alignments as part of the secondary structure prediction process. By mapping the structure of a known homologue (sequence ID >25% onto the query protein's sequence, it is possible to predict at least a portion of that query protein's secondary structure. By integrating this structural alignment approach with conventional (sequence-based secondary structure methods and then combining it with a "jury-of-experts" system to generate a consensus result, it is possible to attain very high prediction accuracy. Using a sequence-unique test set of 1644 proteins from EVA, this new method achieves an average Q3 score of 81.3%. Extensive testing indicates this is approximately 4–5% better than any other method currently available. Assessments using non sequence-unique test sets (typical of those used in proteome annotation or structural genomics indicate that this new method can achieve a Q3 score approaching 88%. Conclusion By using both sequence and structure databases and by exploiting the latest techniques in machine learning it is possible to routinely predict protein secondary structure with an accuracy well above 80%. A program and web server, called PROTEUS, that performs these secondary structure predictions is accessible at http://wishart.biology.ualberta.ca/proteus. For high throughput or batch sequence analyses, the PROTEUS programs

Ensemble-based prediction of RNA secondary structures.

Science.gov (United States)

Aghaeepour, Nima; Hoos, Holger H

2013-04-24

Accurate structure prediction methods play an important role for the understanding of RNA function. Energy-based, pseudoknot-free secondary structure prediction is one of the most widely used and versatile approaches, and improved methods for this task have received much attention over the past five years. Despite the impressive progress that as been achieved in this area, existing evaluations of the prediction accuracy achieved by various algorithms do not provide a comprehensive, statistically sound assessment. Furthermore, while there is increasing evidence that no prediction algorithm consistently outperforms all others, no work has been done to exploit the complementary strengths of multiple approaches. In this work, we present two contributions to the area of RNA secondary structure prediction. Firstly, we use state-of-the-art, resampling-based statistical methods together with a previously published and increasingly widely used dataset of high-quality RNA structures to conduct a comprehensive evaluation of existing RNA secondary structure prediction procedures. The results from this evaluation clarify the performance relationship between ten well-known existing energy-based pseudoknot-free RNA secondary structure prediction methods and clearly demonstrate the progress that has been achieved in recent years. Secondly, we introduce AveRNA, a generic and powerful method for combining a set of existing secondary structure prediction procedures into an ensemble-based method that achieves significantly higher prediction accuracies than obtained from any of its component procedures. Our new, ensemble-based method, AveRNA, improves the state of the art for energy-based, pseudoknot-free RNA secondary structure prediction by exploiting the complementary strengths of multiple existing prediction procedures, as demonstrated using a state-of-the-art statistical resampling approach. In addition, AveRNA allows an intuitive and effective control of the trade-off between

Quantitative structure-activity relationships for predicting potential ecological hazard of organic chemicals for use in regulatory risk assessments.

Science.gov (United States)

Comber, Mike H I; Walker, John D; Watts, Chris; Hermens, Joop

2003-08-01

The use of quantitative structure-activity relationships (QSARs) for deriving the predicted no-effect concentration of discrete organic chemicals for the purposes of conducting a regulatory risk assessment in Europe and the United States is described. In the United States, under the Toxic Substances Control Act (TSCA), the TSCA Interagency Testing Committee and the U.S. Environmental Protection Agency (U.S. EPA) use SARs to estimate the hazards of existing and new chemicals. Within the Existing Substances Regulation in Europe, QSARs may be used for data evaluation, test strategy indications, and the identification and filling of data gaps. To illustrate where and when QSARs may be useful and when their use is more problematic, an example, methyl tertiary-butyl ether (MTBE), is given and the predicted and experimental data are compared. Improvements needed for new QSARs and tools for developing and using QSARs are discussed.

Applications of contact predictions to structural biology

Directory of Open Access Journals (Sweden)

Felix Simkovic

2017-05-01

Full Text Available Evolutionary pressure on residue interactions, intramolecular or intermolecular, that are important for protein structure or function can lead to covariance between the two positions. Recent methodological advances allow much more accurate contact predictions to be derived from this evolutionary covariance signal. The practical application of contact predictions has largely been confined to structural bioinformatics, yet, as this work seeks to demonstrate, the data can be of enormous value to the structural biologist working in X-ray crystallography, cryo-EM or NMR. Integrative structural bioinformatics packages such as Rosetta can already exploit contact predictions in a variety of ways. The contribution of contact predictions begins at construct design, where structural domains may need to be expressed separately and contact predictions can help to predict domain limits. Structure solution by molecular replacement (MR benefits from contact predictions in diverse ways: in difficult cases, more accurate search models can be constructed using ab initio modelling when predictions are available, while intermolecular contact predictions can allow the construction of larger, oligomeric search models. Furthermore, MR using supersecondary motifs or large-scale screens against the PDB can exploit information, such as the parallel or antiparallel nature of any β-strand pairing in the target, that can be inferred from contact predictions. Contact information will be particularly valuable in the determination of lower resolution structures by helping to assign sequence register. In large complexes, contact information may allow the identity of a protein responsible for a certain region of density to be determined and then assist in the orientation of an available model within that density. In NMR, predicted contacts can provide long-range information to extend the upper size limit of the technique in a manner analogous but complementary to experimental

Influence Factor of Tertiary Students’ Employability Awareness Adjust Industry 4.0

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Chun-Mei Chou

2017-09-01

Full Text Available This study aims to analyze the correlation (N=621 among tertiary students’ career planning, erecruiting adoption acceptance, and employability awareness in Taiwan. Tertiary students’ perceived career planning includes four factors, namely, self-appraisal, job expectancy, goal selection, and problem solving. E-recruiting adoption acceptance includes four factors, namely, playfulness, ease of use, effectiveness, and usefulness. Employability awareness includes four factors, namely, personal adaptability, employability ambition, career identity, and labour market. Participants responded to a 5-point Likert-type scale for each factor. Analysis was conducted using the structural equation modeling (SEM, and a good model fit was found for both the measurement and structural models. Research findings demonstrate that tertiary students’ career planning significantly and directly influences employability awareness. Career planning significantly and indirectly influences employability awareness by e-recruiting adoption acceptance. Tertiary students’ career planning and e-recruiting adoption acceptance fit the influence model and empirical data of employability awareness. Implications of this study, including the value of student self-assessment of their skills and utility of the e-recruiting to underpin personal career development planning and inform graduate recruitment processes, are discussed and recommendations made.

Tertiary Students ’ Entrepreneurship Learning Socialization : Factor Analysis and Structural Equation Modeling

Directory of Open Access Journals (Sweden)

Chun- Mei Chou

2015-09-01

Full Text Available This study examines 728 tertiary students’ entrepreneurship learning socialization and its influencing factors to serve as a school reference for the development of internship and entrepreneurship education. The results show that students’ internship experience has a significant direct effect on entrepreneurship learning socialization, and entrepreneurship intention has a significant effect on entrepreneurship learning socialization through internship experience. The influence pattern and empirical data of entrepreneurship intention and internship experience on entrepreneurship learning socialization has a good fit. This paper gives an insight from Taiwan tertiary institutions about entrepreneurial learning socialization of students and contributions to them. We describe the development of the influencing factors, discuss its implications for entrepreneurship and internship education, and finally offer suggestions for further entrepreneurship education development.

Spatio-temporal observations of the tertiary ozone maximum

Directory of Open Access Journals (Sweden)

V. F. Sofieva

2009-07-01

Full Text Available We present spatio-temporal distributions of the tertiary ozone maximum (TOM, based on GOMOS (Global Ozone Monitoring by Occultation of Stars ozone measurements in 2002–2006. The tertiary ozone maximum is typically observed in the high-latitude winter mesosphere at an altitude of ~72 km. Although the explanation for this phenomenon has been found recently – low concentrations of odd-hydrogen cause the subsequent decrease in odd-oxygen losses – models have had significant deviations from existing observations until recently. Good coverage of polar night regions by GOMOS data has allowed for the first time to obtain spatial and temporal observational distributions of night-time ozone mixing ratio in the mesosphere.

The distributions obtained from GOMOS data have specific features, which are variable from year to year. In particular, due to a long lifetime of ozone in polar night conditions, the downward transport of polar air by the meridional circulation is clearly observed in the tertiary ozone maximum time series. Although the maximum tertiary ozone mixing ratio is achieved close to the polar night terminator (as predicted by the theory, TOM can be observed also at very high latitudes, not only in the beginning and at the end, but also in the middle of winter. We have compared the observational spatio-temporal distributions of the tertiary ozone maximum with that obtained using WACCM (Whole Atmosphere Community Climate Model and found that the specific features are reproduced satisfactorily by the model.

Since ozone in the mesosphere is very sensitive to HO_x concentrations, energetic particle precipitation can significantly modify the shape of the ozone profiles. In particular, GOMOS observations have shown that the tertiary ozone maximum was temporarily destroyed during the January 2005 and December 2006 solar proton events as a result of the HO_x enhancement from the increased ionization.

Defining proximity relationships in the tertiary structure of the dopamine transporter. Identification of a conserved glutamic acid as a third coordinate in the endogenous Zn(2+)-binding site

DEFF Research Database (Denmark)

Løland, Claus Juul; Norregaard, L; Gether, U

1999-01-01

, high affinity Zn(2+)-binding site. To achieve further insight into the tertiary organization of hDAT, we set out to identify additional residues involved in Zn(2+) binding and subsequently to engineer artificial Zn(2+)-binding sites. Ten aspartic acids and glutamic acids, predicted...

Algorithms for Protein Structure Prediction

DEFF Research Database (Denmark)

Paluszewski, Martin

-trace. Here we present three different approaches for reconstruction of C-traces from predictable measures. In our first approach [63, 62], the C-trace is positioned on a lattice and a tabu-search algorithm is applied to find minimum energy structures. The energy function is based on half-sphere-exposure (HSE......) is more robust than standard Monte Carlo search. In the second approach for reconstruction of C-traces, an exact branch and bound algorithm has been developed [67, 65]. The model is discrete and makes use of secondary structure predictions, HSE, CN and radius of gyration. We show how to compute good lower...... bounds for partial structures very fast. Using these lower bounds, we are able to find global minimum structures in a huge conformational space in reasonable time. We show that many of these global minimum structures are of good quality compared to the native structure. Our branch and bound algorithm...

Prediction of long-term creep curves

International Nuclear Information System (INIS)

Oikawa, Hiroshi; Maruyama, Kouichi

1992-01-01

This paper aims at discussing how to predict long-term irradiation enhanced creep properties from short-term tests. The predictive method based on the θ concept was examined by using creep data of ferritic steels. The method was successful in predicting creep curves including the tertiary creep stage as well as rupture lifetimes. Some material constants involved in the method are insensitive to the irradiation environment, and their values obtained in thermal creep are applicable to irradiation enhanced creep. The creep mechanisms of most engineering materials definitely change at the athermal yield stress in the non-creep regime. One should be aware that short-term tests must be carried out at stresses lower than the athermal yield stress in order to predict the creep behavior of structural components correctly. (orig.)

Critical Features of Fragment Libraries for Protein Structure Prediction.

Science.gov (United States)

Trevizani, Raphael; Custódio, Fábio Lima; Dos Santos, Karina Baptista; Dardenne, Laurent Emmanuel

2017-01-01

The use of fragment libraries is a popular approach among protein structure prediction methods and has proven to substantially improve the quality of predicted structures. However, some vital aspects of a fragment library that influence the accuracy of modeling a native structure remain to be determined. This study investigates some of these features. Particularly, we analyze the effect of using secondary structure prediction guiding fragments selection, different fragments sizes and the effect of structural clustering of fragments within libraries. To have a clearer view of how these factors affect protein structure prediction, we isolated the process of model building by fragment assembly from some common limitations associated with prediction methods, e.g., imprecise energy functions and optimization algorithms, by employing an exact structure-based objective function under a greedy algorithm. Our results indicate that shorter fragments reproduce the native structure more accurately than the longer. Libraries composed of multiple fragment lengths generate even better structures, where longer fragments show to be more useful at the beginning of the simulations. The use of many different fragment sizes shows little improvement when compared to predictions carried out with libraries that comprise only three different fragment sizes. Models obtained from libraries built using only sequence similarity are, on average, better than those built with a secondary structure prediction bias. However, we found that the use of secondary structure prediction allows greater reduction of the search space, which is invaluable for prediction methods. The results of this study can be critical guidelines for the use of fragment libraries in protein structure prediction.

Protein Structure Prediction by Protein Threading

Science.gov (United States)

Xu, Ying; Liu, Zhijie; Cai, Liming; Xu, Dong

The seminal work of Bowie, Lüthy, and Eisenberg (Bowie et al., 1991) on "the inverse protein folding problem" laid the foundation of protein structure prediction by protein threading. By using simple measures for fitness of different amino acid types to local structural environments defined in terms of solvent accessibility and protein secondary structure, the authors derived a simple and yet profoundly novel approach to assessing if a protein sequence fits well with a given protein structural fold. Their follow-up work (Elofsson et al., 1996; Fischer and Eisenberg, 1996; Fischer et al., 1996a,b) and the work by Jones, Taylor, and Thornton (Jones et al., 1992) on protein fold recognition led to the development of a new brand of powerful tools for protein structure prediction, which we now term "protein threading." These computational tools have played a key role in extending the utility of all the experimentally solved structures by X-ray crystallography and nuclear magnetic resonance (NMR), providing structural models and functional predictions for many of the proteins encoded in the hundreds of genomes that have been sequenced up to now.

Secondary and tertiary hyperparathyroidism.

Science.gov (United States)

Jamal, Sophie A; Miller, Paul D

2013-01-01

We reviewed the etiology and management of secondary and tertiary hyperparathyroidism. Secondary hyperparathyroidism is characterized by an increase in parathyroid hormone (PTH) that is appropriate and in response to a stimulus, most commonly low serum calcium. In secondary hyperparathyroidism, the serum calcium is normal and the PTH level is elevated. Tertiary hyperparathyroidism is characterized by excessive secretion of PTH after longstanding secondary hyperparathyroidism, in which hypercalcemia has ensued. Tertiary hyperparathyroidism typically occurs in men and women with chronic kidney disease usually after kidney transplant. The etiology and treatment of secondary hyperparathyroidism is relatively straightforward whereas data on the management of tertiary hyperparathyroidism is limited to a few small trials with short follow-up. Copyright © 2013 The International Society for Clinical Densitometry. Published by Elsevier Inc. All rights reserved.

Facilitating RNA structure prediction with microarrays.

Science.gov (United States)

Kierzek, Elzbieta; Kierzek, Ryszard; Turner, Douglas H; Catrina, Irina E

2006-01-17

Determining RNA secondary structure is important for understanding structure-function relationships and identifying potential drug targets. This paper reports the use of microarrays with heptamer 2'-O-methyl oligoribonucleotides to probe the secondary structure of an RNA and thereby improve the prediction of that secondary structure. When experimental constraints from hybridization results are added to a free-energy minimization algorithm, the prediction of the secondary structure of Escherichia coli 5S rRNA improves from 27 to 92% of the known canonical base pairs. Optimization of buffer conditions for hybridization and application of 2'-O-methyl-2-thiouridine to enhance binding and improve discrimination between AU and GU pairs are also described. The results suggest that probing RNA with oligonucleotide microarrays can facilitate determination of secondary structure.

Antibody structural modeling with prediction of immunoglobulin structure (PIGS)

DEFF Research Database (Denmark)

Marcatili, Paolo; Olimpieri, Pier Paolo; Chailyan, Anna

2014-01-01

Antibodies (or immunoglobulins) are crucial for defending organisms from pathogens, but they are also key players in many medical, diagnostic and biotechnological applications. The ability to predict their structure and the specific residues involved in antigen recognition has several useful...... applications in all of these areas. Over the years, we have developed or collaborated in developing a strategy that enables researchers to predict the 3D structure of antibodies with a very satisfactory accuracy. The strategy is completely automated and extremely fast, requiring only a few minutes (∼10 min...... on average) to build a structural model of an antibody. It is based on the concept of canonical structures of antibody loops and on our understanding of the way light and heavy chains pack together....

PSPP: a protein structure prediction pipeline for computing clusters.

Directory of Open Access Journals (Sweden)

Michael S Lee

2009-07-01

Full Text Available Protein structures are critical for understanding the mechanisms of biological systems and, subsequently, for drug and vaccine design. Unfortunately, protein sequence data exceed structural data by a factor of more than 200 to 1. This gap can be partially filled by using computational protein structure prediction. While structure prediction Web servers are a notable option, they often restrict the number of sequence queries and/or provide a limited set of prediction methodologies. Therefore, we present a standalone protein structure prediction software package suitable for high-throughput structural genomic applications that performs all three classes of prediction methodologies: comparative modeling, fold recognition, and ab initio. This software can be deployed on a user's own high-performance computing cluster.The pipeline consists of a Perl core that integrates more than 20 individual software packages and databases, most of which are freely available from other research laboratories. The query protein sequences are first divided into domains either by domain boundary recognition or Bayesian statistics. The structures of the individual domains are then predicted using template-based modeling or ab initio modeling. The predicted models are scored with a statistical potential and an all-atom force field. The top-scoring ab initio models are annotated by structural comparison against the Structural Classification of Proteins (SCOP fold database. Furthermore, secondary structure, solvent accessibility, transmembrane helices, and structural disorder are predicted. The results are generated in text, tab-delimited, and hypertext markup language (HTML formats. So far, the pipeline has been used to study viral and bacterial proteomes.The standalone pipeline that we introduce here, unlike protein structure prediction Web servers, allows users to devote their own computing assets to process a potentially unlimited number of queries as well as perform

Tertiary Education and the Crisis of Public Finance

Directory of Open Access Journals (Sweden)

Milos Maryska

2012-04-01

Full Text Available Turbulent economic environment after overwhelming the last crisis period is typical for present days as well as permanent increasing dependability of all our activities on information and communication technology (ICT. Although the global economic crisis was the reason for disinvestment into ICT in 2009 there is expected that ICT will generate almost 5.8 million new jobs in Europe till year 2013 and they have to be saturated also by adequately qualified ICT specialists.This contribution presents the research in the progress focused on the tertiary education system in the Czech Republic. We are predicting trends in education and especially in ICT education in Europe and in the Czech Republic as well for next ten years. We can expect that future ten years period will be critical not only for the Czech tertiary education system, but also for the Czech Republic because number of ICT students will be decreasing and number of ICT specialist demanded by labor market will be increasing. From macroeconomic point of view we can expect that also state subventions into state governed tertiary education system will decrease in the whole Europe.Some recommendations, proposals and forecasts for further development of education system are presented at the end of this contribution.

RNAstructure: software for RNA secondary structure prediction and analysis.

Science.gov (United States)

Reuter, Jessica S; Mathews, David H

2010-03-15

To understand an RNA sequence's mechanism of action, the structure must be known. Furthermore, target RNA structure is an important consideration in the design of small interfering RNAs and antisense DNA oligonucleotides. RNA secondary structure prediction, using thermodynamics, can be used to develop hypotheses about the structure of an RNA sequence. RNAstructure is a software package for RNA secondary structure prediction and analysis. It uses thermodynamics and utilizes the most recent set of nearest neighbor parameters from the Turner group. It includes methods for secondary structure prediction (using several algorithms), prediction of base pair probabilities, bimolecular structure prediction, and prediction of a structure common to two sequences. This contribution describes new extensions to the package, including a library of C++ classes for incorporation into other programs, a user-friendly graphical user interface written in JAVA, and new Unix-style text interfaces. The original graphical user interface for Microsoft Windows is still maintained. The extensions to RNAstructure serve to make RNA secondary structure prediction user-friendly. The package is available for download from the Mathews lab homepage at http://rna.urmc.rochester.edu/RNAstructure.html.

Antibody structural modeling with prediction of immunoglobulin structure (PIGS)

KAUST Repository

Marcatili, Paolo

2014-11-06

© 2014 Nature America, Inc. All rights reserved. Antibodies (or immunoglobulins) are crucial for defending organisms from pathogens, but they are also key players in many medical, diagnostic and biotechnological applications. The ability to predict their structure and the specific residues involved in antigen recognition has several useful applications in all of these areas. Over the years, we have developed or collaborated in developing a strategy that enables researchers to predict the 3D structure of antibodies with a very satisfactory accuracy. The strategy is completely automated and extremely fast, requiring only a few minutes (~10 min on average) to build a structural model of an antibody. It is based on the concept of canonical structures of antibody loops and on our understanding of the way light and heavy chains pack together.

Evaluation of CASP8 model quality predictions

KAUST Repository

Cozzetto, Domenico

2009-01-01

The model quality assessment problem consists in the a priori estimation of the overall and per-residue accuracy of protein structure predictions. Over the past years, a number of methods have been developed to address this issue and CASP established a prediction category to evaluate their performance in 2006. In 2008 the experiment was repeated and its results are reported here. Participants were invited to infer the correctness of the protein models submitted by the registered automatic servers. Estimates could apply to both whole models and individual amino acids. Groups involved in the tertiary structure prediction categories were also asked to assign local error estimates to each predicted residue in their own models and their results are also discussed here. The correlation between the predicted and observed correctness measures was the basis of the assessment of the results. We observe that consensus-based methods still perform significantly better than those accepting single models, similarly to what was concluded in the previous edition of the experiment. © 2009 WILEY-LISS, INC.

Relevance of Donation to Special Federal Tertiary Institution ...

African Journals Online (AJOL)

While structured and open-ended interview and relevant documents, including gift and donation files, acquisition records and library accession registers were used to collect data for the study. The population of the study consisted of the Special Federal Tertiary Institution Libraries under study while the subjects of the study ...

A comprehensive comparison of comparative RNA structure prediction approaches

DEFF Research Database (Denmark)

Gardner, P. P.; Giegerich, R.

2004-01-01

-finding and multiple-sequence-alignment algorithms. Results Here we evaluate a number of RNA folding algorithms using reliable RNA data-sets and compare their relative performance. Conclusions We conclude that comparative data can enhance structure prediction but structure-prediction-algorithms vary widely in terms......Background An increasing number of researchers have released novel RNA structure analysis and prediction algorithms for comparative approaches to structure prediction. Yet, independent benchmarking of these algorithms is rarely performed as is now common practice for protein-folding, gene...

Nucleic acid secondary structure prediction and display.

OpenAIRE

Stüber, K

1986-01-01

A set of programs has been developed for the prediction and display of nucleic acid secondary structures. Information from experimental data can be used to restrict or enforce secondary structural elements. The predictions can be displayed either on normal line printers or on graphic devices like plotters or graphic terminals.

Discovery of tertiary sulfonamides as potent liver X receptor antagonists.

Science.gov (United States)

Zuercher, William J; Buckholz, Richard G; Campobasso, Nino; Collins, Jon L; Galardi, Cristin M; Gampe, Robert T; Hyatt, Stephen M; Merrihew, Susan L; Moore, John T; Oplinger, Jeffrey A; Reid, Paul R; Spearing, Paul K; Stanley, Thomas B; Stewart, Eugene L; Willson, Timothy M

2010-04-22

Tertiary sulfonamides were identified in a HTS as dual liver X receptor (LXR, NR1H2, and NR1H3) ligands, and the binding affinity of the series was increased through iterative analogue synthesis. A ligand-bound cocrystal structure was determined which elucidated key interactions for high binding affinity. Further characterization of the tertiary sulfonamide series led to the identification of high affinity LXR antagonists. GSK2033 (17) is the first potent cell-active LXR antagonist described to date. 17 may be a useful chemical probe to explore the cell biology of this orphan nuclear receptor.

Upgrading and downgrading of prostate cancer from biopsy to radical prostatectomy: incidence and predictive factors using the modified Gleason grading system and factoring in tertiary grades.

Science.gov (United States)

Epstein, Jonathan I; Feng, Zhaoyong; Trock, Bruce J; Pierorazio, Phillip M

2012-05-01

Prior studies assessing the correlation of Gleason score (GS) at needle biopsy and corresponding radical prostatectomy (RP) predated the use of the modified Gleason scoring system and did not factor in tertiary grade patterns. To assess the relation of biopsy and RP grade in the largest study to date. A total of 7643 totally embedded RP and corresponding needle biopsies (2004-2010) were analyzed according to the updated Gleason system. All patients underwent prostate biopsy prior to RP. The relation of upgrading or downgrading to patient and cancer characteristics was compared using the chi-square test, Student t test, and multivariable logistic regression. A total of 36.3% of cases were upgraded from a needle biopsy GS 5-6 to a higher grade at RP (11.2% with GS 6 plus tertiary). Half of the cases had matching GS 3+4=7 at biopsy and RP with an approximately equal number of cases downgraded and upgraded at RP. With biopsy GS 4+3=7, RP GS was almost equally 3+4=7 and 4+3=7. Biopsy GS 8 led to an almost equal distribution between RP GS 4+3=7, 8, and 9-10. A total of 58% of the cases had matching GS 9-10 at biopsy and RP. In multivariable analysis, increasing age (pfactoring in multiple variables including the number of positive cores and the maximum percentage of cancer per core, the concordance indexes were not sufficiently high to justify the use of nomograms for predicting upgrading and downgrading for the individual patient. Almost 20% of RP cases have tertiary patterns. A needle biopsy can sample a tertiary higher Gleason pattern in the RP, which is then not recorded in the standard GS reporting, resulting in an apparent overgrading on the needle biopsy. Copyright © 2012 European Association of Urology. Published by Elsevier B.V. All rights reserved.

A study of structure–activity relationships of commercial tertiary amines for post-combustion CO_2 capture

International Nuclear Information System (INIS)

Xiao, Min; Liu, Helei; Idem, Raphael; Tontiwachwuthikul, Paitoon; Liang, Zhiwu

2016-01-01

Highlights: • Ethyl group is beneficial for tertiary amines of CO_2 absorption. • The existence of side carbon chain may promote the activity of tertiary amine. • Hydroxyl group reduces the equilibrium CO_2 solubility, k_2 and pKa. • Heterocyclic structure decrease the equilibrium CO_2 solubility, k_2 and pKa. • Hydroxyl group results in higher CO_2 absorption heat. - Abstract: This work examined the relationship between the structure of various commercial tertiary amines and their activity in CO_2 absorption/desorption in terms of rate of CO_2 absorption, equilibrium CO_2 loading, pKa and heat of CO_2 absorption in order to establish possible guidelines for selection of tertiary amine components for amine blends. Results show that any electron donating group linked directly to the nitrogen atom increases their reactivity with CO_2. In addition, the presence of steric hindrance effect and good water solubility also show enhancements in activity. In contrast, the existence of a hydroxyl group leads to a decrease in all the activity of the tertiary amine. The heat of CO_2 absorption of tertiary amines, which is closely related to the regeneration energy, can be reduced by decreasing the number of hydroxyethyl groups or by positing the hydroxyl group at the proper carbon relative to the nitrogen atom.

Viral IRES prediction system - a web server for prediction of the IRES secondary structure in silico.

Directory of Open Access Journals (Sweden)

Jun-Jie Hong

Full Text Available The internal ribosomal entry site (IRES functions as cap-independent translation initiation sites in eukaryotic cells. IRES elements have been applied as useful tools for bi-cistronic expression vectors. Current RNA structure prediction programs are unable to predict precisely the potential IRES element. We have designed a viral IRES prediction system (VIPS to perform the IRES secondary structure prediction. In order to obtain better results for the IRES prediction, the VIPS can evaluate and predict for all four different groups of IRESs with a higher accuracy. RNA secondary structure prediction, comparison, and pseudoknot prediction programs were implemented to form the three-stage procedure for the VIPS. The backbone of VIPS includes: the RNAL fold program, aimed to predict local RNA secondary structures by minimum free energy method; the RNA Align program, intended to compare predicted structures; and pknotsRG program, used to calculate the pseudoknot structure. VIPS was evaluated by using UTR database, IRES database and Virus database, and the accuracy rate of VIPS was assessed as 98.53%, 90.80%, 82.36% and 80.41% for IRES groups 1, 2, 3, and 4, respectively. This advance useful search approach for IRES structures will facilitate IRES related studies. The VIPS on-line website service is available at http://140.135.61.250/vips/.

Computational predictions of zinc oxide hollow structures

Science.gov (United States)

Tuoc, Vu Ngoc; Huan, Tran Doan; Thao, Nguyen Thi

2018-03-01

Nanoporous materials are emerging as potential candidates for a wide range of technological applications in environment, electronic, and optoelectronics, to name just a few. Within this active research area, experimental works are predominant while theoretical/computational prediction and study of these materials face some intrinsic challenges, one of them is how to predict porous structures. We propose a computationally and technically feasible approach for predicting zinc oxide structures with hollows at the nano scale. The designed zinc oxide hollow structures are studied with computations using the density functional tight binding and conventional density functional theory methods, revealing a variety of promising mechanical and electronic properties, which can potentially find future realistic applications.

Effects prediction guidelines for structures subjected to ground motion

International Nuclear Information System (INIS)

1975-07-01

Part of the planning for an underground nuclear explosion (UNE) is determining the effects of expected ground motion on exposed structures. Because of the many types of structures and the wide variation in ground motion intensity typically encountered, no single prediction method is both adequate and feasible for a complete evaluation. Furthermore, the nature and variability of ground motion and structure damage prescribe effects predictions that are made probabilistically. Initially, prediction for a UNE involves a preliminary assessment of damage to establish overall project feasibility. Subsequent efforts require more detailed damage evaluations, based on structure inventories and analyses of specific structures, so that safety problems can be identified and safety and remedial measures can be recommended. To cover this broad range of effects prediction needs for a typical UNE project, three distinct but interrelated methods have been developed and are described. First, the fundamental practical and theoretical aspects of predicting the effects of dynamic ground motion on structures are summarized. Next, experimentally derived and theoretically determined observations of the behavior of typical structures subjected to ground motion are presented. Then, based on these fundamental considerations and on the observed behavior of structures, the formulation of the three effects prediction procedures is described, along with guidelines regarding their applicability. Example damage predictions for hypothetical UNEs demonstrate these procedures. To aid in identifying the vibration properties of complex structures, one chapter discusses alternatives in vibration testing, instrumentation, and data analysis. Finally, operational guidelines regarding data acquisition procedures, safety criteria, and remedial measures involved in conducting structure effects evaluations are discussed. (U.S.)

Stochastic Extreme Load Predictions for Marine Structures

DEFF Research Database (Denmark)

Jensen, Jørgen Juncher

1999-01-01

Development of rational design criteria for marine structures requires reliable estimates for the maximum wave-induced loads the structure may encounter during its operational lifetime. The paper discusses various methods for extreme value predictions taking into account the non-linearity of the ......Development of rational design criteria for marine structures requires reliable estimates for the maximum wave-induced loads the structure may encounter during its operational lifetime. The paper discusses various methods for extreme value predictions taking into account the non......-linearity of the waves and the response. As example the wave-induced bending moment in the ship hull girder is considered....

Economics of Tertiary Education - Challenges and dynamics of the public tertiary education in Albania

Directory of Open Access Journals (Sweden)

Gledian Llatja

2016-07-01

Full Text Available The tertiary education is a critic mechanism for the socio-economic progress, for individuals who aspire a brighter future and it is also considered an important catalyzer of the economic mobility (Department of Treasury and Department of Education, 2012, 2. Based on the positive role and impact that the tertiary education has on the sustainable development, President Obama once stated that it is of damage to treat education as a luxurious public service. In line with the general considerations about the tertiary education in the U.S. the parallel comparison with Albania comes as a direct interpretation of utopia in the education policy-making. As policies are usually drafted based on data and findings, in the case of Albania there is a lack of data on expenses on tertiary education as share of GDP. This stands also for the main limitation of the paper.

Model for an RNA tertiary interaction from the structure of an intermolecular complex between a GAAA tetraloop and an RNA helix.

Science.gov (United States)

Pley, H W; Flaherty, K M; McKay, D B

1994-11-03

In large structured RNAs, RNA hairpins in which the strands of the duplex stem are connected by a tetraloop of the consensus sequence 5'-GNRA (where N is any nucleotide, and R is either G or A) are unusually frequent. In group I introns there is a covariation in sequence between nucleotides in the third and fourth positions of the loop with specific distant base pairs in putative RNA duplex stems: GNAA loops correlate with successive 5'-C-C.G-C base pairs in stems, whereas GNGA loops correlate with 5'-C-U.G-A. This has led to the suggestion that GNRA tetraloops may be involved in specific long-range tertiary interactions, with each A in position 3 or 4 of the loop interacting with a C-G base pair in the duplex, and G in position 3 interacting with a U-A base pair. This idea is supported experimentally for the GAAA loop of the P5b extension of the group I intron of Tetrahymena thermophila and the L9 GUGA terminal loop of the td intron of bacteriophage T4 (ref. 4). NMR has revealed the overall structure of the tetraloop for 12-nucleotide hairpins with GCAA and GAAA loops and models have been proposed for the interaction of GNRA tetraloops with base pairs in the minor groove of A-form RNA. Here we describe the crystal structure of an intermolecular complex between a GAAA tetraloop and an RNA helix. The interactions we observe correlate with the specificity of GNRA tetraloops inferred from phylogenetic studies, suggesting that this complex is a legitimate model for intramolecular tertiary interactions mediated by GNRA tetraloops in large structured RNAs.

Why Do Tertiary Education Graduates Regret Their Study Program? A Comparison between Spain and the Netherlands

Science.gov (United States)

Kucel, Aleksander; Vilalta-Bufi, Montserrat

2013-01-01

In this paper we investigate the determinants of regret of study program for tertiary education graduates in Spain and the Netherlands. These two countries differ in their educational system in terms of the tracking structure in their secondary education and the strength of their education-labor market linkages in tertiary education. Therefore, by…

Risk factors predicting mortality in patients with lung abscess in a public tertiary care center in Karachi, Pakistan.

Science.gov (United States)

Ghazal, Shaista; Kumar, Ashok; Shrestha, Binav; Sajid, Sana; Malik, Maria; Rizvi, Nadeen

2013-01-01

Lung abscess is a commonly encountered entity in South-East Asia but not much data regarding its outcome is available. The objective of this study was to identify the factors associated with increased mortality in patients diagnosed with lung abscess in a tertiary care center of Karachi, Pakistan. A retrospective case analysis was performed via hospital records, on patients admitted with lung abscess between January 2009 and January 2011 at the largest state-owned tertiary care centre in Karachi, Pakistan. Out of the 41 patients hospitalized, 17 could not survive and were evaluated for clinical, radiological and microbiological factors to determine association with heightened mortality. Mortality due to lung abscess stood at 41.4% (17 of 41 cases). Adult male patients were found to have higher mortality with 13 out of 17 (43%) dead patients being male. A majority (21/41, 51.2%) of the cases belonged to the 41-60 year old age group. Highest mortality was seen in patients200 mg/dL (56%) succumb to disease. Patients with a positive history of smoking, diabetes mellitus, and alcohol intake expressed mortality rates of 44%, 56%, and 50% respectively; while 29.4% of the mortalities were positive for Pseudomonas aeruginosa on sputum culture. A significant association was found with elevated mortality and low haemoglobin levels at time of admission; mortality was 58% (p=0.005) in patients with Hb less than or equal to 10 mg/dL. The risk factors involved with heightened mortality included male gender and history of smoking, diabetes and alcohol intake. High blood sugar levels and detection of Pseudomonas aeruginosa on sputum cultures were also implicated. Anemia (Hb level less than or equal to 10 mg/dl) was statistically significant predictive factor for increased mortality.

Correlation of RNA secondary structure statistics with thermodynamic stability and applications to folding.

Science.gov (United States)

Wu, Johnny C; Gardner, David P; Ozer, Stuart; Gutell, Robin R; Ren, Pengyu

2009-08-28

The accurate prediction of the secondary and tertiary structure of an RNA with different folding algorithms is dependent on several factors, including the energy functions. However, an RNA higher-order structure cannot be predicted accurately from its sequence based on a limited set of energy parameters. The inter- and intramolecular forces between this RNA and other small molecules and macromolecules, in addition to other factors in the cell such as pH, ionic strength, and temperature, influence the complex dynamics associated with transition of a single stranded RNA to its secondary and tertiary structure. Since all of the factors that affect the formation of an RNAs 3D structure cannot be determined experimentally, statistically derived potential energy has been used in the prediction of protein structure. In the current work, we evaluate the statistical free energy of various secondary structure motifs, including base-pair stacks, hairpin loops, and internal loops, using their statistical frequency obtained from the comparative analysis of more than 50,000 RNA sequences stored in the RNA Comparative Analysis Database (rCAD) at the Comparative RNA Web (CRW) Site. Statistical energy was computed from the structural statistics for several datasets. While the statistical energy for a base-pair stack correlates with experimentally derived free energy values, suggesting a Boltzmann-like distribution, variation is observed between different molecules and their location on the phylogenetic tree of life. Our statistical energy values calculated for several structural elements were utilized in the Mfold RNA-folding algorithm. The combined statistical energy values for base-pair stacks, hairpins and internal loop flanks result in a significant improvement in the accuracy of secondary structure prediction; the hairpin flanks contribute the most.

Evolving stochastic context-free grammars for RNA secondary structure prediction

DEFF Research Database (Denmark)

Anderson, James WJ; Tataru, Paula Cristina; Stains, Joe

2012-01-01

Background Stochastic Context-Free Grammars (SCFGs) were applied successfully to RNA secondary structure prediction in the early 90s, and used in combination with comparative methods in the late 90s. The set of SCFGs potentially useful for RNA secondary structure prediction is very large, but a few...... to structure prediction as has been previously suggested. Results These search techniques were applied to predict RNA secondary structure on a maximal data set and revealed new and interesting grammars, though none are dramatically better than classic grammars. In general, results showed that many grammars...... with quite different structure could have very similar predictive ability. Many ambiguous grammars were found which were at least as effective as the best current unambiguous grammars. Conclusions Overall the method of evolving SCFGs for RNA secondary structure prediction proved effective in finding many...

RNA secondary structure prediction using soft computing.

Science.gov (United States)

Ray, Shubhra Sankar; Pal, Sankar K

2013-01-01

Prediction of RNA structure is invaluable in creating new drugs and understanding genetic diseases. Several deterministic algorithms and soft computing-based techniques have been developed for more than a decade to determine the structure from a known RNA sequence. Soft computing gained importance with the need to get approximate solutions for RNA sequences by considering the issues related with kinetic effects, cotranscriptional folding, and estimation of certain energy parameters. A brief description of some of the soft computing-based techniques, developed for RNA secondary structure prediction, is presented along with their relevance. The basic concepts of RNA and its different structural elements like helix, bulge, hairpin loop, internal loop, and multiloop are described. These are followed by different methodologies, employing genetic algorithms, artificial neural networks, and fuzzy logic. The role of various metaheuristics, like simulated annealing, particle swarm optimization, ant colony optimization, and tabu search is also discussed. A relative comparison among different techniques, in predicting 12 known RNA secondary structures, is presented, as an example. Future challenging issues are then mentioned.

The role of big five factors on predicting job crafting propensities amongst administrative employees in a South African tertiary institution

Directory of Open Access Journals (Sweden)

Clement Bell

2016-04-01

Full Text Available Orientation: Personality provides a foundation for understanding employee job behaviours. It determines and reflects how they respond to their work situations. There is a shortage of previous researches that have specifically dealt with the predictive role of personality on job crafting. Job crafting is also a significantly new concept in the South African work context. It has both positive and negative consequences on employee job behaviours. Research purpose: The present study investigated the role of big five factors on predicting job crafting propensities amongst administrative employees in Alice, South Africa. Motivation for the study: The present study aimed to determine the role of big five factors on predicting job crafting propensities amongst administrative employees. It was premised on previous research that the big five factors are associated with many employee job behaviours. Research approach, design and method: The present study employed a quantitative, crosssectional research design with a sample of 246 administrative employees in Alice, South Africa. A biographical questionnaire, a Big Five Inventory, and a job crafting questionnaire were used to collect data. Main findings: The findings showed that big five factors of Conscientiousness, Extraversion, Agreeableness, Openness to experience and Neuroticism play a significant role in predicting job crafting propensities. Practical implications: The present study suggests that big five factors of Conscientiousness, Extraversion, Agreeableness, Openness to experience and Neuroticism have a predictive role on job crafting behaviours. Managers of tertiary institutions can therefore consider these big five personalities to understand and predict the impacts of their job design strategies on administrative employees’ behaviours. Contribution: The contribution of the study was significant in that it contributed to research literature representing the influence of the big five factors in

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.

In silico modeling techniques for predicting the tertiary structure of human H4 receptor.

Science.gov (United States)

Zaid, Hilal; Raiyn, Jamal; Osman, Midhat; Falah, Mizied; Srouji, Samer; Rayan, Anwar

2016-01-01

First cloned in 2000, the human Histamine H4 Receptor (hH4R) is the last member of the histamine receptors family discovered so far, it belongs to the GPCR super-family and is involved in a wide variety of immunological and inflammatory responses. Potential hH4R antagonists are proposed to have therapeutic potential for the treatment of allergies, inflammation, asthma and colitis. So far, no hH4R ligands have been successfully introduced to the pharmaceutical market, which creates a strong demand for new selective ligands to be developed. in silico techniques and structural based modeling are likely to facilitate the achievement of this goal. In this review paper we attempt to cover the fundamental concepts of hH4R structure modeling and its implementations in drug discovery and development, especially those that have been experimentally tested and to highlight some ideas that are currently being discussed on the dynamic nature of hH4R and GPCRs, in regards to computerized techniques for 3-D structure modeling.

A theoretical analysis of procurement auctions for tertiary control in Germany

International Nuclear Information System (INIS)

Mueller, Gernot; Rammerstorfer, Margarethe

2008-01-01

As far as energy policy is concerned, the design of the regulatory framework for energy transmission and distribution is a key issue. Consequently, also the embodiment of balancing power markets drives mainly the effectiveness of political implications for the energy sector. Initially, tertiary control in Germany was solely offered by transmission system operators of the respective power control areas and their associated power plant. The recast of the Energy Industry Act of 2005 led in last consequence to a common procurement auction for the supply of tertiary control, which starts on December 1, 2006. Admittedly, the reform has fallen short of expectations so far, first concerning the intensification of market entry of tertiary control providers as well as the desired decline of the price level. Hence, this article examines the effects of the changeover on observable demand charges. In order to identify attributes of the common procurement auction for tertiary control hampering market entry of providers, giving stimuli to collusion and strategic behavior, reducing intensity of competition and encouraging an upswing of prices, we analyze the design under an auction theoretical approach and deduce empirically whether structural components of the auction design have to be touched up again

CONFOLD2: improved contact-driven ab initio protein structure modeling.

Science.gov (United States)

Adhikari, Badri; Cheng, Jianlin

2018-01-25

Contact-guided protein structure prediction methods are becoming more and more successful because of the latest advances in residue-residue contact prediction. To support contact-driven structure prediction, effective tools that can quickly build tertiary structural models of good quality from predicted contacts need to be developed. We develop an improved contact-driven protein modelling method, CONFOLD2, and study how it may be effectively used for ab initio protein structure prediction with predicted contacts as input. It builds models using various subsets of input contacts to explore the fold space under the guidance of a soft square energy function, and then clusters the models to obtain the top five models. CONFOLD2 obtains an average reconstruction accuracy of 0.57 TM-score for the 150 proteins in the PSICOV contact prediction dataset. When benchmarked on the CASP11 contacts predicted using CONSIP2 and CASP12 contacts predicted using Raptor-X, CONFOLD2 achieves a mean TM-score of 0.41 on both datasets. CONFOLD2 allows to quickly generate top five structural models for a protein sequence when its secondary structures and contacts predictions at hand. The source code of CONFOLD2 is publicly available at https://github.com/multicom-toolbox/CONFOLD2/ .

EVA: continuous automatic evaluation of protein structure prediction servers.

Science.gov (United States)

Eyrich, V A; Martí-Renom, M A; Przybylski, D; Madhusudhan, M S; Fiser, A; Pazos, F; Valencia, A; Sali, A; Rost, B

2001-12-01

Evaluation of protein structure prediction methods is difficult and time-consuming. Here, we describe EVA, a web server for assessing protein structure prediction methods, in an automated, continuous and large-scale fashion. Currently, EVA evaluates the performance of a variety of prediction methods available through the internet. Every week, the sequences of the latest experimentally determined protein structures are sent to prediction servers, results are collected, performance is evaluated, and a summary is published on the web. EVA has so far collected data for more than 3000 protein chains. These results may provide valuable insight to both developers and users of prediction methods. http://cubic.bioc.columbia.edu/eva. eva@cubic.bioc.columbia.edu

Tertiary Lymphoid Structures in Cancer: Drivers of Antitumor Immunity, Immunosuppression, or Bystander Sentinels in Disease?

Science.gov (United States)

Colbeck, Emily Jayne; Ager, Ann; Gallimore, Awen; Jones, Gareth Wyn

2017-01-01

Secondary lymphoid organs are integral to initiation and execution of adaptive immune responses. These organs provide a setting for interactions between antigen-specific lymphocytes and antigen-presenting cells recruited from local infected or inflamed tissues. Secondary lymphoid organs develop as a part of a genetically preprogrammed process during embryogenesis. However, organogenesis of secondary lymphoid tissues can also be recapitulated in adulthood during de novo lymphoid neogenesis of tertiary lymphoid structures (TLSs). These ectopic lymphoid-like structures form in the inflamed tissues afflicted by various pathological conditions, including cancer, autoimmunity, infection, or allograft rejection. Studies are beginning to shed light on the function of such structures in different disease settings, raising important questions regarding their contribution to progression or resolution of disease. Data show an association between the tumor-associated TLSs and a favorable prognosis in various types of human cancer, attracting the speculation that TLSs support effective local antitumor immune responses. However, definitive evidence for the role for TLSs in fostering immune responses in vivo are lacking, with current data remaining largely correlative by nature. In fact, some more recent studies have even demonstrated an immunosuppressive, tumor-promoting role for cancer-associated TLSs. In this review, we will discuss what is known about the development of cancer-associated TLSs and the current understanding of their potential role in the antitumor immune response. PMID:29312327

Interaction Of Calcium Phosphate Nanoparticles With Human Chorionic Gonadotropin Modifies Secondary And Tertiary Protein Structure

Directory of Open Access Journals (Sweden)

Al-Hakeim Hussein K

2015-12-01

Full Text Available Calcium phosphate nanoparticles (CaPNP have good biocompatibility and bioactivity inside human body. In this study, the interaction between CaPNP and human chorionic gonadotropin (hCG was analyzed to determine the changes in the protein structure in the presence of CaPNP and the quantity of protein adsorbed on the CaPNP surface. The results showed a significant adsorption of hCG on the CaPNP nanoparticle surface. The optimal fit was achieved using the Sips isotherm equation with a maximum adsorption capacity of 68.23 µg/mg. The thermodynamic parameters, including ∆H° and ∆G°, of the adsorption process are positive, whereas ∆S° is negative. The circular dichroism results of the adsorption of hCG on CaPNP showed the changes in its secondary structure; such changes include the decomposition of α-helix strand and the increase in β-pleated sheet and random coil percentages. Fluorescence study indicated minimal changes in the tertiary structure near the microenvironment of the aromatic amino acids such as tyrosine and phenyl alanine caused by the interaction forces between the CaPNP and hCG protein. The desorption process showed that the quantity of the hCG desorbed significantly increases as temperature increases, which indicates the weak forces between hCG and the surface.

A Kernel for Protein Secondary Structure Prediction

OpenAIRE

Guermeur , Yann; Lifchitz , Alain; Vert , Régis

2004-01-01

http://mitpress.mit.edu/catalog/item/default.asp?ttype=2&tid=10338&mode=toc; International audience; Multi-class support vector machines have already proved efficient in protein secondary structure prediction as ensemble methods, to combine the outputs of sets of classifiers based on different principles. In this chapter, their implementation as basic prediction methods, processing the primary structure or the profile of multiple alignments, is investigated. A kernel devoted to the task is in...

Tertiary climatic fluctuations and methods of analysis of tertiary floras

Science.gov (United States)

Wolfe, J.A.

1971-01-01

On theoretical grounds, an analysis of the physiognomy of a Tertiary leaf assemblage is more direct and reliable than a circuitous floristic analysis in assigning thermal regimes to fossil assemblages. Using primarily foliar physiognomy and secondarily floristic composition, it can be shown that: (1) some middle latitude Tertiary assemblages probably lived under meteoroligically tropical climates; (2) a major and rapid climatic deterioration occurred in the Oligocene; and (3) a major climatic fluctuation probably occurred in the Late Eocene. These analyses thus substantiate the conclusions of several other paleobotanists regarding climatic fluctuations. Recent criticisms of these analyses are shown to be invalid and to be based largely on misinterpretations. ?? 1971.

Blind Test of Physics-Based Prediction of Protein Structures

Science.gov (United States)

Shell, M. Scott; Ozkan, S. Banu; Voelz, Vincent; Wu, Guohong Albert; Dill, Ken A.

2009-01-01

We report here a multiprotein blind test of a computer method to predict native protein structures based solely on an all-atom physics-based force field. We use the AMBER 96 potential function with an implicit (GB/SA) model of solvation, combined with replica-exchange molecular-dynamics simulations. Coarse conformational sampling is performed using the zipping and assembly method (ZAM), an approach that is designed to mimic the putative physical routes of protein folding. ZAM was applied to the folding of six proteins, from 76 to 112 monomers in length, in CASP7, a community-wide blind test of protein structure prediction. Because these predictions have about the same level of accuracy as typical bioinformatics methods, and do not utilize information from databases of known native structures, this work opens up the possibility of predicting the structures of membrane proteins, synthetic peptides, or other foldable polymers, for which there is little prior knowledge of native structures. This approach may also be useful for predicting physical protein folding routes, non-native conformations, and other physical properties from amino acid sequences. PMID:19186130

Protein structure prediction using bee colony optimization metaheuristic

DEFF Research Database (Denmark)

Fonseca, Rasmus; Paluszewski, Martin; Winter, Pawel

2010-01-01

of the proteins structure, an energy potential and some optimization algorithm that ¿nds the structure with minimal energy. Bee Colony Optimization (BCO) is a relatively new approach to solving opti- mization problems based on the foraging behaviour of bees. Several variants of BCO have been suggested......Predicting the native structure of proteins is one of the most challenging problems in molecular biology. The goal is to determine the three-dimensional struc- ture from the one-dimensional amino acid sequence. De novo prediction algorithms seek to do this by developing a representation...... our BCO method to generate good solutions to the protein structure prediction problem. The results show that BCO generally ¿nds better solutions than simulated annealing which so far has been the metaheuristic of choice for this problem....

Pushing the size limit of de novo structure ensemble prediction guided by sparse SDSL-EPR restraints to 200 residues: The monomeric and homodimeric forms of BAX

Science.gov (United States)

Fischer, Axel W.; Bordignon, Enrica; Bleicken, Stephanie; García-Sáez, Ana J.; Jeschke, Gunnar; Meiler, Jens

2016-01-01

Structure determination remains a challenge for many biologically important proteins. In particular, proteins that adopt multiple conformations often evade crystallization in all biologically relevant states. Although computational de novo protein folding approaches often sample biologically relevant conformations, the selection of the most accurate model for different functional states remains a formidable challenge, in particular, for proteins with more than about 150 residues. Electron paramagnetic resonance (EPR) spectroscopy can obtain limited structural information for proteins in well-defined biological states and thereby assist in selecting biologically relevant conformations. The present study demonstrates that de novo folding methods are able to accurately sample the folds of 192-residue long soluble monomeric Bcl-2-associated X protein (BAX). The tertiary structures of the monomeric and homodimeric forms of BAX were predicted using the primary structure as well as 25 and 11 EPR distance restraints, respectively. The predicted models were subsequently compared to respective NMR/X-ray structures of BAX. EPR restraints improve the protein-size normalized root-mean-square-deviation (RMSD100) of the most accurate models with respect to the NMR/crystal structure from 5.9 Å to 3.9 Å and from 5.7 Å to 3.3 Å, respectively. Additionally, the model discrimination is improved, which is demonstrated by an improvement of the enrichment from 5% to 15% and from 13% to 21%, respectively. PMID:27129417

NEAT-FLEX: Predicting the conformational flexibility of amino acids using neuroevolution of augmenting topologies.

Science.gov (United States)

Grisci, Bruno; Dorn, Márcio

2017-06-01

The development of computational methods to accurately model three-dimensional protein structures from sequences of amino acid residues is becoming increasingly important to the structural biology field. This paper addresses the challenge of predicting the tertiary structure of a given amino acid sequence, which has been reported to belong to the NP-Complete class of problems. We present a new method, namely NEAT-FLEX, based on NeuroEvolution of Augmenting Topologies (NEAT) to extract structural features from (ABS) proteins that are determined experimentally. The proposed method manipulates structural information from the Protein Data Bank (PDB) and predicts the conformational flexibility (FLEX) of residues of a target amino acid sequence. This information may be used in three-dimensional structure prediction approaches as a way to reduce the conformational search space. The proposed method was tested with 24 different amino acid sequences. Evolving neural networks were compared against a traditional error back-propagation algorithm; results show that the proposed method is a powerful way to extract and represent structural information from protein molecules that are determined experimentally.

Comparison of initial and tertiary centre second opinion reads of multiparametric magnetic resonance imaging of the prostate prior to repeat biopsy

Energy Technology Data Exchange (ETDEWEB)

Hansen, Nienke L. [University Hospital RWTH Aachen, Department of Diagnostic and Interventional Radiology, Aachen (Germany); Addenbrooke' s Hospital and University of Cambridge, CamPARI Clinic, Cambridge (United Kingdom); Koo, Brendan C.; Gallagher, Ferdia A. [Addenbrooke' s Hospital and University of Cambridge, CamPARI Clinic, Cambridge (United Kingdom); Addenbrooke' s Hospital and University of Cambridge, Department of Radiology, Cambridge (United Kingdom); Warren, Anne Y. [Addenbrooke' s Hospital and University of Cambridge, CamPARI Clinic, Cambridge (United Kingdom); Addenbrooke' s Hospital, Department of Pathology, Cambridge (United Kingdom); Doble, Andrew; Gnanapragasam, Vincent; Bratt, Ola; Kastner, Christof [Addenbrooke' s Hospital and University of Cambridge, CamPARI Clinic, Cambridge (United Kingdom); Addenbrooke' s Hospital, Department of Urology, Cambridge (United Kingdom); Barrett, Tristan [Addenbrooke' s Hospital and University of Cambridge, CamPARI Clinic, Cambridge (United Kingdom); Addenbrooke' s Hospital and University of Cambridge, Department of Radiology, Cambridge (United Kingdom); University of Cambridge School of Clinical Medicine, Department of Radiology, Box 218, Cambridge (United Kingdom)

2017-06-15

To investigate the value of second-opinion evaluation of multiparametric prostate magnetic resonance imaging (MRI) by subspecialised uroradiologists at a tertiary centre for the detection of significant cancer in transperineal fusion prostate biopsy. Evaluation of prospectively acquired initial and second-opinion radiology reports of 158 patients who underwent MRI at regional hospitals prior to transperineal MR/untrasound fusion biopsy at a tertiary referral centre over a 3-year period. Gleason score (GS) 7-10 cancer, positive predictive value (PPV) and negative (NPV) predictive value (±95 % confidence intervals) were calculated and compared by Fisher's exact test. Disagreement between initial and tertiary centre second-opinion reports was observed in 54 % of cases (86/158). MRIs had a higher NPV for GS 7-10 in tertiary centre reads compared to initial reports (0.89 ± 0.08 vs 0.72 ± 0.16; p = 0.04), and a higher PPV in the target area for all cancer (0.61 ± 0.12 vs 0.28 ± 0.10; p = 0.01) and GS 7-10 cancer (0.43 ± 0.12 vs 0.2 3 ± 0.09; p = 0.02). For equivocal suspicion, the PPV for GS 7-10 was 0.12 ± 0.11 for tertiary centre and 0.11 ± 0.09 for initial reads; p = 1.00. Second readings of prostate MRI by subspecialised uroradiologists at a tertiary centre significantly improved both NPV and PPV. Reporter experience may help to reduce overcalling and avoid overtargeting of lesions. (orig.)

Protein secondary structure: category assignment and predictability

DEFF Research Database (Denmark)

Andersen, Claus A.; Bohr, Henrik; Brunak, Søren

2001-01-01

In the last decade, the prediction of protein secondary structure has been optimized using essentially one and the same assignment scheme known as DSSP. We present here a different scheme, which is more predictable. This scheme predicts directly the hydrogen bonds, which stabilize the secondary......-forward neural network with one hidden layer on a data set identical to the one used in earlier work....

PASS Student Leader and Mentor Roles: A Tertiary Leadership Pathway

Science.gov (United States)

Skalicky, Jane; Caney, Annaliese

2010-01-01

In relation to developing leadership skills during tertiary studies, this paper considers the leadership pathway afforded by a Peer Assisted Study Sessions (PASS) program which includes the traditional PASS Leader role and a more senior PASS Mentor role. Data was collected using a structured survey with open-ended questions designed to capture the…

Energy Management Systems and tertiary regulation in hierarchical control architectures for islanded micro-grids

DEFF Research Database (Denmark)

Sanseverino, Eleonora Riva; Di Silvestre, Maria Luisa; Quang, Ninh Nguyen

2015-01-01

In this paper, the structure of the highest level of a hierarchical control architecture for micro-grids is proposed. Such structure includes two sub-levels: the Energy Management System, EMS, and the tertiary regulation. The first devoted to energy resources allocation in each time slot based...

A semi-supervised learning approach for RNA secondary structure prediction.

Science.gov (United States)

Yonemoto, Haruka; Asai, Kiyoshi; Hamada, Michiaki

2015-08-01

RNA secondary structure prediction is a key technology in RNA bioinformatics. Most algorithms for RNA secondary structure prediction use probabilistic models, in which the model parameters are trained with reliable RNA secondary structures. Because of the difficulty of determining RNA secondary structures by experimental procedures, such as NMR or X-ray crystal structural analyses, there are still many RNA sequences that could be useful for training whose secondary structures have not been experimentally determined. In this paper, we introduce a novel semi-supervised learning approach for training parameters in a probabilistic model of RNA secondary structures in which we employ not only RNA sequences with annotated secondary structures but also ones with unknown secondary structures. Our model is based on a hybrid of generative (stochastic context-free grammars) and discriminative models (conditional random fields) that has been successfully applied to natural language processing. Computational experiments indicate that the accuracy of secondary structure prediction is improved by incorporating RNA sequences with unknown secondary structures into training. To our knowledge, this is the first study of a semi-supervised learning approach for RNA secondary structure prediction. This technique will be useful when the number of reliable structures is limited. Copyright © 2015 Elsevier Ltd. All rights reserved.

QCD dipole predictions for DIS and diffractive structure functions

International Nuclear Information System (INIS)

Royon, C.

1997-01-01

The proton structure function F 2 , the gluon density F G , and the longitudinal structure function F L are derived in the QCD dipole picture of BFKL dynamics. We use a three parameter fit to describe the 1994 H1 proton structure function F 2 data in the low x, moderate Q 2 range. Without any additional parameter, the gluon density and the longitudinal structure functions are predicted. The diffractive dissociation processes are also discussed within the same framework, and a new prediction for the proton diffractive structure function is obtained

Evolutionary rate variation and RNA secondary structure prediction

DEFF Research Database (Denmark)

Knudsen, B.; Andersen, E.S.; Damgaard, C.

2004-01-01

Predicting RNA secondary structure using evolutionary history can be carried out by using an alignment of related RNA sequences with conserved structure. Accurately determining evolutionary substitution rates for base pairs and single stranded nucleotides is a concern for methods based on this type...... by applying rates derived from tRNA and rRNA to the prediction of the much more rapidly evolving 5'-region of HIV-1. We find that the HIV-1 prediction is in agreement with experimental data, even though the relative evolutionary rate between A and G is significantly increased, both in stem and loop regions...

Distance matrix-based approach to protein structure prediction.

Science.gov (United States)

Kloczkowski, Andrzej; Jernigan, Robert L; Wu, Zhijun; Song, Guang; Yang, Lei; Kolinski, Andrzej; Pokarowski, Piotr

2009-03-01

Much structural information is encoded in the internal distances; a distance matrix-based approach can be used to predict protein structure and dynamics, and for structural refinement. Our approach is based on the square distance matrix D = [r(ij)(2)] containing all square distances between residues in proteins. This distance matrix contains more information than the contact matrix C, that has elements of either 0 or 1 depending on whether the distance r (ij) is greater or less than a cutoff value r (cutoff). We have performed spectral decomposition of the distance matrices D = sigma lambda(k)V(k)V(kT), in terms of eigenvalues lambda kappa and the corresponding eigenvectors v kappa and found that it contains at most five nonzero terms. A dominant eigenvector is proportional to r (2)--the square distance of points from the center of mass, with the next three being the principal components of the system of points. By predicting r (2) from the sequence we can approximate a distance matrix of a protein with an expected RMSD value of about 7.3 A, and by combining it with the prediction of the first principal component we can improve this approximation to 4.0 A. We can also explain the role of hydrophobic interactions for the protein structure, because r is highly correlated with the hydrophobic profile of the sequence. Moreover, r is highly correlated with several sequence profiles which are useful in protein structure prediction, such as contact number, the residue-wise contact order (RWCO) or mean square fluctuations (i.e. crystallographic temperature factors). We have also shown that the next three components are related to spatial directionality of the secondary structure elements, and they may be also predicted from the sequence, improving overall structure prediction. We have also shown that the large number of available HIV-1 protease structures provides a remarkable sampling of conformations, which can be viewed as direct structural information about the

Epitope targeting of tertiary protein structure enables target-guided synthesis of a potent in-cell inhibitor of botulinum neurotoxin.

Science.gov (United States)

Farrow, Blake; Wong, Michelle; Malette, Jacquie; Lai, Bert; Deyle, Kaycie M; Das, Samir; Nag, Arundhati; Agnew, Heather D; Heath, James R

2015-06-08

Botulinum neurotoxin (BoNT) serotype A is the most lethal known toxin and has an occluded structure, which prevents direct inhibition of its active site before it enters the cytosol. Target-guided synthesis by in situ click chemistry is combined with synthetic epitope targeting to exploit the tertiary structure of the BoNT protein as a landscape for assembling a competitive inhibitor. A substrate-mimicking peptide macrocycle is used as a direct inhibitor of BoNT. An epitope-targeting in situ click screen is utilized to identify a second peptide macrocycle ligand that binds to an epitope that, in the folded BoNT structure, is active-site-adjacent. A second in situ click screen identifies a molecular bridge between the two macrocycles. The resulting divalent inhibitor exhibits an in vitro inhibition constant of 165 pM against the BoNT/A catalytic chain. The inhibitor is carried into cells by the intact holotoxin, and demonstrates protection and rescue of BoNT intoxication in a human neuron model. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

QCD dipole prediction for dis and diffractive structure functions

International Nuclear Information System (INIS)

Royon, CH.

1996-01-01

The F 2 , F G , R = F L /F T proton structure functions are derived in the QCD dipole picture of BFKL dynamics. We get a three parameter fit describing the 1994 H1 proton structure function F 2 data in the low x, moderate Q 2 range. Without any additional parameter, the gluon density and the longitudinal structure functions are predicted. The diffractive dissociation processes are also discussed, and a new prediction for the proton diffractive structure function is obtained. (author)

I-TASSER server for protein 3D structure prediction

Directory of Open Access Journals (Sweden)

Zhang Yang

2008-01-01

Full Text Available Abstract Background Prediction of 3-dimensional protein structures from amino acid sequences represents one of the most important problems in computational structural biology. The community-wide Critical Assessment of Structure Prediction (CASP experiments have been designed to obtain an objective assessment of the state-of-the-art of the field, where I-TASSER was ranked as the best method in the server section of the recent 7th CASP experiment. Our laboratory has since then received numerous requests about the public availability of the I-TASSER algorithm and the usage of the I-TASSER predictions. Results An on-line version of I-TASSER is developed at the KU Center for Bioinformatics which has generated protein structure predictions for thousands of modeling requests from more than 35 countries. A scoring function (C-score based on the relative clustering structural density and the consensus significance score of multiple threading templates is introduced to estimate the accuracy of the I-TASSER predictions. A large-scale benchmark test demonstrates a strong correlation between the C-score and the TM-score (a structural similarity measurement with values in [0, 1] of the first models with a correlation coefficient of 0.91. Using a C-score cutoff > -1.5 for the models of correct topology, both false positive and false negative rates are below 0.1. Combining C-score and protein length, the accuracy of the I-TASSER models can be predicted with an average error of 0.08 for TM-score and 2 Å for RMSD. Conclusion The I-TASSER server has been developed to generate automated full-length 3D protein structural predictions where the benchmarked scoring system helps users to obtain quantitative assessments of the I-TASSER models. The output of the I-TASSER server for each query includes up to five full-length models, the confidence score, the estimated TM-score and RMSD, and the standard deviation of the estimations. The I-TASSER server is freely available

Chemical Properties, Decomposition, and Methane Production of Tertiary Relict Plant Litters: Implications for Atmospheric Trace Gas Production in the Early Tertiary

Science.gov (United States)

Yavitt, J. B.; Bartella, T. M.; Williams, C. J.

2006-12-01

Throughout the early Tertiary (ca. 65-38 Ma) Taxodiaceae-dominated (redwood) wetland forests occupied the high latitudes and were circumpolar in their distribution. Many of these forests had high standing biomass with moderate primary productivity. The geographic extent and amount of Tertiary coals and fossil forests throughout Arctic Canada suggests large areas of wetland forests that may have cycled substantial quantities of carbon, particularly methane until they were replaced by cold tolerant Pinus, Picea, and Larix following climatic cooling associated with the Terminal Eocene Event. To test this hypothesis we compared physiochemical properties, decomposition, and trace gas production of litter from extant Metasequoia, Pinus, Picea, and Larix. Initial results from plantation-grown trees indicate Metasequoia litter is a better source of labile organic substrate than pinaceous litter. Metasequoia litter contained the least lignin and highest amounts of water-soluble compounds of the four litter types studied. Analysis of the lignin structure using cupric oxide oxidation indicates that Metasequoia lignin is enriched in 4'-hydroxyacetophenone and 4'- Hydroxy-3'-methoxyacetophenone relative to the pinaceous litter. In a 12-month decomposition study using litterbags, average litter mass loss was greater for Metasequoia litter (62%) compared to the pinaceous species (50%). Moreover, Metasequoia litter incubated under anoxic conditions produced nearly twice as much CO2 (ca. 4.2 umol/g.day) and CH4 (2.1 umol/g.day) as the pinaceous litter (2.4 umol/g.day for CO2; 1.2 umol/g.day for CH4). Our results support the idea of greater decomposability and palatability of Metasequoia litter as compared to Larix, Picea, or Pinus. Provided that the biochemical properties of Metasequoia have remained relatively stable through geologic time, it appears that early Tertiary Metasequoia-dominated wetland forests may have had higher microbial driven trace gas production than the

Correlating Structural Order with Structural Rearrangement in Dusty Plasma Liquids: Can Structural Rearrangement be Predicted by Static Structural Information?

Science.gov (United States)

Su, Yen-Shuo; Liu, Yu-Hsuan; I, Lin

2012-11-01

Whether the static microstructural order information is strongly correlated with the subsequent structural rearrangement (SR) and their predicting power for SR are investigated experimentally in the quenched dusty plasma liquid with microheterogeneities. The poor local structural order is found to be a good alarm to identify the soft spot and predict the short term SR. For the site with good structural order, the persistent time for sustaining the structural memory until SR has a large mean value but a broad distribution. The deviation of the local structural order from that averaged over nearest neighbors serves as a good second alarm to further sort out the short time SR sites. It has the similar sorting power to that using the temporal fluctuation of the local structural order over a small time interval.

Facilities management: Structuring a body of knowledge for continuing and tertiary education in South Africa

Directory of Open Access Journals (Sweden)

A. C. Hauptfleisch

2010-01-01

is exacerbated by the fact that very little is being done at the level of continuing education and formal tertiary education in South Africa. The limited attempts in this regard are furthermore taking place in isolation, with practically no dialogue between the limited facilities management industry and the providers of the limited education that is available.Although the study that was undertaken did not have the objective to create comprehensive interaction between the existing role-players, the stated problems were addressed by involving the industry, participants in continuing education programmes and other role-players in the condensed research problem as stated below. The problem at hand is firstly to extract, from the present practice of facilities management, a knowledge framework and secondly to formulate the results in terms of suitable continuing and tertiary education programmes to address the shortcomings in South Africa. Research was therefore undertaken to address the structuring of educational programmes. The methodology applied comprised a comprehensive literature survey and three quantified and qualified data surveys, the latter conducted amongst facilities management practitioners, primarily the perceived beneficiaries of such programmes. These surveys provided information that led to the resultant educational activities stated below. The most important aspects that were determined were the following: It was possible to create and test amongst facilities management practitioners a diagrammatic presentation that contextualised facilities management. The literature survey, including international and South African sources, contributed towards compiling a primary knowledge framework for facilities management. The perceived value of the contents of a continuing education programme that had been attended by numerous groups of delegates over a number of years was established. A proposed tertiary education programme was presented to practitioners

Diversification Management at Tertiary Education Level: A Review

Science.gov (United States)

Takwate, Kwaji Tizhe

2016-01-01

This paper examines the concept of management of diversification at tertiary education level in view of the growth of national secondary education system which vested high scramble for tertiary education was made in relation to question of access and expansion. This paper examines management of diversification at tertiary education level as a…

Prediction of degradation and fracture of structural materials

International Nuclear Information System (INIS)

Tomkins, B.

1992-01-01

Prediction of materials performance in an engineering integrity context requires the underpinning of predictive modelling tuned by inputs from design, fabrication, operating experience, and laboratory testing. In this regard, in addition to fracture resistance four important areas of time dependent degradation are considered - mechanical, environmental, irradiation and thermal. The status of prediction of materials performance is discussed in relation to a number of important components such as LWR reactor pressure vessels and steam generators, and Fast Reactor high temperature structures. In each case the role of materials modelling is examined and the balance of factors which contribute to the overall prediction of component integrity/reliability noted. Structural integrity arguments must follow a clear strategy if the required level of confidence is to be established. Various strategies and their evolution are discussed. (author)

New tips for structure prediction by comparative modeling

Science.gov (United States)

Rayan, Anwar

2009-01-01

Comparative modelling is utilized to predict the 3-dimensional conformation of a given protein (target) based on its sequence alignment to experimentally determined protein structure (template). The use of such technique is already rewarding and increasingly widespread in biological research and drug development. The accuracy of the predictions as commonly accepted depends on the score of sequence identity of the target protein to the template. To assess the relationship between sequence identity and model quality, we carried out an analysis of a set of 4753 sequence and structure alignments. Throughout this research, the model accuracy was measured by root mean square deviations of Cα atoms of the target-template structures. Surprisingly, the results show that sequence identity of the target protein to the template is not a good descriptor to predict the accuracy of the 3-D structure model. However, in a large number of cases, comparative modelling with lower sequence identity of target to template proteins led to more accurate 3-D structure model. As a consequence of this study, we suggest new tips for improving the quality of omparative models, particularly for models whose target-template sequence identity is below 50%. PMID:19255646

Cloud prediction of protein structure and function with PredictProtein for Debian.

Science.gov (United States)

Kaján, László; Yachdav, Guy; Vicedo, Esmeralda; Steinegger, Martin; Mirdita, Milot; Angermüller, Christof; Böhm, Ariane; Domke, Simon; Ertl, Julia; Mertes, Christian; Reisinger, Eva; Staniewski, Cedric; Rost, Burkhard

2013-01-01

We report the release of PredictProtein for the Debian operating system and derivatives, such as Ubuntu, Bio-Linux, and Cloud BioLinux. The PredictProtein suite is available as a standard set of open source Debian packages. The release covers the most popular prediction methods from the Rost Lab, including methods for the prediction of secondary structure and solvent accessibility (profphd), nuclear localization signals (predictnls), and intrinsically disordered regions (norsnet). We also present two case studies that successfully utilize PredictProtein packages for high performance computing in the cloud: the first analyzes protein disorder for whole organisms, and the second analyzes the effect of all possible single sequence variants in protein coding regions of the human genome.

The secondary structure and the thermal unfolding parameters of the S-layer protein from Lactobacillus salivarius.

Science.gov (United States)

Lighezan, Liliana; Georgieva, Ralitsa; Neagu, Adrian

2016-09-01

Surface layer (S-layer) proteins have been identified in the cell envelope of many organisms, such as bacteria and archaea. They self-assemble, forming monomolecular crystalline arrays. Isolated S-layer proteins are able to recrystallize into regular lattices, which proved useful in biotechnology. Here we investigate the structure and thermal unfolding of the S-layer protein isolated from Lactobacillus salivarius 16 strain of human origin. Using circular dichroism (CD) spectroscopy, and the software CDSSTR from DICHROWEB, CONTINLL from CDPro, as well as CDNN, we assess the fractions of the protein's secondary structural elements at temperatures ranging between 10 and 90 °C, and predict the tertiary class of the protein. To study the thermal unfolding of the protein, we analyze the temperature dependence of the CD signal in the far- and near-UV domains. Fitting the experimental data by two- and three-state models of thermal unfolding, we infer the midpoint temperatures, the temperature dependence of the changes in Gibbs free energy, enthalpy, and entropy of the unfolding transitions in standard conditions, and the temperature dependence of the equilibrium constant. We also estimate the changes in heat capacity at constant pressure in standard conditions. The results indicate that the thermal unfolding of the S-layer protein from L. salivarius is highly cooperative, since changes in the secondary and tertiary structures occur simultaneously. The thermodynamic analysis predicts a "cold" transition, at about -3 °C, of both the secondary and tertiary structures. Our findings may be important for the use of S-layer proteins in biotechnology and in biomedical applications.

The leucine-rich repeat structure.

Science.gov (United States)

Bella, J; Hindle, K L; McEwan, P A; Lovell, S C

2008-08-01

The leucine-rich repeat is a widespread structural motif of 20-30 amino acids with a characteristic repetitive sequence pattern rich in leucines. Leucine-rich repeat domains are built from tandems of two or more repeats and form curved solenoid structures that are particularly suitable for protein-protein interactions. Thousands of protein sequences containing leucine-rich repeats have been identified by automatic annotation methods. Three-dimensional structures of leucine-rich repeat domains determined to date reveal a degree of structural variability that translates into the considerable functional versatility of this protein superfamily. As the essential structural principles become well established, the leucine-rich repeat architecture is emerging as an attractive framework for structural prediction and protein engineering. This review presents an update of the current understanding of leucine-rich repeat structure at the primary, secondary, tertiary and quaternary levels and discusses specific examples from recently determined three-dimensional structures.

Vfold: a web server for RNA structure and folding thermodynamics prediction.

Science.gov (United States)

Xu, Xiaojun; Zhao, Peinan; Chen, Shi-Jie

2014-01-01

The ever increasing discovery of non-coding RNAs leads to unprecedented demand for the accurate modeling of RNA folding, including the predictions of two-dimensional (base pair) and three-dimensional all-atom structures and folding stabilities. Accurate modeling of RNA structure and stability has far-reaching impact on our understanding of RNA functions in human health and our ability to design RNA-based therapeutic strategies. The Vfold server offers a web interface to predict (a) RNA two-dimensional structure from the nucleotide sequence, (b) three-dimensional structure from the two-dimensional structure and the sequence, and (c) folding thermodynamics (heat capacity melting curve) from the sequence. To predict the two-dimensional structure (base pairs), the server generates an ensemble of structures, including loop structures with the different intra-loop mismatches, and evaluates the free energies using the experimental parameters for the base stacks and the loop entropy parameters given by a coarse-grained RNA folding model (the Vfold model) for the loops. To predict the three-dimensional structure, the server assembles the motif scaffolds using structure templates extracted from the known PDB structures and refines the structure using all-atom energy minimization. The Vfold-based web server provides a user friendly tool for the prediction of RNA structure and stability. The web server and the source codes are freely accessible for public use at "http://rna.physics.missouri.edu".

Sub-crop geologic map of pre-Tertiary rocks in the Yucca Flat and northern Frenchman Flat areas, Nevada Test Site, southern Nevada

Energy Technology Data Exchange (ETDEWEB)

Cole, J.C.; Harris, A.G.; Wahl, R.R.

1997-10-02

for ground water flow through pre-Tertiary rocks beneath the Yucca Flat and northern Frenchman Flat areas, and has consequences for ground water modeling and model validation. Our data indicate that the Mississippian Chainman Shale is not laterally extensive confining unit in the western part of the basin because it is folded back onto itself by the convergent structures of the Belted Range and CP thrust systems. Early and Middle Paleozoic limestone and dolomite are present beneath most of both basins and, regardless of structural complications, are interpreted to form a laterally continuous and extensive carbonate aquifer. Structural culmination that marks the French Peak accommodation zone along the topographic divide between the two basins provides a lateral pathway through highly fractured rock between the volcanic aquifers of Yucca Flat and the regional carbonate aquifer. This pathway may accelerate the migration of ground-water contaminants introduced by underground nuclear testing toward discharge areas beyond the Nevada Test Site boundaries. Predictive three-dimensional models of hydrostratigraphic units and ground-water flow in the pre-Tertiary rocks of subsurface Yucca Flat are likely to be unrealistic due to the extreme structural complexities. The interpretation of hydrologic and geochemical data obtained from monitoring wells will be difficult to extrapolate through the flow system until more is known about the continuity of hydrostratigraphic units. 1 plate

Sub-crop geologic map of pre-Tertiary rocks in the Yucca Flat and northern Frenchman Flat areas, Nevada Test Site, southern Nevada

International Nuclear Information System (INIS)

Cole, J.C.; Harris, A.G.; Wahl, R.R.

1997-01-01

for ground water flow through pre-Tertiary rocks beneath the Yucca Flat and northern Frenchman Flat areas, and has consequences for ground water modeling and model validation. Our data indicate that the Mississippian Chainman Shale is not laterally extensive confining unit in the western part of the basin because it is folded back onto itself by the convergent structures of the Belted Range and CP thrust systems. Early and Middle Paleozoic limestone and dolomite are present beneath most of both basins and, regardless of structural complications, are interpreted to form a laterally continuous and extensive carbonate aquifer. Structural culmination that marks the French Peak accommodation zone along the topographic divide between the two basins provides a lateral pathway through highly fractured rock between the volcanic aquifers of Yucca Flat and the regional carbonate aquifer. This pathway may accelerate the migration of ground-water contaminants introduced by underground nuclear testing toward discharge areas beyond the Nevada Test Site boundaries. Predictive three-dimensional models of hydrostratigraphic units and ground-water flow in the pre-Tertiary rocks of subsurface Yucca Flat are likely to be unrealistic due to the extreme structural complexities. The interpretation of hydrologic and geochemical data obtained from monitoring wells will be difficult to extrapolate through the flow system until more is known about the continuity of hydrostratigraphic units. 1 plate

Functional region prediction with a set of appropriate homologous sequences-an index for sequence selection by integrating structure and sequence information with spatial statistics

Science.gov (United States)

2012-01-01

Background The detection of conserved residue clusters on a protein structure is one of the effective strategies for the prediction of functional protein regions. Various methods, such as Evolutionary Trace, have been developed based on this strategy. In such approaches, the conserved residues are identified through comparisons of homologous amino acid sequences. Therefore, the selection of homologous sequences is a critical step. It is empirically known that a certain degree of sequence divergence in the set of homologous sequences is required for the identification of conserved residues. However, the development of a method to select homologous sequences appropriate for the identification of conserved residues has not been sufficiently addressed. An objective and general method to select appropriate homologous sequences is desired for the efficient prediction of functional regions. Results We have developed a novel index to select the sequences appropriate for the identification of conserved residues, and implemented the index within our method to predict the functional regions of a protein. The implementation of the index improved the performance of the functional region prediction. The index represents the degree of conserved residue clustering on the tertiary structure of the protein. For this purpose, the structure and sequence information were integrated within the index by the application of spatial statistics. Spatial statistics is a field of statistics in which not only the attributes but also the geometrical coordinates of the data are considered simultaneously. Higher degrees of clustering generate larger index scores. We adopted the set of homologous sequences with the highest index score, under the assumption that the best prediction accuracy is obtained when the degree of clustering is the maximum. The set of sequences selected by the index led to higher functional region prediction performance than the sets of sequences selected by other sequence

Structural features that predict real-value fluctuations of globular proteins.

Science.gov (United States)

Jamroz, Michal; Kolinski, Andrzej; Kihara, Daisuke

2012-05-01

It is crucial to consider dynamics for understanding the biological function of proteins. We used a large number of molecular dynamics (MD) trajectories of nonhomologous proteins as references and examined static structural features of proteins that are most relevant to fluctuations. We examined correlation of individual structural features with fluctuations and further investigated effective combinations of features for predicting the real value of residue fluctuations using the support vector regression (SVR). It was found that some structural features have higher correlation than crystallographic B-factors with fluctuations observed in MD trajectories. Moreover, SVR that uses combinations of static structural features showed accurate prediction of fluctuations with an average Pearson's correlation coefficient of 0.669 and a root mean square error of 1.04 Å. This correlation coefficient is higher than the one observed in predictions by the Gaussian network model (GNM). An advantage of the developed method over the GNMs is that the former predicts the real value of fluctuation. The results help improve our understanding of relationships between protein structure and fluctuation. Furthermore, the developed method provides a convienient practial way to predict fluctuations of proteins using easily computed static structural features of proteins. Copyright © 2012 Wiley Periodicals, Inc.

Predicting beta-turns and their types using predicted backbone dihedral angles and secondary structures.

Science.gov (United States)

Kountouris, Petros; Hirst, Jonathan D

2010-07-31

Beta-turns are secondary structure elements usually classified as coil. Their prediction is important, because of their role in protein folding and their frequent occurrence in protein chains. We have developed a novel method that predicts beta-turns and their types using information from multiple sequence alignments, predicted secondary structures and, for the first time, predicted dihedral angles. Our method uses support vector machines, a supervised classification technique, and is trained and tested on three established datasets of 426, 547 and 823 protein chains. We achieve a Matthews correlation coefficient of up to 0.49, when predicting the location of beta-turns, the highest reported value to date. Moreover, the additional dihedral information improves the prediction of beta-turn types I, II, IV, VIII and "non-specific", achieving correlation coefficients up to 0.39, 0.33, 0.27, 0.14 and 0.38, respectively. Our results are more accurate than other methods. We have created an accurate predictor of beta-turns and their types. Our method, called DEBT, is available online at http://comp.chem.nottingham.ac.uk/debt/.

Modeling protein structures: construction and their applications.

Science.gov (United States)

Ring, C S; Cohen, F E

1993-06-01

Although no general solution to the protein folding problem exists, the three-dimensional structures of proteins are being successfully predicted when experimentally derived constraints are used in conjunction with heuristic methods. In the case of interleukin-4, mutagenesis data and CD spectroscopy were instrumental in the accurate assignment of secondary structure. In addition, the tertiary structure was highly constrained by six cysteines separated by many residues that formed three disulfide bridges. Although the correct structure was a member of a short list of plausible structures, the "best" structure was the topological enantiomer of the experimentally determined conformation. For many proteases, other experimentally derived structures can be used as templates to identify the secondary structure elements. In a procedure called modeling by homology, the structure of a known protein is used as a scaffold to predict the structure of another related protein. This method has been used to model a serine and a cysteine protease that are important in the schistosome and malarial life cycles, respectively. The model structures were then used to identify putative small molecule enzyme inhibitors computationally. Experiments confirm that some of these nonpeptidic compounds are active at concentrations of less than 10 microM.

Building the Nonuniversity, Tertiary Care Center Hepatobiliary and Pancreatic Surgery Practice: Structural and Financial Considerations.

Science.gov (United States)

Baker, Erin H; Siddiqui, Imran; Vrochides, Dionisios; Iannitti, David A; Martinie, John B; Rorabaugh, Lauren; Jeyarajah, D Rohan; Swan, Ryan Z

2016-12-01

Early in their careers, many new surgeons lack the background and experience to understand essential components needed to build a surgical practice. Surgical resident education is often devoid of specific instruction on the business of medicine and practice management. In particular, hepatobiliary and pancreatic (HPB) surgeons require many key components to build a successful practice secondary to significant interdisciplinary coordination and a scope of complex surgery, which spans challenging benign and malignant disease processes. In the following, we describe the required clinical and financial components for developing a successful HPB surgery practice in the nonuniversity tertiary care center. We discuss significant financial considerations for understanding community need and hospital investment, contract establishment, billing, and coding. We summarize the structural elements and key personnel necessary for establishing an effectual HPB surgical team. This article provides useful, essential information for a new HPB surgeon looking to establish a surgical practice. It also provides insight for health-care administrators as to the value an HPB surgeon can bring to a hospital or health-care system.

Clinical predictive value of the ABCD2 score for early risk of stroke in patients who have had transient ischaemic attack and who present to an Australian tertiary hospital.

Science.gov (United States)

Sanders, Lauren M; Srikanth, Velandai K; Psihogios, Helen; Wong, Kitty K; Ramsay, David; Phan, Thanh G

2011-02-07

To determine the predictive value of the ABCD(2) score for early risk of stroke in Australian patients who have had transient ischaemic attack (TIA). Cohort study of 512 consecutive patients with suspected TIA referred by the emergency department to the acute stroke unit (in accordance with the TIA pathway) of an urban tertiary hospital in Melbourne, Victoria, between 1 June 2004 and 30 November 2007. Overall accuracy, estimated by the area under the curve (AUC) of receiver operating characteristic plots (of true positive rate v false positive rate), and sensitivity, specificity, predictive values and likelihood ratios at prespecified cut-off ABCD(2) scores for stroke within 2, 7 and 90 days. 24 patients were excluded because their symptoms lasted more than 24 hours. All included patients were reviewed by a stroke physician; TIA was confirmed in 301/488 (61.7%). Most (289/301; 96.0%) had complete follow-up. Stroke occurred in 4/292 patients (1.37%; 95% CI, 0.37%-3.47%) within 2 days and 7/289 (2.42%; 95% CI, 0.98%-4.93%) within 90 days; no patient had a stroke between 2 and 7 days. The AUCs for stroke in patients with confirmed TIA were 0.80 (95% CI, 0.68-0.91) and 0.62 (95% CI, 0.40-0.83) for stroke within 2 days and 90 days, respectively. At a cut-off of ≥ 5, the ABCD(2) score had modest specificity for stroke within 2 days (0.58) and 90 days (0.58), but positive predictive values (2 days, 0.03; 90 days, 0.04) and positive likelihood ratios (2 days, 2.40; 90 days, 1.71) were both poor. The score performed similarly poorly at other prespecified cut-off scores. Given its poor predictive value, the use of the ABCD(2) score alone may not be dependable for guiding clinical treatment decisions or service organisation in an Australian tertiary setting. Validation in other Australian settings is recommended before it can be applied with confidence.

Reflections on entrepreneurship education in African tertiary institutions

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K. Bawuah

2006-12-01

Full Text Available It is a well-established fact that several developed economies grew on the back of small businesses and entrepreneurial development. It stands to reason then that the development of Sub-Saharan Africa (SSA can also be catalysed by a rise in the number of entrepreneurs and entrepreneurial activity. In that general regard, this paper sought to investigate the state of entrepreneurship education in Sub-Saharan Africa (SSA. The method adopted in investigating this phenomenon was to critique the existing tertiary education entrepreneurship structures (where these existed at all and to proffer recommendations where anomalies were discovered. It came to light that despite the critical importance of entrepreneurs in the economic development of a nation, Sub-Saharan African (SSA countries have not fully developed strategies to tap this resource. What the countries have, are haphazard policies designed to promote the lesser or uneducated individuals in the informal sector into entrepreneurship. SSA educational leaders must find ways to structure their curricula so that all or most of their students can take courses in entrepreneurship. This is essential for SSA countries in order to move them from their present disadvantaged economic status, to greater economic and social development. A tentative syllabus for African tertiary education is proffered at the end of the article but its robustness needs to be tested.

Wage Inequalities: A Result of Different Levels and Fields of Tertiary Education?

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Darjan Petek

2017-03-01

Full Text Available In this article we examine the impact of tertiary education on the amounts of wages in Slovenia for 2011. We use micro data from the statistical survey Structure of Earnings Statistics and micro data from the survey of graduates from tertiary education. We found out that there are significant differences in the amounts of wages as regards the level and field of education. Region and activity of the company where the person is employed also plays an important role in wage determination. Also the effects of gender and public/private sector are statistically significant. Using the average wage per hour as dependent variable gives similar results as the average annual wages.

Extraterrestrial cause for the Cretaceous-Tertiary extinction

International Nuclear Information System (INIS)

Alvarez, L.W.; Alvarez, W.; Asaro, F.; Michel, H.V.

1980-01-01

Platinum metals are depleted in the earth's crust relative to their cosmic abundance; concentrations of these elements in deep-sea sediments may thus indicate influxes of extraterrestrial material. Deep-sea limestones exposed in Italy, Denmark, and New Zealand show iridium increases of about 30, 160, and 20 times, respectively, above the background level at precisely the time of the Cretaceous-Tertiary extinctions, 65 million years ago. Reasons are given to indicate that this iridium is of extraterrestrial origin, but did not come from a nearby supernova. A hypothesis is suggested which accounts for the extinctions and the iridium observations. Impact of a large earth-crossing asteroid would inject about 60 times the object's mass into the atmosphere as pulverized rock; a fraction of this dust would stay in the stratosphere for several years and be distributed worldwide. The resulting darkness would suppress photosynthesis, and the expected biological consequences match quite closely the extinctions observed in the paleontological record. One prediction of this hypothesis has been verified: the chemical composition of the boundary clay, which is thought to come from the stratospheric dust, is markedly different from that of clay mixed with the Cretaceous and Tertiary limestones, which are chemically similar to each other. Four different independent estimates of the diameter of the asteroid give values that lie in the range 10 +- 4 kilometers

Stratigraphic structure of the B1 Tertiary tectonostratigraphic unit in eastern Slovenia

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Bogomir Jelen

2002-06-01

Full Text Available High inconsistency and incoherence in the stratigraphy of the Slovenian upper Paleogene and lower Miocene have remained unsolved in the past 150 years. To solve the problem, we tried to rigorously conduct the authentic Galilei’s scientific method. Steps of logical and empirical verification confirmed the existence of the posited B1 Tertiary tectonostratigraphic unit, and a general chronostratigraphic model of new positional relationships of lithologic units resulted from rather good biochronostratigraphic resolution achieved by nannoplankton and planktonic foraminifera biostratigraphy. The application of principles of newly developed fields in science helped us to avoid errors in transmission of messages (to reduce noise from the source (rock to the concept formation,which had been done previously. This in turn has strongly reduced inconsistency andincoherence (high information entropy = uncertainty. The released amount of information enabled us to answer also questions that reached beyond the original difficulty, e.g.: is the tectonostratigraphic structure of eastern Slovenia a manifestation of plate tectonics processes, and of which ones, are theories of continental escape in the Alps and associated dissection and offset of the formerly uniform Slovenian-Hungarian Paleogene basin tenableor not, are then there in the B1 stratigraphic equivalents of the Hungarian Paleogene basin formations, where are the important Eocene / Oligocene, Paleogene / Neogene, Rupelian / Chattian and Kiscellian / Egerian boundaries in Slovenia, and is there acontinuation of the B1 in Croatia and in the Mid-Hungarian tectonic zone?

Prediction of beta-turns at over 80% accuracy based on an ensemble of predicted secondary structures and multiple alignments.

Science.gov (United States)

Zheng, Ce; Kurgan, Lukasz

2008-10-10

beta-turn is a secondary protein structure type that plays significant role in protein folding, stability, and molecular recognition. To date, several methods for prediction of beta-turns from protein sequences were developed, but they are characterized by relatively poor prediction quality. The novelty of the proposed sequence-based beta-turn predictor stems from the usage of a window based information extracted from four predicted three-state secondary structures, which together with a selected set of position specific scoring matrix (PSSM) values serve as an input to the support vector machine (SVM) predictor. We show that (1) all four predicted secondary structures are useful; (2) the most useful information extracted from the predicted secondary structure includes the structure of the predicted residue, secondary structure content in a window around the predicted residue, and features that indicate whether the predicted residue is inside a secondary structure segment; (3) the PSSM values of Asn, Asp, Gly, Ile, Leu, Met, Pro, and Val were among the top ranked features, which corroborates with recent studies. The Asn, Asp, Gly, and Pro indicate potential beta-turns, while the remaining four amino acids are useful to predict non-beta-turns. Empirical evaluation using three nonredundant datasets shows favorable Q total, Q predicted and MCC values when compared with over a dozen of modern competing methods. Our method is the first to break the 80% Q total barrier and achieves Q total = 80.9%, MCC = 0.47, and Q predicted higher by over 6% when compared with the second best method. We use feature selection to reduce the dimensionality of the feature vector used as the input for the proposed prediction method. The applied feature set is smaller by 86, 62 and 37% when compared with the second and two third-best (with respect to MCC) competing methods, respectively. Experiments show that the proposed method constitutes an improvement over the competing prediction

Structure Prediction and Analysis of Neuraminidase Sequence Variants

Science.gov (United States)

Thayer, Kelly M.

2016-01-01

Analyzing protein structure has become an integral aspect of understanding systems of biochemical import. The laboratory experiment endeavors to introduce protein folding to ascertain structures of proteins for which the structure is unavailable, as well as to critically evaluate the quality of the prediction obtained. The model system used is the…

Building a better fragment library for de novo protein structure prediction.

Directory of Open Access Journals (Sweden)

Saulo H P de Oliveira

Full Text Available Fragment-based approaches are the current standard for de novo protein structure prediction. These approaches rely on accurate and reliable fragment libraries to generate good structural models. In this work, we describe a novel method for structure fragment library generation and its application in fragment-based de novo protein structure prediction. The importance of correct testing procedures in assessing the quality of fragment libraries is demonstrated. In particular, the exclusion of homologs to the target from the libraries to correctly simulate a de novo protein structure prediction scenario, something which surprisingly is not always done. We demonstrate that fragments presenting different predominant predicted secondary structures should be treated differently during the fragment library generation step and that exhaustive and random search strategies should both be used. This information was used to develop a novel method, Flib. On a validation set of 41 structurally diverse proteins, Flib libraries presents both a higher precision and coverage than two of the state-of-the-art methods, NNMake and HHFrag. Flib also achieves better precision and coverage on the set of 275 protein domains used in the two previous experiments of the the Critical Assessment of Structure Prediction (CASP9 and CASP10. We compared Flib libraries against NNMake libraries in a structure prediction context. Of the 13 cases in which a correct answer was generated, Flib models were more accurate than NNMake models for 10. "Flib is available for download at: http://www.stats.ox.ac.uk/research/proteins/resources".

Building a Better Fragment Library for De Novo Protein Structure Prediction

Science.gov (United States)

de Oliveira, Saulo H. P.; Shi, Jiye; Deane, Charlotte M.

2015-01-01

Fragment-based approaches are the current standard for de novo protein structure prediction. These approaches rely on accurate and reliable fragment libraries to generate good structural models. In this work, we describe a novel method for structure fragment library generation and its application in fragment-based de novo protein structure prediction. The importance of correct testing procedures in assessing the quality of fragment libraries is demonstrated. In particular, the exclusion of homologs to the target from the libraries to correctly simulate a de novo protein structure prediction scenario, something which surprisingly is not always done. We demonstrate that fragments presenting different predominant predicted secondary structures should be treated differently during the fragment library generation step and that exhaustive and random search strategies should both be used. This information was used to develop a novel method, Flib. On a validation set of 41 structurally diverse proteins, Flib libraries presents both a higher precision and coverage than two of the state-of-the-art methods, NNMake and HHFrag. Flib also achieves better precision and coverage on the set of 275 protein domains used in the two previous experiments of the the Critical Assessment of Structure Prediction (CASP9 and CASP10). We compared Flib libraries against NNMake libraries in a structure prediction context. Of the 13 cases in which a correct answer was generated, Flib models were more accurate than NNMake models for 10. “Flib is available for download at: http://www.stats.ox.ac.uk/research/proteins/resources”. PMID:25901595

Seepage characteristics of the second tertiary combined model

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Huan ZHAO

2015-08-01

Full Text Available The second tertiary combined model experiment zone has been developed in Block B, Field L. The percolation feature of the second tertiary combined develop model shows great importance to rational and efficient development of the reservoir. In order to clearly illuminate its percolation feature, the typical reservoir numerical model is built by Eclipse, which is a reservoir numerical simulation software. The percolation features of original and added perforation interval under the second tertiary combined model are studied, and the variation features of general water-cut, recovery percentage, wellbore pressure, reservoir pressure and water saturation on condition of higher injection rate under the second tertiary combined model are analyzed. The research indicates that the second tertiary combined enhances the recovery of remaining oil on top of thick reservoir by developing and enhancing original perforation interval under water drive, then improves development results by polymer flooding, and gains higher recovery rate by synthetic action of water driver and polymer flooding.

Prediction of RNA secondary structure using generalized centroid estimators.

Science.gov (United States)

Hamada, Michiaki; Kiryu, Hisanori; Sato, Kengo; Mituyama, Toutai; Asai, Kiyoshi

2009-02-15

Recent studies have shown that the methods for predicting secondary structures of RNAs on the basis of posterior decoding of the base-pairing probabilities has an advantage with respect to prediction accuracy over the conventionally utilized minimum free energy methods. However, there is room for improvement in the objective functions presented in previous studies, which are maximized in the posterior decoding with respect to the accuracy measures for secondary structures. We propose novel estimators which improve the accuracy of secondary structure prediction of RNAs. The proposed estimators maximize an objective function which is the weighted sum of the expected number of the true positives and that of the true negatives of the base pairs. The proposed estimators are also improved versions of the ones used in previous works, namely CONTRAfold for secondary structure prediction from a single RNA sequence and McCaskill-MEA for common secondary structure prediction from multiple alignments of RNA sequences. We clarify the relations between the proposed estimators and the estimators presented in previous works, and theoretically show that the previous estimators include additional unnecessary terms in the evaluation measures with respect to the accuracy. Furthermore, computational experiments confirm the theoretical analysis by indicating improvement in the empirical accuracy. The proposed estimators represent extensions of the centroid estimators proposed in Ding et al. and Carvalho and Lawrence, and are applicable to a wide variety of problems in bioinformatics. Supporting information and the CentroidFold software are available online at: http://www.ncrna.org/software/centroidfold/.

Clinical course of a cohort of children with non-neurogenic daytime urinary incontinence symptoms followed at a tertiary center

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Adrienne Lebl

2016-04-01

Full Text Available Abstract Objective: To characterize a cohort of children with non-neurogenic daytime urinary incontinence followed-up in a tertiary center. Methods: Retrospective analysis of 50 medical records of children who had attained bladder control or minimum age of 5 years, using a structured protocol that included lower urinary tract dysfunction symptoms, comorbidities, associated manifestations, physical examination, voiding diary, complementary tests, therapeutic options, and clinical outcome, in accordance with the 2006 and 2014 International Children's Continence Society standardizations. Results: Female patients represented 86.0% of this sample. Mean age was 7.9 years and mean follow-up was 4.7 years. Urgency (56.0%, urgency incontinence (56.0%, urinary retention (8.0%, nocturnal enuresis (70.0%, urinary tract infections (62.0%, constipation (62.0%, and fecal incontinence (16.0% were the most prevalent symptoms and comorbidities. Ultrasound examinations showed alterations in 53.0% of the cases; the urodynamic study showed alterations in 94.7%. At the last follow-up, 32.0% of patients persisted with urinary incontinence. When assessing the diagnostic methods, 85% concordance was observed between the predictive diagnosis of overactive bladder attained through medical history plus non-invasive exams and the diagnosis of detrusor overactivity achieved through the invasive urodynamic study. Conclusions: This subgroup of patients with clinical characteristics of an overactive bladder, with no history of urinary tract infection, and normal urinary tract ultrasound and uroflowmetry, could start treatment without invasive studies even at a tertiary center. Approximately one-third of the patients treated at the tertiary level remained refractory to treatment.

Update on protein structure prediction: results of the 1995 IRBM workshop

DEFF Research Database (Denmark)

Hubbard, Tim; Tramontano, Anna; Hansen, Jan

1996-01-01

Computational tools for protein structure prediction are of great interest to molecular, structural and theoretical biologists due to a rapidly increasing number of protein sequences with no known structure. In October 1995, a workshop was held at IRBM to predict as much as possible about a numbe...

Update on protein structure prediction: results of the 1995 IRBM workshop

DEFF Research Database (Denmark)

Hubbard, Tim; Tramontano, Anna; Hansen, Jan

1996-01-01

Computational tools for protein structure prediction are of great interest to molecular, structural and theoretical biologists due to a rapidly increasing number of protein sequences with no known structure. In October 1995, a workshop was held at IRBM to predict as much as possible about a number...

Predicting nucleic acid binding interfaces from structural models of proteins.

Science.gov (United States)

Dror, Iris; Shazman, Shula; Mukherjee, Srayanta; Zhang, Yang; Glaser, Fabian; Mandel-Gutfreund, Yael

2012-02-01

The function of DNA- and RNA-binding proteins can be inferred from the characterization and accurate prediction of their binding interfaces. However, the main pitfall of various structure-based methods for predicting nucleic acid binding function is that they are all limited to a relatively small number of proteins for which high-resolution three-dimensional structures are available. In this study, we developed a pipeline for extracting functional electrostatic patches from surfaces of protein structural models, obtained using the I-TASSER protein structure predictor. The largest positive patches are extracted from the protein surface using the patchfinder algorithm. We show that functional electrostatic patches extracted from an ensemble of structural models highly overlap the patches extracted from high-resolution structures. Furthermore, by testing our pipeline on a set of 55 known nucleic acid binding proteins for which I-TASSER produces high-quality models, we show that the method accurately identifies the nucleic acids binding interface on structural models of proteins. Employing a combined patch approach we show that patches extracted from an ensemble of models better predicts the real nucleic acid binding interfaces compared with patches extracted from independent models. Overall, these results suggest that combining information from a collection of low-resolution structural models could be a valuable approach for functional annotation. We suggest that our method will be further applicable for predicting other functional surfaces of proteins with unknown structure. Copyright © 2011 Wiley Periodicals, Inc.

Prediction of beta-turns at over 80% accuracy based on an ensemble of predicted secondary structures and multiple alignments

Directory of Open Access Journals (Sweden)

Kurgan Lukasz

2008-10-01

Full Text Available Abstract Background β-turn is a secondary protein structure type that plays significant role in protein folding, stability, and molecular recognition. To date, several methods for prediction of β-turns from protein sequences were developed, but they are characterized by relatively poor prediction quality. The novelty of the proposed sequence-based β-turn predictor stems from the usage of a window based information extracted from four predicted three-state secondary structures, which together with a selected set of position specific scoring matrix (PSSM values serve as an input to the support vector machine (SVM predictor. Results We show that (1 all four predicted secondary structures are useful; (2 the most useful information extracted from the predicted secondary structure includes the structure of the predicted residue, secondary structure content in a window around the predicted residue, and features that indicate whether the predicted residue is inside a secondary structure segment; (3 the PSSM values of Asn, Asp, Gly, Ile, Leu, Met, Pro, and Val were among the top ranked features, which corroborates with recent studies. The Asn, Asp, Gly, and Pro indicate potential β-turns, while the remaining four amino acids are useful to predict non-β-turns. Empirical evaluation using three nonredundant datasets shows favorable Qtotal, Qpredicted and MCC values when compared with over a dozen of modern competing methods. Our method is the first to break the 80% Qtotal barrier and achieves Qtotal = 80.9%, MCC = 0.47, and Qpredicted higher by over 6% when compared with the second best method. We use feature selection to reduce the dimensionality of the feature vector used as the input for the proposed prediction method. The applied feature set is smaller by 86, 62 and 37% when compared with the second and two third-best (with respect to MCC competing methods, respectively. Conclusion Experiments show that the proposed method constitutes an

QCD predictions for weak neutral current structure functions

International Nuclear Information System (INIS)

Wu Jimin

1987-01-01

Employing the analytic expression (to the next leading order) for non-singlet component of structure function which the author got from QCD theory and putting recent experiment result of neutral current structure function at Q 2 = 11 (GeV/C) 2 as input, the QCD prediction for neutral current structure function of their scaling violation behaviours was given

Predicting protein structures with a multiplayer online game.

Science.gov (United States)

Cooper, Seth; Khatib, Firas; Treuille, Adrien; Barbero, Janos; Lee, Jeehyung; Beenen, Michael; Leaver-Fay, Andrew; Baker, David; Popović, Zoran; Players, Foldit

2010-08-05

People exert large amounts of problem-solving effort playing computer games. Simple image- and text-recognition tasks have been successfully 'crowd-sourced' through games, but it is not clear if more complex scientific problems can be solved with human-directed computing. Protein structure prediction is one such problem: locating the biologically relevant native conformation of a protein is a formidable computational challenge given the very large size of the search space. Here we describe Foldit, a multiplayer online game that engages non-scientists in solving hard prediction problems. Foldit players interact with protein structures using direct manipulation tools and user-friendly versions of algorithms from the Rosetta structure prediction methodology, while they compete and collaborate to optimize the computed energy. We show that top-ranked Foldit players excel at solving challenging structure refinement problems in which substantial backbone rearrangements are necessary to achieve the burial of hydrophobic residues. Players working collaboratively develop a rich assortment of new strategies and algorithms; unlike computational approaches, they explore not only the conformational space but also the space of possible search strategies. The integration of human visual problem-solving and strategy development capabilities with traditional computational algorithms through interactive multiplayer games is a powerful new approach to solving computationally-limited scientific problems.

(PS)2: protein structure prediction server version 3.0.

Science.gov (United States)

Huang, Tsun-Tsao; Hwang, Jenn-Kang; Chen, Chu-Huang; Chu, Chih-Sheng; Lee, Chi-Wen; Chen, Chih-Chieh

2015-07-01

Protein complexes are involved in many biological processes. Examining coupling between subunits of a complex would be useful to understand the molecular basis of protein function. Here, our updated (PS)(2) web server predicts the three-dimensional structures of protein complexes based on comparative modeling; furthermore, this server examines the coupling between subunits of the predicted complex by combining structural and evolutionary considerations. The predicted complex structure could be indicated and visualized by Java-based 3D graphics viewers and the structural and evolutionary profiles are shown and compared chain-by-chain. For each subunit, considerations with or without the packing contribution of other subunits cause the differences in similarities between structural and evolutionary profiles, and these differences imply which form, complex or monomeric, is preferred in the biological condition for the subunit. We believe that the (PS)(2) server would be a useful tool for biologists who are interested not only in the structures of protein complexes but also in the coupling between subunits of the complexes. The (PS)(2) is freely available at http://ps2v3.life.nctu.edu.tw/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Compound Structure-Independent Activity Prediction in High-Dimensional Target Space.

Science.gov (United States)

Balfer, Jenny; Hu, Ye; Bajorath, Jürgen

2014-08-01

Profiling of compound libraries against arrays of targets has become an important approach in pharmaceutical research. The prediction of multi-target compound activities also represents an attractive task for machine learning with potential for drug discovery applications. Herein, we have explored activity prediction in high-dimensional target space. Different types of models were derived to predict multi-target activities. The models included naïve Bayesian (NB) and support vector machine (SVM) classifiers based upon compound structure information and NB models derived on the basis of activity profiles, without considering compound structure. Because the latter approach can be applied to incomplete training data and principally depends on the feature independence assumption, SVM modeling was not applicable in this case. Furthermore, iterative hybrid NB models making use of both activity profiles and compound structure information were built. In high-dimensional target space, NB models utilizing activity profile data were found to yield more accurate activity predictions than structure-based NB and SVM models or hybrid models. An in-depth analysis of activity profile-based models revealed the presence of correlation effects across different targets and rationalized prediction accuracy. Taken together, the results indicate that activity profile information can be effectively used to predict the activity of test compounds against novel targets. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

RNA folding: structure prediction, folding kinetics and ion electrostatics.

Science.gov (United States)

Tan, Zhijie; Zhang, Wenbing; Shi, Yazhou; Wang, Fenghua

2015-01-01

Beyond the "traditional" functions such as gene storage, transport and protein synthesis, recent discoveries reveal that RNAs have important "new" biological functions including the RNA silence and gene regulation of riboswitch. Such functions of noncoding RNAs are strongly coupled to the RNA structures and proper structure change, which naturally leads to the RNA folding problem including structure prediction and folding kinetics. Due to the polyanionic nature of RNAs, RNA folding structure, stability and kinetics are strongly coupled to the ion condition of solution. The main focus of this chapter is to review the recent progress in the three major aspects in RNA folding problem: structure prediction, folding kinetics and ion electrostatics. This chapter will introduce both the recent experimental and theoretical progress, while emphasize the theoretical modelling on the three aspects in RNA folding.

Enthalpy-Driven RNA Folding: Single-Molecule Thermodynamics of Tetraloop–Receptor Tertiary Interaction†

Science.gov (United States)

Fiore, Julie L.; Kraemer, Benedikt; Koberling, Felix; Edmann, Rainer; Nesbitt, David J.

2010-01-01

RNA folding thermodynamics are crucial for structure prediction, which requires characterization of both enthalpic and entropic contributions of tertiary motifs to conformational stability. We explore the temperature dependence of RNA folding due to the ubiquitous GAAA tetraloop–receptor docking interaction, exploiting immobilized and freely diffusing single-molecule fluorescence resonance energy transfer (smFRET) methods. The equilibrium constant for intramolecular docking is obtained as a function of temperature (T = 21–47 °C), from which a van’t Hoff analysis yields the enthalpy (ΔH°) and entropy (ΔS°) of docking. Tetraloop–receptor docking is significantly exothermic and entropically unfavorable in 1 mM MgCl2 and 100 mM NaCl, with excellent agreement between immobilized (ΔH° = −17.4 ± 1.6 kcal/mol, and ΔS° = −56.2 ± 5.4 cal mol−1 K−1) and freely diffusing (ΔH° = −17.2 ± 1.6 kcal/mol, and ΔS° = −55.9 ± 5.2 cal mol−1 K−1) species. Kinetic heterogeneity in the tetraloop–receptor construct is unaffected over the temperature range investigated, indicating a large energy barrier for interconversion between the actively docking and nondocking subpopulations. Formation of the tetraloop–receptor interaction can account for ~60% of the ΔH° and ΔS° of P4–P6 domain folding in the Tetrahymena ribozyme, suggesting that it may act as a thermodynamic clamp for the domain. Comparison of the isolated tetraloop–receptor and other tertiary folding thermodynamics supports a theme that enthalpy- versus entropy-driven folding is determined by the number of hydrogen bonding and base stacking interactions. PMID:19186984

Constraint Logic Programming approach to protein structure prediction

Directory of Open Access Journals (Sweden)

Fogolari Federico

2004-11-01

Full Text Available Abstract Background The protein structure prediction problem is one of the most challenging problems in biological sciences. Many approaches have been proposed using database information and/or simplified protein models. The protein structure prediction problem can be cast in the form of an optimization problem. Notwithstanding its importance, the problem has very seldom been tackled by Constraint Logic Programming, a declarative programming paradigm suitable for solving combinatorial optimization problems. Results Constraint Logic Programming techniques have been applied to the protein structure prediction problem on the face-centered cube lattice model. Molecular dynamics techniques, endowed with the notion of constraint, have been also exploited. Even using a very simplified model, Constraint Logic Programming on the face-centered cube lattice model allowed us to obtain acceptable results for a few small proteins. As a test implementation their (known secondary structure and the presence of disulfide bridges are used as constraints. Simplified structures obtained in this way have been converted to all atom models with plausible structure. Results have been compared with a similar approach using a well-established technique as molecular dynamics. Conclusions The results obtained on small proteins show that Constraint Logic Programming techniques can be employed for studying protein simplified models, which can be converted into realistic all atom models. The advantage of Constraint Logic Programming over other, much more explored, methodologies, resides in the rapid software prototyping, in the easy way of encoding heuristics, and in exploiting all the advances made in this research area, e.g. in constraint propagation and its use for pruning the huge search space.

Constraint Logic Programming approach to protein structure prediction.

Science.gov (United States)

Dal Palù, Alessandro; Dovier, Agostino; Fogolari, Federico

2004-11-30

The protein structure prediction problem is one of the most challenging problems in biological sciences. Many approaches have been proposed using database information and/or simplified protein models. The protein structure prediction problem can be cast in the form of an optimization problem. Notwithstanding its importance, the problem has very seldom been tackled by Constraint Logic Programming, a declarative programming paradigm suitable for solving combinatorial optimization problems. Constraint Logic Programming techniques have been applied to the protein structure prediction problem on the face-centered cube lattice model. Molecular dynamics techniques, endowed with the notion of constraint, have been also exploited. Even using a very simplified model, Constraint Logic Programming on the face-centered cube lattice model allowed us to obtain acceptable results for a few small proteins. As a test implementation their (known) secondary structure and the presence of disulfide bridges are used as constraints. Simplified structures obtained in this way have been converted to all atom models with plausible structure. Results have been compared with a similar approach using a well-established technique as molecular dynamics. The results obtained on small proteins show that Constraint Logic Programming techniques can be employed for studying protein simplified models, which can be converted into realistic all atom models. The advantage of Constraint Logic Programming over other, much more explored, methodologies, resides in the rapid software prototyping, in the easy way of encoding heuristics, and in exploiting all the advances made in this research area, e.g. in constraint propagation and its use for pruning the huge search space.

Factors influencing phase-disengagement rates in solvent-extraction systems employing tertiary amine extractants

International Nuclear Information System (INIS)

Moyer, B.A.; McDowell, W.J.

1981-01-01

The primary purpose of the present investigation was to examine the effects of amine size and structure on phase disengagement. Nine commercial tertiary amines were tested together with four laboratory-quality amines for uranium extraction and both organic-continuous (OC) and aqueous-continuous (AC) phase disengagement under Amex-type conditions. Synthetic acid sulfate solutions with and without added colloidal silica and actual ore leach solutions were used as the aqueous phases. Phase disengagement results were correlated with amine size and branching and solution wetting behavior on a silicate (glass) surface. The results suggest that the performance of some Amex systems may be improved by using branched chain tertiary amine extractants of higher molecular weight than are now normally used

Free energy minimization to predict RNA secondary structures and computational RNA design.

Science.gov (United States)

Churkin, Alexander; Weinbrand, Lina; Barash, Danny

2015-01-01

Determining the RNA secondary structure from sequence data by computational predictions is a long-standing problem. Its solution has been approached in two distinctive ways. If a multiple sequence alignment of a collection of homologous sequences is available, the comparative method uses phylogeny to determine conserved base pairs that are more likely to form as a result of billions of years of evolution than by chance. In the case of single sequences, recursive algorithms that compute free energy structures by using empirically derived energy parameters have been developed. This latter approach of RNA folding prediction by energy minimization is widely used to predict RNA secondary structure from sequence. For a significant number of RNA molecules, the secondary structure of the RNA molecule is indicative of its function and its computational prediction by minimizing its free energy is important for its functional analysis. A general method for free energy minimization to predict RNA secondary structures is dynamic programming, although other optimization methods have been developed as well along with empirically derived energy parameters. In this chapter, we introduce and illustrate by examples the approach of free energy minimization to predict RNA secondary structures.

Protein Secondary Structure Prediction Using Deep Convolutional Neural Fields.

Science.gov (United States)

Wang, Sheng; Peng, Jian; Ma, Jianzhu; Xu, Jinbo

2016-01-11

Protein secondary structure (SS) prediction is important for studying protein structure and function. When only the sequence (profile) information is used as input feature, currently the best predictors can obtain ~80% Q3 accuracy, which has not been improved in the past decade. Here we present DeepCNF (Deep Convolutional Neural Fields) for protein SS prediction. DeepCNF is a Deep Learning extension of Conditional Neural Fields (CNF), which is an integration of Conditional Random Fields (CRF) and shallow neural networks. DeepCNF can model not only complex sequence-structure relationship by a deep hierarchical architecture, but also interdependency between adjacent SS labels, so it is much more powerful than CNF. Experimental results show that DeepCNF can obtain ~84% Q3 accuracy, ~85% SOV score, and ~72% Q8 accuracy, respectively, on the CASP and CAMEO test proteins, greatly outperforming currently popular predictors. As a general framework, DeepCNF can be used to predict other protein structure properties such as contact number, disorder regions, and solvent accessibility.

The Phyre2 web portal for protein modeling, prediction and analysis.

Science.gov (United States)

Kelley, Lawrence A; Mezulis, Stefans; Yates, Christopher M; Wass, Mark N; Sternberg, Michael J E

2015-06-01

Phyre2 is a suite of tools available on the web to predict and analyze protein structure, function and mutations. The focus of Phyre2 is to provide biologists with a simple and intuitive interface to state-of-the-art protein bioinformatics tools. Phyre2 replaces Phyre, the original version of the server for which we previously published a paper in Nature Protocols. In this updated protocol, we describe Phyre2, which uses advanced remote homology detection methods to build 3D models, predict ligand binding sites and analyze the effect of amino acid variants (e.g., nonsynonymous SNPs (nsSNPs)) for a user's protein sequence. Users are guided through results by a simple interface at a level of detail they determine. This protocol will guide users from submitting a protein sequence to interpreting the secondary and tertiary structure of their models, their domain composition and model quality. A range of additional available tools is described to find a protein structure in a genome, to submit large number of sequences at once and to automatically run weekly searches for proteins that are difficult to model. The server is available at http://www.sbg.bio.ic.ac.uk/phyre2. A typical structure prediction will be returned between 30 min and 2 h after submission.

Evolutionary Structure Prediction of Stoichiometric Compounds

Science.gov (United States)

Zhu, Qiang; Oganov, Artem

2014-03-01

In general, for a given ionic compound AmBn\\ at ambient pressure condition, its stoichiometry reflects the valence state ratio between per chemical specie (i.e., the charges for each anion and cation). However, compounds under high pressure exhibit significantly behavior, compared to those analogs at ambient condition. Here we developed a method to solve the crystal structure prediction problem based on the evolutionary algorithms, which can predict both the stable compounds and their crystal structures at arbitrary P,T-conditions, given just the set of chemical elements. By applying this method to a wide range of binary ionic systems (Na-Cl, Mg-O, Xe-O, Cs-F, etc), we discovered a lot of compounds with brand new stoichimetries which can become thermodynamically stable. Further electronic structure analysis on these novel compounds indicates that several factors can contribute to this extraordinary phenomenon: (1) polyatomic anions; (2) free electron localization; (3) emergence of new valence states; (4) metallization. In particular, part of the results have been confirmed by experiment, which warrants that this approach can play a crucial role in new materials design under extreme pressure conditions. This work is funded by DARPA (Grants No. W31P4Q1210008 and W31P4Q1310005), NSF (EAR-1114313 and DMR-1231586).

Molecular identification of aiiA homologous gene from endophytic Enterobacter species and in silico analysis of putative tertiary structure of AHL-lactonase.

Science.gov (United States)

Rajesh, P S; Rai, V Ravishankar

2014-01-03

The aiiA homologous gene known to encode AHL- lactonase enzyme which hydrolyze the N-acylhomoserine lactone (AHL) quorum sensing signaling molecules produced by Gram negative bacteria. In this study, the degradation of AHL molecules was determined by cell-free lysate of endophytic Enterobacter species. The percentage of quorum quenching was confirmed and quantified by HPLC method (pEnterobacter asburiae VT65, Enterobacter aerogenes VT66 and Enterobacter ludwigii VT70 strains. Sequence alignment analysis revealed the presence of two zinc binding sites, "HXHXDH" motif as well as tyrosine residue at the position 194. Based on known template available at Swiss-Model, putative tertiary structure of AHL-lactonase was constructed. The result showed that novel endophytic strains of Enterobacter genera encode the novel aiiA homologous gene and its structural importance for future study. Copyright © 2013 Elsevier Inc. All rights reserved.

Social media use profile, social skills, and nurse-patient interaction among Registered Nurses in tertiary hospitals: A structural equation model analysis.

Science.gov (United States)

Mariano, Micah Celine O; Maniego, John Christian M; Manila, Hariette Lou Marie D; Mapanoo, Ram Cedrick C; Maquiran, Kerwin Miguel A; Macindo, John Rey B; Tejero, Lourdes Marie S; Torres, Gian Carlo S

2018-04-01

Social media has become increasingly important over the past decades and has been integrated in various environments, including the healthcare setting. Yet, the influence of social media use on the social skills and nurse-patient interaction of nurses is an area in nursing that requires further studies. This study determined the interrelationships among social media use profile, social skills, and nurse-patient interaction of Registered Nurses in tertiary hospitals. Employing structural equation modeling, a descriptive-correlational study was conducted among 212 consecutively-selected nurses from two tertiary hospitals. Consenting respondents completed a two-part survey composed of the respondent profile sheet and the Social Skills Inventory. The respondent profile sheet assessed demographic profile and social media use profile in terms of the mode, frequency, and duration of utilization. Three trained team members observed each nurse-patient dyad and completed the Nurse-Patient Bonding Instrument. A good fit model illustrated the negative effects of frequent social media use to patient openness (β = -0.18, p social media on a daily basis, however, positively affected both dimensions of social skills. Accessing social media platforms using non-handheld devices showed the most influential positive effects to social skills and nurse-patient interaction. Additionally, although verbal social skills positively affected most dimensions of nurse-patient interaction, non-verbal social skills negatively influenced patient engagement (β = -0.19, p = 0.019) and nurse openness (β = -0.38, p ≤ 0.05). The structural model illustrates the effects of using social media on the social skills and nurse-patient interaction of nurses and emphasizes the need for implementing institutional policies on the judicious use and application of social media in the workplace. Further, social skills development programs geared toward having a balanced social skill must

Predicted crystal structures of molybdenum under high pressure

Energy Technology Data Exchange (ETDEWEB)

Wang, Bing; Zhang, Guang Biao [Institute for Computational Materials Science, School of Physics and Electronics, Henan University, Kaifeng 475004 (China); Wang, Yuan Xu, E-mail: wangyx@henu.edu.cn [Institute for Computational Materials Science, School of Physics and Electronics, Henan University, Kaifeng 475004 (China); Guizhou Provincial Key Laboratory of Computational Nano-Material Science, Institute of Applied Physics, Guizhou Normal College, Guiyang 550018 (China)

2013-04-15

Highlights: ► A double-hexagonal close-packed (dhcp) structure of molybdenum is predicted. ► Calculated acoustic velocity confirms the bcc–dhcp phase transition at 660 GPa. ► The valence electrons of dhcp Mo are mostly localized in the interstitial sites. -- Abstract: The high-pressure structures of molybdenum (Mo) at zero temperature have been extensively explored through the newly developed particle swarm optimization (PSO) algorithm on crystal structural prediction. All the experimental and earlier theoretical structures were successfully reproduced in certain pressure ranges, validating our methodology in application to Mo. A double-hexagonal close-packed (dhcp) structure found by Mikhaylushkin et al. (2008) [12] is confirmed by the present PSO calculations. The lattice parameters and physical properties of the dhcp phase were investigated based on first principles calculations. The phase transition occurs only from bcc phase to dhcp phase at 660 GPa and at zero temperature. The calculated acoustic velocities also indicate a transition from the bcc to dhcp phases for Mo. More intriguingly, the calculated density of states (DOS) shows that the dhcp structure remains metallic. The calculated electron density difference (EDD) reveals that its valence electrons are localized in the interstitial regions.

Ab initio/GIAO-CCSD(T) (13)C NMR study of the rearrangement and dynamic aspects of rapidly equilibrating tertiary carbocations, C6H13(+) and C7H15(+).

Science.gov (United States)

Olah, George A; Prakash, G K Surya; Rasul, Golam

2016-01-05

The rearrangement pathways of the equilibrating tertiary carbocations, 2,3-dimethyl-2-butyl cation (C6H13(+), 1), 2,3,3-trimethyl-2-butyl cation (C7H15(+), 5) and 2,3-dimethyl-2-pentyl cation (C7H15(+), 8 and 9) were investigated using the ab initio/GIAO-CCSD(T) (13)C NMR method. Comparing the calculated and experimental (13)C NMR chemical shifts of a series of carbocations indicates that excellent prediction of δ(13)C could be achieved through scaling. In the case of symmetrical equilibrating cations (1 and 5) the Wagner-Meerwein 1,2-hydride and 1,2-methide shifts, respectively, produce the same structure. This indicates that the overall (13)C NMR chemical shifts are conserved and independent of temperature. However, in the case of unsymmetrical equilibrating cations (8 and 9) the Wagner-Meerwein shift produces different tertiary structures, which have slightly different thermodynamic stabilities and, thus, different spectra. At the MP4(SDTQ)/cc-pVTZ//MP2/cc-pVTZ + ZPE level structure 8 is only 90 calories/mol more stable than structure 9. Based on computed (13)C NMR chemical shift calculations, mole fractions of these isomers were determined by assuming the observed chemical shifts are due to the weighted average of the chemical shifts of the static ions. © 2015 Wiley Periodicals, Inc.

Contingency Table Browser - prediction of early stage protein structure.

Science.gov (United States)

Kalinowska, Barbara; Krzykalski, Artur; Roterman, Irena

2015-01-01

The Early Stage (ES) intermediate represents the starting structure in protein folding simulations based on the Fuzzy Oil Drop (FOD) model. The accuracy of FOD predictions is greatly dependent on the accuracy of the chosen intermediate. A suitable intermediate can be constructed using the sequence-structure relationship information contained in the so-called contingency table - this table expresses the likelihood of encountering various structural motifs for each tetrapeptide fragment in the amino acid sequence. The limited accuracy with which such structures could previously be predicted provided the motivation for a more indepth study of the contingency table itself. The Contingency Table Browser is a tool which can visualize, search and analyze the table. Our work presents possible applications of Contingency Table Browser, among them - analysis of specific protein sequences from the point of view of their structural ambiguity.

G-LoSA for Prediction of Protein-Ligand Binding Sites and Structures.

Science.gov (United States)

Lee, Hui Sun; Im, Wonpil

2017-01-01

Recent advances in high-throughput structure determination and computational protein structure prediction have significantly enriched the universe of protein structure. However, there is still a large gap between the number of available protein structures and that of proteins with annotated function in high accuracy. Computational structure-based protein function prediction has emerged to reduce this knowledge gap. The identification of a ligand binding site and its structure is critical to the determination of a protein's molecular function. We present a computational methodology for predicting small molecule ligand binding site and ligand structure using G-LoSA, our protein local structure alignment and similarity measurement tool. All the computational procedures described here can be easily implemented using G-LoSA Toolkit, a package of standalone software programs and preprocessed PDB structure libraries. G-LoSA and G-LoSA Toolkit are freely available to academic users at http://compbio.lehigh.edu/GLoSA . We also illustrate a case study to show the potential of our template-based approach harnessing G-LoSA for protein function prediction.

Assessment of performance and utility of mortality prediction models in a single Indian mixed tertiary intensive care unit.

Science.gov (United States)

Sathe, Prachee M; Bapat, Sharda N

2014-01-01

To assess the performance and utility of two mortality prediction models viz. Acute Physiology and Chronic Health Evaluation II (APACHE II) and Simplified Acute Physiology Score II (SAPS II) in a single Indian mixed tertiary intensive care unit (ICU). Secondary objectives were bench-marking and setting a base line for research. In this observational cohort, data needed for calculation of both scores were prospectively collected for all consecutive admissions to 28-bedded ICU in the year 2011. After excluding readmissions, discharges within 24 h and age <18 years, the records of 1543 patients were analyzed using appropriate statistical methods. Both models overpredicted mortality in this cohort [standardized mortality ratio (SMR) 0.88 ± 0.05 and 0.95 ± 0.06 using APACHE II and SAPS II respectively]. Patterns of predicted mortality had strong association with true mortality (R (2) = 0.98 for APACHE II and R (2) = 0.99 for SAPS II). Both models performed poorly in formal Hosmer-Lemeshow goodness-of-fit testing (Chi-square = 12.8 (P = 0.03) for APACHE II, Chi-square = 26.6 (P = 0.001) for SAPS II) but showed good discrimination (area under receiver operating characteristic curve 0.86 ± 0.013 SE (P < 0.001) and 0.83 ± 0.013 SE (P < 0.001) for APACHE II and SAPS II, respectively). There were wide variations in SMRs calculated for subgroups based on International Classification of Disease, 10(th) edition (standard deviation ± 0.27 for APACHE II and 0.30 for SAPS II). Lack of fit of data to the models and wide variation in SMRs in subgroups put a limitation on utility of these models as tools for assessing quality of care and comparing performances of different units without customization. Considering comparable performance and simplicity of use, efforts should be made to adapt SAPS II.

LocARNA-P: Accurate boundary prediction and improved detection of structural RNAs

DEFF Research Database (Denmark)

Will, Sebastian; Joshi, Tejal; Hofacker, Ivo L.

2012-01-01

Current genomic screens for noncoding RNAs (ncRNAs) predict a large number of genomic regions containing potential structural ncRNAs. The analysis of these data requires highly accurate prediction of ncRNA boundaries and discrimination of promising candidate ncRNAs from weak predictions. Existing...... methods struggle with these goals because they rely on sequence-based multiple sequence alignments, which regularly misalign RNA structure and therefore do not support identification of structural similarities. To overcome this limitation, we compute columnwise and global reliabilities of alignments based...... on sequence and structure similarity; we refer to these structure-based alignment reliabilities as STARs. The columnwise STARs of alignments, or STAR profiles, provide a versatile tool for the manual and automatic analysis of ncRNAs. In particular, we improve the boundary prediction of the widely used nc...

Structural protein descriptors in 1-dimension and their sequence-based predictions.

Science.gov (United States)

Kurgan, Lukasz; Disfani, Fatemeh Miri

2011-09-01

The last few decades observed an increasing interest in development and application of 1-dimensional (1D) descriptors of protein structure. These descriptors project 3D structural features onto 1D strings of residue-wise structural assignments. They cover a wide-range of structural aspects including conformation of the backbone, burying depth/solvent exposure and flexibility of residues, and inter-chain residue-residue contacts. We perform first-of-its-kind comprehensive comparative review of the existing 1D structural descriptors. We define, review and categorize ten structural descriptors and we also describe, summarize and contrast over eighty computational models that are used to predict these descriptors from the protein sequences. We show that the majority of the recent sequence-based predictors utilize machine learning models, with the most popular being neural networks, support vector machines, hidden Markov models, and support vector and linear regressions. These methods provide high-throughput predictions and most of them are accessible to a non-expert user via web servers and/or stand-alone software packages. We empirically evaluate several recent sequence-based predictors of secondary structure, disorder, and solvent accessibility descriptors using a benchmark set based on CASP8 targets. Our analysis shows that the secondary structure can be predicted with over 80% accuracy and segment overlap (SOV), disorder with over 0.9 AUC, 0.6 Matthews Correlation Coefficient (MCC), and 75% SOV, and relative solvent accessibility with PCC of 0.7 and MCC of 0.6 (0.86 when homology is used). We demonstrate that the secondary structure predicted from sequence without the use of homology modeling is as good as the structure extracted from the 3D folds predicted by top-performing template-based methods.

Tertiary Education in the Czech Republic: The Pathway to Change

Science.gov (United States)

Pesik, Richard; Gounko, Tatiana

2011-01-01

This article analyzes recent policy proposals to reform Czech tertiary education. A brief overview of the evolution of Czech tertiary education presents the background against which emerging policy trends in education are examined. We relate the changes in tertiary education to the policy framework and recommendations of the OECD, underpinned by…

Advances in Rosetta structure prediction for difficult molecular-replacement problems

International Nuclear Information System (INIS)

DiMaio, Frank

2013-01-01

Modeling advances using Rosetta structure prediction to aid in solving difficult molecular-replacement problems are discussed. Recent work has shown the effectiveness of structure-prediction methods in solving difficult molecular-replacement problems. The Rosetta protein structure modeling suite can aid in the solution of difficult molecular-replacement problems using templates from 15 to 25% sequence identity; Rosetta refinement guided by noisy density has consistently led to solved structures where other methods fail. In this paper, an overview of the use of Rosetta for these difficult molecular-replacement problems is provided and new modeling developments that further improve model quality are described. Several variations to the method are introduced that significantly reduce the time needed to generate a model and the sampling required to improve the starting template. The improvements are benchmarked on a set of nine difficult cases and it is shown that this improved method obtains consistently better models in less running time. Finally, strategies for best using Rosetta to solve difficult molecular-replacement problems are presented and future directions for the role of structure-prediction methods in crystallography are discussed

Validation of Molecular Dynamics Simulations for Prediction of Three-Dimensional Structures of Small Proteins.

Science.gov (United States)

Kato, Koichi; Nakayoshi, Tomoki; Fukuyoshi, Shuichi; Kurimoto, Eiji; Oda, Akifumi

2017-10-12

Although various higher-order protein structure prediction methods have been developed, almost all of them were developed based on the three-dimensional (3D) structure information of known proteins. Here we predicted the short protein structures by molecular dynamics (MD) simulations in which only Newton's equations of motion were used and 3D structural information of known proteins was not required. To evaluate the ability of MD simulationto predict protein structures, we calculated seven short test protein (10-46 residues) in the denatured state and compared their predicted and experimental structures. The predicted structure for Trp-cage (20 residues) was close to the experimental structure by 200-ns MD simulation. For proteins shorter or longer than Trp-cage, root-mean square deviation values were larger than those for Trp-cage. However, secondary structures could be reproduced by MD simulations for proteins with 10-34 residues. Simulations by replica exchange MD were performed, but the results were similar to those from normal MD simulations. These results suggest that normal MD simulations can roughly predict short protein structures and 200-ns simulations are frequently sufficient for estimating the secondary structures of protein (approximately 20 residues). Structural prediction method using only fundamental physical laws are useful for investigating non-natural proteins, such as primitive proteins and artificial proteins for peptide-based drug delivery systems.

2. Tertiary Foraminifera

NARCIS (Netherlands)

Umbgrove, J.H.F.

1931-01-01

In his review of the palaeozoology of Java, K. Martin could in 1919, record 49 foraminifera from tertiary strata of Java, on the strength of a critical study of the existant literature, and especially on the strength of his own studies and knowledge of the above mentioned fossils (Bibl. 49). In

Predicting Protein Secondary Structure with Markov Models

DEFF Research Database (Denmark)

Fischer, Paul; Larsen, Simon; Thomsen, Claus

2004-01-01

we are considering here, is to predict the secondary structure from the primary one. To this end we train a Markov model on training data and then use it to classify parts of unknown protein sequences as sheets, helices or coils. We show how to exploit the directional information contained...... in the Markov model for this task. Classifications that are purely based on statistical models might not always be biologically meaningful. We present combinatorial methods to incorporate biological background knowledge to enhance the prediction performance....

Limits and opportunities of marketeering tertiary education in post-colonial Zimbabwe

OpenAIRE

Patrick Sibanda

2016-01-01

This paper intended to assess the impact of marketeering tertiary education in Zimbabwe. The paper revealed that marketeering of tertiary education in Zimbabwe has drastically impacted on access to higher education and training. Poor and vulnerable students have found it difficult to access tertiary education due to escalating commercialized fees. Literature indicates that, even in developed countries like UK, marketeering tertiary education has led to decreased enrolments, diminishing prospe...

The equivalent thermal conductivity of lattice core sandwich structure: A predictive model

International Nuclear Information System (INIS)

Cheng, Xiangmeng; Wei, Kai; He, Rujie; Pei, Yongmao; Fang, Daining

2016-01-01

Highlights: • A predictive model of the equivalent thermal conductivity was established. • Both the heat conduction and radiation were considered. • The predictive results were in good agreement with experiment and FEM. • Some methods for improving the thermal protection performance were proposed. - Abstract: The equivalent thermal conductivity of lattice core sandwich structure was predicted using a novel model. The predictive results were in good agreement with experimental and Finite Element Method results. The thermal conductivity of the lattice core sandwich structure was attributed to both core conduction and radiation. The core conduction caused thermal conductivity only relied on the relative density of the structure. And the radiation caused thermal conductivity increased linearly with the thickness of the core. It was found that the equivalent thermal conductivity of the lattice core sandwich structure showed a highly dependent relationship on temperature. At low temperatures, the structure exhibited a nearly thermal insulated behavior. With the temperature increasing, the thermal conductivity of the structure increased owing to radiation. Therefore, some attempts, such as reducing the emissivity of the core or designing multilayered structure, are believe to be of benefit for improving the thermal protection performance of the structure at high temperatures.

Solution Patterns Predicting Pythagorean Triples

Science.gov (United States)

Ezenweani, Ugwunna Louis

2013-01-01

Pythagoras Theorem is an old mathematical treatise that has traversed the school curricula from secondary to tertiary levels. The patterns it produced are quite interesting that many researchers have tried to generate a kind of predictive approach to identifying triples. Two attempts, namely Diophantine equation and Brahmagupta trapezium presented…

Mixed La-Li heterobimetallic complexes for tertiary nitroaldol resolution.

Science.gov (United States)

Tosaki, Shin-ya; Hara, Keiichi; Gnanadesikan, Vijay; Morimoto, Hiroyuki; Harada, Shinji; Sugita, Mari; Yamagiwa, Noriyuki; Matsunaga, Shigeki; Shibasaki, Masakatsu

2006-09-13

A kinetic resolution of tertiary nitroaldols derived from simple ketones is described. Mixed BINOL/biphenol La-Li heterobimetallic complexes gave the best selectivity in retro-nitroaldol reactions of racemic tertiary nitroaldols. By using a mixture of La-Li3-(1a)3 complex (LLB 2a) and La-Li3-(1b)3 (LLB* 2b) complex in a ratio of 2/1, chiral tertiary nitroaldols were obtained in 80-97% ee and 30-47% recovery yield.

Massification and Quality Assurance in Tertiary Education: The ...

African Journals Online (AJOL)

The study sets out to examine massification and its impact on quality assurance in tertiary education and the extent to which lecturer–student ratio, adequacy of infrastructure and pedagogical resources affect quality in tertiary institutions. Two research questions and one hypothesis were posed to guide the investigation.

Factors predictive of abnormal semen parameters in male partners of couples attending the infertility clinic of a tertiary hospital in southwestern Nigeria

Directory of Open Access Journals (Sweden)

Peter Aduloju

2016-12-01

Full Text Available Background: Infertility is a common gynaecological problem and male factor contributes significantly in the aetiology of infertility. Semen analysis has remained a useful investigation in the search for male factor infertility.Aim: This study assessed the pattern of semen parameters and predictive factors associated with abnormal parameters in male partners of infertile couples attending a Nigerian tertiary hospital.Methods: A descriptive study of infertile couples presenting at the clinic between January 2012and December 2015 was done at Ekiti State University Teaching Hospital, Ado-Ekiti.  Seminal fluid from the male partners were analysed in the laboratory using the WHO 2010 criteria for human semen characteristics. Data was analysed using SPSS 17 and logistic regression analysis was used to determine the predictive factors associated with abnormal semen parameters.Results: A total of 443 men participated in the study and 38.2% had abnormal sperm parameters. Oligozoospermia (34.8% and asthenozoospermia (26.9% are leading single factor abnormality found, astheno-oligozoospermia occurred in 14.2% and oligo-astheno-teratozoospermia in 3.6% of cases. The prevalence of azoospermia was 3.4%. Smoking habit, past infection with mumps and previous groin surgery significantly predicted abnormal semen parameters with p values of 0.025, 0.040 and 0.017 respectively. Positive cultures were recorded in 36.2% of cases and staph aureus was the commonest organism.Conclusion: Male factor abnormalities remain significant contributors to infertility and men should be encouraged through advocacy to participate in investigation of infertility to reduce the level of stigmatization and ostracizing of women with infertility especially in sub-Saharan Africa.

Combining neural networks for protein secondary structure prediction

DEFF Research Database (Denmark)

Riis, Søren Kamaric

1995-01-01

In this paper structured neural networks are applied to the problem of predicting the secondary structure of proteins. A hierarchical approach is used where specialized neural networks are designed for each structural class and then combined using another neural network. The submodels are designed...... by using a priori knowledge of the mapping between protein building blocks and the secondary structure and by using weight sharing. Since none of the individual networks have more than 600 adjustable weights over-fitting is avoided. When ensembles of specialized experts are combined the performance...

Challenges with Tertiary-Level Mechatronic Fluid Power

DEFF Research Database (Denmark)

Dransfield, Peter; Conrad, Finn

1996-01-01

As authors we take the view that mechatronics, as it relates to fluid power, has three levels which we designate as primary, secondary and tertiary. A brief review of the current status of fluid power, hydraulic and pneumatic, and of electronic control of it is presented and discussed. The focus...... is then on tertiary-level mechatronic fluid power and the challenges to it being applied successfully....

Reduced Fragment Diversity for Alpha and Alpha-Beta Protein Structure Prediction using Rosetta.

Science.gov (United States)

Abbass, Jad; Nebel, Jean-Christophe

2017-01-01

Protein structure prediction is considered a main challenge in computational biology. The biannual international competition, Critical Assessment of protein Structure Prediction (CASP), has shown in its eleventh experiment that free modelling target predictions are still beyond reliable accuracy, therefore, much effort should be made to improve ab initio methods. Arguably, Rosetta is considered as the most competitive method when it comes to targets with no homologues. Relying on fragments of length 9 and 3 from known structures, Rosetta creates putative structures by assembling candidate fragments. Generally, the structure with the lowest energy score, also known as first model, is chosen to be the "predicted one". A thorough study has been conducted on the role and diversity of 3-mers involved in Rosetta's model "refinement" phase. Usage of the standard number of 3-mers - i.e. 200 - has been shown to degrade alpha and alpha-beta protein conformations initially achieved by assembling 9-mers. Therefore, a new prediction pipeline is proposed for Rosetta where the "refinement" phase is customised according to a target's structural class prediction. Over 8% improvement in terms of first model structure accuracy is reported for alpha and alpha-beta classes when decreasing the number of 3- mers. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Exploiting the Past and the Future in Protein Secondary Structure Prediction

DEFF Research Database (Denmark)

Baldi, Pierre; Brunak, Søren; Frasconi, P

1999-01-01

predictions based on variable ranges of dependencies. These architectures extend recurrent neural networks, introducing non-causal bidirectional dynamics to capture both upstream and downstream information. The prediction algorithm is completed by the use of mixtures of estimators that leverage evolutionary......Motivation: Predicting the secondary structure of a protein (alpha-helix, beta-sheet, coil) is an important step towards elucidating its three-dimensional structure, as well as its function. Presently, the best predictors are based on machine learning approaches, in particular neural network...

Prediction of Seismic Damage-Based Degradation in RC Structures

DEFF Research Database (Denmark)

Kirkegaard, Poul Henning; Gupta, Vinay K.; Nielsen, Søren R.K.

Estimation of structural damage from known increase in the fundamental period of a structure after an earthquake or prediction of degradation of stiffness and strength for known damage requires reliable correlations between these response functionals. This study proposes a modified Clough-Johnsto...

Measurements and Predictions of the Noise from Three-Stream Jets

Science.gov (United States)

Henderson, Brenda S.; Leib, Stewart J.; Wernet, Mark P.

2015-01-01

An experimental and numerical investigation of the noise produced by high-subsonic and supersonic three-stream jets was conducted. The exhaust system consisted of externally-mixed-convergent nozzles and an external plug. Bypass- and tertiary-to-core area ratios between 1.0 and 2.5, and 0.4 and 1.0, respectively, were studied. Axisymmetric and offset tertiary nozzles were investigated for heated and unheated conditions. For axisymmetric configurations, the addition of the third stream was found to reduce peak- and high-frequency acoustic levels in the peak-jet-noise direction, with greater reductions at the lower bypass-to-core area ratios. For the offset configurations, an offset duct was found to decrease acoustic levels on the thick side of the tertiary nozzle relative to those produced by the simulated two-stream jet with up to 8 dB mid-frequency noise reduction at large angles to the jet inlet axis. Noise reduction in the peak-jet-noise direction was greater for supersonic core speeds than for subsonic core speeds. The addition of a tertiary nozzle insert used to divert the third-stream jet to one side of the nozzle system provided no noise reduction. Noise predictions are presented for selected cases using a method based on an acoustic analogy with mean flow interaction effects accounted for using a Green's function, computed in terms of its coupled azimuthal modes for the offset cases, and a source model previously used for round and rectangular jets. Comparisons of the prediction results with data show that the noise model predicts the observed increase in low-frequency noise with the introduction of a third, axisymmetric stream, but not the high-frequency reduction. For an offset third stream, the model predicts the observed trend of decreased sound levels on the thick side of the jet compared with the thin side, but the predicted azimuthal variations are much less than those seen in the data. Also, the shift of the spectral peak to lower frequencies with

RaptorX-Property: a web server for protein structure property prediction.

Science.gov (United States)

Wang, Sheng; Li, Wei; Liu, Shiwang; Xu, Jinbo

2016-07-08

RaptorX Property (http://raptorx2.uchicago.edu/StructurePropertyPred/predict/) is a web server predicting structure property of a protein sequence without using any templates. It outperforms other servers, especially for proteins without close homologs in PDB or with very sparse sequence profile (i.e. carries little evolutionary information). This server employs a powerful in-house deep learning model DeepCNF (Deep Convolutional Neural Fields) to predict secondary structure (SS), solvent accessibility (ACC) and disorder regions (DISO). DeepCNF not only models complex sequence-structure relationship by a deep hierarchical architecture, but also interdependency between adjacent property labels. Our experimental results show that, tested on CASP10, CASP11 and the other benchmarks, this server can obtain ∼84% Q3 accuracy for 3-state SS, ∼72% Q8 accuracy for 8-state SS, ∼66% Q3 accuracy for 3-state solvent accessibility, and ∼0.89 area under the ROC curve (AUC) for disorder prediction. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Manual for the prediction of blast and fragment loadings on structures

Energy Technology Data Exchange (ETDEWEB)

1980-11-01

The purpose of this manual is to provide Architect-Engineer (AE) firms guidance for the prediction of air blast, ground shock and fragment loadings on structures as a result of accidental explosions in or near these structures. Information in this manual is the result of an extensive literature survey and data gathering effort, supplemented by some original analytical studies on various aspects of blast phenomena. Many prediction equations and graphs are presented, accompanied by numerous example problems illustrating their use. The manual is complementary to existing structural design manuals and is intended to reflect the current state-of-the-art in prediction of blast and fragment loads for accidental explosions of high explosives at the Pantex Plant. In some instances, particularly for explosions within blast-resistant structures of complex geometry, rational estimation of these loads is beyond the current state-of-the-art.

EXPLORING THE TERTIARY EFL STUDENTS' ACADEMIC WRITING COMPETENCIES

Directory of Open Access Journals (Sweden)

Aunurrahman Aunurrahman

2017-05-01

Full Text Available For tertiary English as a Foreign Language (EFL students, academic writing is not an easy task. It requires knowledge of the academic writing genres with their particular linguistic features. Moreover, academic writing demands good critical thinking. This research aims to explore the students' academic writing competencies that also focus on critical thinking. The research involved thirty-six first-year tertiary EFL students from a regular class of a private university in Pontianak, West Kalimantan, Indonesia. The source for data collection was the students’ texts. Three texts were selected and the students were categorized into low, medium, and high levels of writing achievement. The text analysis utilized functional grammar rooted in systemic functional linguistics (Emilia, 2014. The analysis shows that the students, regardless of their levels of writing achievement, have little control over the schematic structure and linguistic features of an argumentative writing. The text analysis also shows that the students’ texts have some limitations as regards their critical thinking capacity. Still, a few examples of academic language were detected in the texts. The findings suggest that the lecturer should incorporate explicit teaching and cooperative learning activities to alleviate the students' difficulties and develop their academic writing and critical thinking capacity.

New tips for structure prediction by comparative modeling

OpenAIRE

Rayan, Anwar

2009-01-01

Comparative modelling is utilized to predict the 3-dimensional conformation of a given protein (target) based on its sequence alignment to experimentally determined protein structure (template). The use of such technique is already rewarding and increasingly widespread in biological research and drug development. The accuracy of the predictions as commonly accepted depends on the score of sequence identity of the target protein to the template. To assess the relationship between sequence iden...

Crime and Crime Management in Nigeria Tertiary Institutions

Science.gov (United States)

Adebanjo, Margaret Adewunmi

2014-01-01

This paper examines crime and its management in Nigerian tertiary institutions. Tertiary institutions today have become arenas for crime activities such as rape, cultism, murder, theft, internet fraud, drug abuse, and examination malpractices. This paper delves into what crime is, and its causes; and the positions of the law on crime management.…

10 CFR 212.78 - Tertiary incentive crude oil.

Science.gov (United States)

2010-01-01

... 10 Energy 3 2010-01-01 2010-01-01 false Tertiary incentive crude oil. 212.78 Section 212.78 Energy DEPARTMENT OF ENERGY OIL MANDATORY PETROLEUM PRICE REGULATIONS Producers of Crude Oil § 212.78 Tertiary incentive crude oil. Annual prepaid expenses report. By January 31 of each year after 1980, the project...

Automatic prediction of facial trait judgments: appearance vs. structural models.

Directory of Open Access Journals (Sweden)

Mario Rojas

Full Text Available Evaluating other individuals with respect to personality characteristics plays a crucial role in human relations and it is the focus of attention for research in diverse fields such as psychology and interactive computer systems. In psychology, face perception has been recognized as a key component of this evaluation system. Multiple studies suggest that observers use face information to infer personality characteristics. Interactive computer systems are trying to take advantage of these findings and apply them to increase the natural aspect of interaction and to improve the performance of interactive computer systems. Here, we experimentally test whether the automatic prediction of facial trait judgments (e.g. dominance can be made by using the full appearance information of the face and whether a reduced representation of its structure is sufficient. We evaluate two separate approaches: a holistic representation model using the facial appearance information and a structural model constructed from the relations among facial salient points. State of the art machine learning methods are applied to a derive a facial trait judgment model from training data and b predict a facial trait value for any face. Furthermore, we address the issue of whether there are specific structural relations among facial points that predict perception of facial traits. Experimental results over a set of labeled data (9 different trait evaluations and classification rules (4 rules suggest that a prediction of perception of facial traits is learnable by both holistic and structural approaches; b the most reliable prediction of facial trait judgments is obtained by certain type of holistic descriptions of the face appearance; and c for some traits such as attractiveness and extroversion, there are relationships between specific structural features and social perceptions.

Hill-Climbing search and diversification within an evolutionary approach to protein structure prediction.

Science.gov (United States)

Chira, Camelia; Horvath, Dragos; Dumitrescu, D

2011-07-30

Proteins are complex structures made of amino acids having a fundamental role in the correct functioning of living cells. The structure of a protein is the result of the protein folding process. However, the general principles that govern the folding of natural proteins into a native structure are unknown. The problem of predicting a protein structure with minimum-energy starting from the unfolded amino acid sequence is a highly complex and important task in molecular and computational biology. Protein structure prediction has important applications in fields such as drug design and disease prediction. The protein structure prediction problem is NP-hard even in simplified lattice protein models. An evolutionary model based on hill-climbing genetic operators is proposed for protein structure prediction in the hydrophobic - polar (HP) model. Problem-specific search operators are implemented and applied using a steepest-ascent hill-climbing approach. Furthermore, the proposed model enforces an explicit diversification stage during the evolution in order to avoid local optimum. The main features of the resulting evolutionary algorithm - hill-climbing mechanism and diversification strategy - are evaluated in a set of numerical experiments for the protein structure prediction problem to assess their impact to the efficiency of the search process. Furthermore, the emerging consolidated model is compared to relevant algorithms from the literature for a set of difficult bidimensional instances from lattice protein models. The results obtained by the proposed algorithm are promising and competitive with those of related methods.

Hill-Climbing search and diversification within an evolutionary approach to protein structure prediction

Directory of Open Access Journals (Sweden)

Chira Camelia

2011-07-01

Full Text Available Abstract Proteins are complex structures made of amino acids having a fundamental role in the correct functioning of living cells. The structure of a protein is the result of the protein folding process. However, the general principles that govern the folding of natural proteins into a native structure are unknown. The problem of predicting a protein structure with minimum-energy starting from the unfolded amino acid sequence is a highly complex and important task in molecular and computational biology. Protein structure prediction has important applications in fields such as drug design and disease prediction. The protein structure prediction problem is NP-hard even in simplified lattice protein models. An evolutionary model based on hill-climbing genetic operators is proposed for protein structure prediction in the hydrophobic - polar (HP model. Problem-specific search operators are implemented and applied using a steepest-ascent hill-climbing approach. Furthermore, the proposed model enforces an explicit diversification stage during the evolution in order to avoid local optimum. The main features of the resulting evolutionary algorithm - hill-climbing mechanism and diversification strategy - are evaluated in a set of numerical experiments for the protein structure prediction problem to assess their impact to the efficiency of the search process. Furthermore, the emerging consolidated model is compared to relevant algorithms from the literature for a set of difficult bidimensional instances from lattice protein models. The results obtained by the proposed algorithm are promising and competitive with those of related methods.

Halitosis amongst students in tertiary institutions in Lagos state.

Science.gov (United States)

Arinola, J E; Olukoju, O O

2012-12-01

Halitosis is defined as a noticeable unpleasant odor from the mouth. It is a medico-social problem that affects a significant number of people around the world. Research reveals that nearly 50% of the adult population has halitosis. To determine level of awareness of halitosis and prevalence of the condition amongst students in tertiary institutions as a baseline survey. For this project, 100 students from three tertiary institutions in Lagos state were chosen: University of Lagos, Lagos State University, Ojo campus and Yaba College of Technology. A semi-structured questionnaire and practical testing/diagnostic tool were utilized. Data collected was collated and analyzed using Microsoft Excel 2007 and SPSS statistical software. Most of the respondents were single and Christian. Level of awareness of halitosis was high. Results showed that 15%, 2% and 22% from UNILAG, LASU and YCT respectively said they had halitosis. Using the diagnostic tool, 6%, 8% and 2% respectively were positive for halitosis. There is high level of awareness of halitosis among the respondents. The prevalence of the disorder is low, however, it is recommended that enlightenment campaigns be mounted in schools to improve level of awareness and treatment seeking.

Exploring high-pressure FeB{sub 2}: Structural and electronic properties predictions

Energy Technology Data Exchange (ETDEWEB)

Harran, Ismail [School of Physical Science and Technology, Key Laboratory of Advanced Technologies of Materials, Ministry of Education of China, Southwest Jiaotong University, Chengdu, 610031 (China); Al Fashir University (Sudan); Wang, Hongyan [School of Physical Science and Technology, Key Laboratory of Advanced Technologies of Materials, Ministry of Education of China, Southwest Jiaotong University, Chengdu, 610031 (China); Chen, Yuanzheng, E-mail: cyz@calypso.org.cn [School of Physical Science and Technology, Key Laboratory of Advanced Technologies of Materials, Ministry of Education of China, Southwest Jiaotong University, Chengdu, 610031 (China); Jia, Mingzhen [School of Physical Science and Technology, Key Laboratory of Advanced Technologies of Materials, Ministry of Education of China, Southwest Jiaotong University, Chengdu, 610031 (China); Wu, Nannan [School of Mathematics, Physics and Biological Engineering, Inner Mongolia University of Science & Technology, Baotou, 014010 (China)

2016-09-05

The high pressure (HP) structural phase of FeB{sub 2} compound is investigated by using first-principles crystal structure prediction based on the CALYPSO technique. A thermodynamically stable phase of FeB{sub 2} with space group Imma is predicted at pressure above 225 GPa, which is characterized by a layered orthorhombic structure containing puckered graphite-like boron layers. Its electronic and mechanical properties are identified and analyzed. The feature of band structures favors the occurrence of superconductivity, whereas, the calculated Pugh's ratio reveals that the HP Imma structure exhibits ductile mechanical property. - Highlights: • The high pressure structural phase of FeB{sub 2} compound is firstly investigated by the CALYPSO technique. • A thermodynamically stable Imma phase of FeB{sub 2} is predicted at pressure above 225 GPa. • The Imma structure is characterized by a 2D boron network containing puckered graphite-like boron layers. • The band feature of Imma structure favors the occurrence of superconductivity. • The calculated Pugh's ratio suggests that the Imma structure exhibits ductile mechanical property.

Tunable differentiation of tertiary C-H bonds in intramolecular transition metal-catalyzed nitrene transfer reactions.

Science.gov (United States)

Corbin, Joshua R; Schomaker, Jennifer M

2017-04-13

Metal-catalyzed nitrene transfer reactions are an appealing and efficient strategy for accessing tetrasubstituted amines through the direct amination of tertiary C-H bonds. Traditional catalysts for these reactions rely on substrate control to achieve site-selectivity in the C-H amination event; thus, tunability is challenging when competing C-H bonds have similar steric or electronic features. One consequence of this fact is that the impact of catalyst identity on the selectivity in the competitive amination of tertiary C-H bonds has not been well-explored, despite the potential for progress towards predictable and catalyst-controlled C-N bond formation. In this communication, we report investigations into tunable and site-selective nitrene transfers between tertiary C(sp 3 )-H bonds using a combination of transition metal catalysts, including complexes based on Ag, Mn, Rh and Ru. Particularly striking was the ability to reverse the selectivity of nitrene transfer by a simple change in the identity of the N-donor ligand supporting the Ag(i) complex. The combination of our Ag(i) catalysts with known Rh 2 (ii) complexes expands the scope of successful catalyst-controlled intramolecular nitrene transfer and represents a promising springboard for the future development of intermolecular C-H N-group transfer methods.

Geology of drill hole UE25p No. 1: A test hole into pre-Tertiary rocks near Yucca Mountain, southern Nevada

International Nuclear Information System (INIS)

Carr, M.D.; Waddell, S.J.; Vick, G.S.; Stock, J.M.; Monsen, S.A.; Harris, A.G.; Cork, B.W.; Byers, F.M. Jr.

1986-01-01

Yucca Mountain in southern Nye County, Nevada, has been proposed as a potential site for the underground disposal of high-level nuclear waste. An exploratory drill hole designated UE25p No. 1 was drilled 3 km east of the proposed repository site to investigate the geology and hydrology of the rocks that underlie the Tertiary volcanic and sedimentary rock sequence forming Yucca Mountain. Silurian dolomite assigned to the Roberts Mountain and Lone Mountain Formations was intersected below the Tertiary section between a depth of approximately 1244 m (4080 ft) and the bottom of the drill hole at 1807 m (5923 ft). These formations are part of an important regional carbonate aquifer in the deep ground-water system. Tertiary units deeper than 1139 m (3733 ft) in drill hole UE25p No. 1 are stratigraphically older than any units previously penetrated by drill holes at Yucca Mountain. These units are, in ascending order, the tuff of Yucca Flat, an unnamed calcified ash-flow tuff, and a sequence of clastic deposits. The upper part of the Tertiary sequence in drill hole UE25p No. 1 is similar to that found in other drill holes at Yucca Mountain. The Tertiary sequence is in fault contact with the Silurian rocks. This fault between Tertiary and Paleozoic rocks may correlate with the Fran Ridge fault, a steeply westward-dipping fault exposed approximately 0.5 km east of the drill hole. Another fault intersects UE25p No. 1 at 873 m (2863 ft), but its surface trace is concealed beneath the valley west of the Fran Ridge fault. The Paintbrush Canyon fault, the trace of which passes less than 100 m (330 ft) east of the drilling site, intersects drill hole UE25p No. 1 at a depth of approximately 78 m (255 ft). The drill hole apparently intersected the west flank of a structural high of pre-Tertiary rocks, near the eastern edge of the Crater Flat structural depression

Development of laboratory acceleration test method for service life prediction of concrete structures

International Nuclear Information System (INIS)

Cho, M. S.; Song, Y. C.; Bang, K. S.; Lee, J. S.; Kim, D. K.

1999-01-01

Service life prediction of nuclear power plants depends on the application of history of structures, field inspection and test, the development of laboratory acceleration tests, their analysis method and predictive model. In this study, laboratory acceleration test method for service life prediction of concrete structures and application of experimental test results are introduced. This study is concerned with environmental condition of concrete structures and is to develop the acceleration test method for durability factors of concrete structures e.g. carbonation, sulfate attack, freeze-thaw cycles and shrinkage-expansion etc

TBI server: a web server for predicting ion effects in RNA folding.

Science.gov (United States)

Zhu, Yuhong; He, Zhaojian; Chen, Shi-Jie

2015-01-01

Metal ions play a critical role in the stabilization of RNA structures. Therefore, accurate prediction of the ion effects in RNA folding can have a far-reaching impact on our understanding of RNA structure and function. Multivalent ions, especially Mg²⁺, are essential for RNA tertiary structure formation. These ions can possibly become strongly correlated in the close vicinity of RNA surface. Most of the currently available software packages, which have widespread success in predicting ion effects in biomolecular systems, however, do not explicitly account for the ion correlation effect. Therefore, it is important to develop a software package/web server for the prediction of ion electrostatics in RNA folding by including ion correlation effects. The TBI web server http://rna.physics.missouri.edu/tbi_index.html provides predictions for the total electrostatic free energy, the different free energy components, and the mean number and the most probable distributions of the bound ions. A novel feature of the TBI server is its ability to account for ion correlation and ion distribution fluctuation effects. By accounting for the ion correlation and fluctuation effects, the TBI server is a unique online tool for computing ion-mediated electrostatic properties for given RNA structures. The results can provide important data for in-depth analysis for ion effects in RNA folding including the ion-dependence of folding stability, ion uptake in the folding process, and the interplay between the different energetic components.

TBI server: a web server for predicting ion effects in RNA folding.

Directory of Open Access Journals (Sweden)

Yuhong Zhu

Full Text Available Metal ions play a critical role in the stabilization of RNA structures. Therefore, accurate prediction of the ion effects in RNA folding can have a far-reaching impact on our understanding of RNA structure and function. Multivalent ions, especially Mg²⁺, are essential for RNA tertiary structure formation. These ions can possibly become strongly correlated in the close vicinity of RNA surface. Most of the currently available software packages, which have widespread success in predicting ion effects in biomolecular systems, however, do not explicitly account for the ion correlation effect. Therefore, it is important to develop a software package/web server for the prediction of ion electrostatics in RNA folding by including ion correlation effects.The TBI web server http://rna.physics.missouri.edu/tbi_index.html provides predictions for the total electrostatic free energy, the different free energy components, and the mean number and the most probable distributions of the bound ions. A novel feature of the TBI server is its ability to account for ion correlation and ion distribution fluctuation effects.By accounting for the ion correlation and fluctuation effects, the TBI server is a unique online tool for computing ion-mediated electrostatic properties for given RNA structures. The results can provide important data for in-depth analysis for ion effects in RNA folding including the ion-dependence of folding stability, ion uptake in the folding process, and the interplay between the different energetic components.

MCTBI: a web server for predicting metal ion effects in RNA structures.

Science.gov (United States)

Sun, Li-Zhen; Zhang, Jing-Xiang; Chen, Shi-Jie

2017-08-01

Metal ions play critical roles in RNA structure and function. However, web servers and software packages for predicting ion effects in RNA structures are notably scarce. Furthermore, the existing web servers and software packages mainly neglect ion correlation and fluctuation effects, which are potentially important for RNAs. We here report a new web server, the MCTBI server (http://rna.physics.missouri.edu/MCTBI), for the prediction of ion effects for RNA structures. This server is based on the recently developed MCTBI, a model that can account for ion correlation and fluctuation effects for nucleic acid structures and can provide improved predictions for the effects of metal ions, especially for multivalent ions such as Mg 2+ effects, as shown by extensive theory-experiment test results. The MCTBI web server predicts metal ion binding fractions, the most probable bound ion distribution, the electrostatic free energy of the system, and the free energy components. The results provide mechanistic insights into the role of metal ions in RNA structure formation and folding stability, which is important for understanding RNA functions and the rational design of RNA structures. © 2017 Sun et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Tertiary Technical Education and Youth Integration in Brazil, Colombia and Mexico

Directory of Open Access Journals (Sweden)

Claudia Jacinto

2014-11-01

Full Text Available Vocational training versus a traditional university education. This chapter seeks to answer the question of whether ‘tertiary technical education’ has contributed to increasing economic and social opportunity for young people in Latin America, using three case studies from Brazil, Colombia and Mexico. It examines the extent to which tertiary technical education has contributed towards democratising access to education through institutional diversification, expanded enrolment and, at least theoretically, improved access to quality employment. The analysis shows that tertiary technical education has contributed to widening of opportunities by offering an alternative form of education to new generations of young people. Tertiary technical education is more accessible, shorter in duration, has a vocational orientation, and tends to be cheaper than a university education. However, the case studies also reveal that while a tertiary technical education diploma is an asset for young people seeking employment, it nonetheless does not have the same perceived value as a traditional university education. Available data appear to indicate that graduates of tertiary technical education earn less on average than university graduates and face several challenges in the labour market. Furthermore, the studies reveal that despite the presence of highly regarded tertiary technical education institutions in all three countries, these carry less prestige and status than universities.

A fast and robust iterative algorithm for prediction of RNA pseudoknotted secondary structures

Science.gov (United States)

2014-01-01

Background Improving accuracy and efficiency of computational methods that predict pseudoknotted RNA secondary structures is an ongoing challenge. Existing methods based on free energy minimization tend to be very slow and are limited in the types of pseudoknots that they can predict. Incorporating known structural information can improve prediction accuracy; however, there are not many methods for prediction of pseudoknotted structures that can incorporate structural information as input. There is even less understanding of the relative robustness of these methods with respect to partial information. Results We present a new method, Iterative HFold, for pseudoknotted RNA secondary structure prediction. Iterative HFold takes as input a pseudoknot-free structure, and produces a possibly pseudoknotted structure whose energy is at least as low as that of any (density-2) pseudoknotted structure containing the input structure. Iterative HFold leverages strengths of earlier methods, namely the fast running time of HFold, a method that is based on the hierarchical folding hypothesis, and the energy parameters of HotKnots V2.0. Our experimental evaluation on a large data set shows that Iterative HFold is robust with respect to partial information, with average accuracy on pseudoknotted structures steadily increasing from roughly 54% to 79% as the user provides up to 40% of the input structure. Iterative HFold is much faster than HotKnots V2.0, while having comparable accuracy. Iterative HFold also has significantly better accuracy than IPknot on our HK-PK and IP-pk168 data sets. Conclusions Iterative HFold is a robust method for prediction of pseudoknotted RNA secondary structures, whose accuracy with more than 5% information about true pseudoknot-free structures is better than that of IPknot, and with about 35% information about true pseudoknot-free structures compares well with that of HotKnots V2.0 while being significantly faster. Iterative HFold and all data used in

Bi-objective integer programming for RNA secondary structure prediction with pseudoknots.

Science.gov (United States)

Legendre, Audrey; Angel, Eric; Tahi, Fariza

2018-01-15

RNA structure prediction is an important field in bioinformatics, and numerous methods and tools have been proposed. Pseudoknots are specific motifs of RNA secondary structures that are difficult to predict. Almost all existing methods are based on a single model and return one solution, often missing the real structure. An alternative approach would be to combine different models and return a (small) set of solutions, maximizing its quality and diversity in order to increase the probability that it contains the real structure. We propose here an original method for predicting RNA secondary structures with pseudoknots, based on integer programming. We developed a generic bi-objective integer programming algorithm allowing to return optimal and sub-optimal solutions optimizing simultaneously two models. This algorithm was then applied to the combination of two known models of RNA secondary structure prediction, namely MEA and MFE. The resulting tool, called BiokoP, is compared with the other methods in the literature. The results show that the best solution (structure with the highest F 1 -score) is, in most cases, given by BiokoP. Moreover, the results of BiokoP are homogeneous, regardless of the pseudoknot type or the presence or not of pseudoknots. Indeed, the F 1 -scores are always higher than 70% for any number of solutions returned. The results obtained by BiokoP show that combining the MEA and the MFE models, as well as returning several optimal and several sub-optimal solutions, allow to improve the prediction of secondary structures. One perspective of our work is to combine better mono-criterion models, in particular to combine a model based on the comparative approach with the MEA and the MFE models. This leads to develop in the future a new multi-objective algorithm to combine more than two models. BiokoP is available on the EvryRNA platform: https://EvryRNA.ibisc.univ-evry.fr .

Cascaded bidirectional recurrent neural networks for protein secondary structure prediction.

Science.gov (United States)

Chen, Jinmiao; Chaudhari, Narendra

2007-01-01

Protein secondary structure (PSS) prediction is an important topic in bioinformatics. Our study on a large set of non-homologous proteins shows that long-range interactions commonly exist and negatively affect PSS prediction. Besides, we also reveal strong correlations between secondary structure (SS) elements. In order to take into account the long-range interactions and SS-SS correlations, we propose a novel prediction system based on cascaded bidirectional recurrent neural network (BRNN). We compare the cascaded BRNN against another two BRNN architectures, namely the original BRNN architecture used for speech recognition as well as Pollastri's BRNN that was proposed for PSS prediction. Our cascaded BRNN achieves an overall three state accuracy Q3 of 74.38\\%, and reaches a high Segment OVerlap (SOV) of 66.0455. It outperforms the original BRNN and Pollastri's BRNN in both Q3 and SOV. Specifically, it improves the SOV score by 4-6%.

Theoretical prediction of low-density hexagonal ZnO hollow structures

Energy Technology Data Exchange (ETDEWEB)

Tuoc, Vu Ngoc, E-mail: tuoc.vungoc@hust.edu.vn [Institute of Engineering Physics, Hanoi University of Science and Technology, 1 Dai Co Viet Road, Hanoi (Viet Nam); Huan, Tran Doan [Institute of Materials Science, University of Connecticut, Storrs, Connecticut 06269-3136 (United States); Thao, Nguyen Thi [Institute of Engineering Physics, Hanoi University of Science and Technology, 1 Dai Co Viet Road, Hanoi (Viet Nam); Hong Duc University, 307 Le Lai, Thanh Hoa City (Viet Nam); Tuan, Le Manh [Hong Duc University, 307 Le Lai, Thanh Hoa City (Viet Nam)

2016-10-14

Along with wurtzite and zinc blende, zinc oxide (ZnO) has been found in a large number of polymorphs with substantially different properties and, hence, applications. Therefore, predicting and synthesizing new classes of ZnO polymorphs are of great significance and have been gaining considerable interest. Herein, we perform a density functional theory based tight-binding study, predicting several new series of ZnO hollow structures using the bottom-up approach. The geometry of the building blocks allows for obtaining a variety of hexagonal, low-density nanoporous, and flexible ZnO hollow structures. Their stability is discussed by means of the free energy computed within the lattice-dynamics approach. Our calculations also indicate that all the reported hollow structures are wide band gap semiconductors in the same fashion with bulk ZnO. The electronic band structures of the ZnO hollow structures are finally examined in detail.

Tertiary recovery and tritide injection equipment

International Nuclear Information System (INIS)

Li Lin

1989-01-01

The exploitation of an oil field is a continously developing process, undergoing seveal stages, such as the low production, the high production, the stable production and the decline. The tertiary recovery is an important means of the enhanced oil recovery. Since the object of the tertiary recovery is to treat the oil in micropores which is difficult to be produced, it is more necessary to know further the reservoir. Tritide can be used as a tracer and is an ideal marker of knowing the reservoir and the state of the fluid movement. The paper presents the tritide injection equipment

Factors predictive of abnormal semen parameters in male partners of couples attending the infertility clinic of a tertiary hospital in south-western Nigeria

Directory of Open Access Journals (Sweden)

Peter Olusola Aduloju

2016-11-01

Full Text Available Background: Infertility is a common gynaecological problem and male factor contributes significantly in the aetiology of infertility. Semen analysis has remained a useful investigation in the search for male factor infertility. Aim: This study assessed the pattern of semen parameters and predictive factors associated with abnormal parameters in male partners of infertile couples attending a Nigerian tertiary hospital. Methods: A descriptive study of infertile couples presenting at the clinic between January 2012and December 2015 was done at Ekiti State University Teaching Hospital, Ado-Ekiti. Seminal fluid from the male partners were analysed in the laboratory using the WHO 2010 criteria for human semen characteristics. Data was analysed using SPSS 17 and logistic regression analysis was used to determine the predictive factors associated with abnormal semen parameters. Results: A total of 443 men participated in the study and 38.2% had abnormal sperm parameters. Oligozoospermia (34.8% and asthenozoospermia (26.9% are leading single factor abnormality found, astheno-oligozoospermia occurred in 14.2% and oligo-astheno-teratozoospermia in 3.6% of cases. The prevalence of azoospermia was 3.4%. Smoking habit, past infection with mumps and previous groin surgery significantly predicted abnormal semen parameters with p values of 0.025, 0.040 and 0.017 respectively. Positive cultures were recorded in 36.2% of cases and staph aureus was the commonest organism. Conclusion: Male factor abnormalities remain significant contributors to infertility and men should be encouraged through advocacy to participate in investigation of infertility to reduce the level of stigmatization and ostracizing of women with infertility especially in sub-Saharan Africa.

Sparse RNA folding revisited: space-efficient minimum free energy structure prediction.

Science.gov (United States)

Will, Sebastian; Jabbari, Hosna

2016-01-01

RNA secondary structure prediction by energy minimization is the central computational tool for the analysis of structural non-coding RNAs and their interactions. Sparsification has been successfully applied to improve the time efficiency of various structure prediction algorithms while guaranteeing the same result; however, for many such folding problems, space efficiency is of even greater concern, particularly for long RNA sequences. So far, space-efficient sparsified RNA folding with fold reconstruction was solved only for simple base-pair-based pseudo-energy models. Here, we revisit the problem of space-efficient free energy minimization. Whereas the space-efficient minimization of the free energy has been sketched before, the reconstruction of the optimum structure has not even been discussed. We show that this reconstruction is not possible in trivial extension of the method for simple energy models. Then, we present the time- and space-efficient sparsified free energy minimization algorithm SparseMFEFold that guarantees MFE structure prediction. In particular, this novel algorithm provides efficient fold reconstruction based on dynamically garbage-collected trace arrows. The complexity of our algorithm depends on two parameters, the number of candidates Z and the number of trace arrows T; both are bounded by [Formula: see text], but are typically much smaller. The time complexity of RNA folding is reduced from [Formula: see text] to [Formula: see text]; the space complexity, from [Formula: see text] to [Formula: see text]. Our empirical results show more than 80 % space savings over RNAfold [Vienna RNA package] on the long RNAs from the RNA STRAND database (≥2500 bases). The presented technique is intentionally generalizable to complex prediction algorithms; due to their high space demands, algorithms like pseudoknot prediction and RNA-RNA-interaction prediction are expected to profit even stronger than "standard" MFE folding. SparseMFEFold is free

Bridge Structure Deformation Prediction Based on GNSS Data Using Kalman-ARIMA-GARCH Model.

Science.gov (United States)

Xin, Jingzhou; Zhou, Jianting; Yang, Simon X; Li, Xiaoqing; Wang, Yu

2018-01-19

Bridges are an essential part of the ground transportation system. Health monitoring is fundamentally important for the safety and service life of bridges. A large amount of structural information is obtained from various sensors using sensing technology, and the data processing has become a challenging issue. To improve the prediction accuracy of bridge structure deformation based on data mining and to accurately evaluate the time-varying characteristics of bridge structure performance evolution, this paper proposes a new method for bridge structure deformation prediction, which integrates the Kalman filter, autoregressive integrated moving average model (ARIMA), and generalized autoregressive conditional heteroskedasticity (GARCH). Firstly, the raw deformation data is directly pre-processed using the Kalman filter to reduce the noise. After that, the linear recursive ARIMA model is established to analyze and predict the structure deformation. Finally, the nonlinear recursive GARCH model is introduced to further improve the accuracy of the prediction. Simulation results based on measured sensor data from the Global Navigation Satellite System (GNSS) deformation monitoring system demonstrated that: (1) the Kalman filter is capable of denoising the bridge deformation monitoring data; (2) the prediction accuracy of the proposed Kalman-ARIMA-GARCH model is satisfactory, where the mean absolute error increases only from 3.402 mm to 5.847 mm with the increment of the prediction step; and (3) in comparision to the Kalman-ARIMA model, the Kalman-ARIMA-GARCH model results in superior prediction accuracy as it includes partial nonlinear characteristics (heteroscedasticity); the mean absolute error of five-step prediction using the proposed model is improved by 10.12%. This paper provides a new way for structural behavior prediction based on data processing, which can lay a foundation for the early warning of bridge health monitoring system based on sensor data using sensing

Bridge Structure Deformation Prediction Based on GNSS Data Using Kalman-ARIMA-GARCH Model

Directory of Open Access Journals (Sweden)

Jingzhou Xin

2018-01-01

Full Text Available Bridges are an essential part of the ground transportation system. Health monitoring is fundamentally important for the safety and service life of bridges. A large amount of structural information is obtained from various sensors using sensing technology, and the data processing has become a challenging issue. To improve the prediction accuracy of bridge structure deformation based on data mining and to accurately evaluate the time-varying characteristics of bridge structure performance evolution, this paper proposes a new method for bridge structure deformation prediction, which integrates the Kalman filter, autoregressive integrated moving average model (ARIMA, and generalized autoregressive conditional heteroskedasticity (GARCH. Firstly, the raw deformation data is directly pre-processed using the Kalman filter to reduce the noise. After that, the linear recursive ARIMA model is established to analyze and predict the structure deformation. Finally, the nonlinear recursive GARCH model is introduced to further improve the accuracy of the prediction. Simulation results based on measured sensor data from the Global Navigation Satellite System (GNSS deformation monitoring system demonstrated that: (1 the Kalman filter is capable of denoising the bridge deformation monitoring data; (2 the prediction accuracy of the proposed Kalman-ARIMA-GARCH model is satisfactory, where the mean absolute error increases only from 3.402 mm to 5.847 mm with the increment of the prediction step; and (3 in comparision to the Kalman-ARIMA model, the Kalman-ARIMA-GARCH model results in superior prediction accuracy as it includes partial nonlinear characteristics (heteroscedasticity; the mean absolute error of five-step prediction using the proposed model is improved by 10.12%. This paper provides a new way for structural behavior prediction based on data processing, which can lay a foundation for the early warning of bridge health monitoring system based on sensor data

Chemical structure-based predictive model for methanogenic anaerobic biodegradation potential.

Science.gov (United States)

Meylan, William; Boethling, Robert; Aronson, Dallas; Howard, Philip; Tunkel, Jay

2007-09-01

Many screening-level models exist for predicting aerobic biodegradation potential from chemical structure, but anaerobic biodegradation generally has been ignored by modelers. We used a fragment contribution approach to develop a model for predicting biodegradation potential under methanogenic anaerobic conditions. The new model has 37 fragments (substructures) and classifies a substance as either fast or slow, relative to the potential to be biodegraded in the "serum bottle" anaerobic biodegradation screening test (Organization for Economic Cooperation and Development Guideline 311). The model correctly classified 90, 77, and 91% of the chemicals in the training set (n = 169) and two independent validation sets (n = 35 and 23), respectively. Accuracy of predictions of fast and slow degradation was equal for training-set chemicals, but fast-degradation predictions were less accurate than slow-degradation predictions for the validation sets. Analysis of the signs of the fragment coefficients for this and the other (aerobic) Biowin models suggests that in the context of simple group contribution models, the majority of positive and negative structural influences on ultimate degradation are the same for aerobic and methanogenic anaerobic biodegradation.

Protein 8-class secondary structure prediction using conditional neural fields.

Science.gov (United States)

Wang, Zhiyong; Zhao, Feng; Peng, Jian; Xu, Jinbo

2011-10-01

Compared with the protein 3-class secondary structure (SS) prediction, the 8-class prediction gains less attention and is also much more challenging, especially for proteins with few sequence homologs. This paper presents a new probabilistic method for 8-class SS prediction using conditional neural fields (CNFs), a recently invented probabilistic graphical model. This CNF method not only models the complex relationship between sequence features and SS, but also exploits the interdependency among SS types of adjacent residues. In addition to sequence profiles, our method also makes use of non-evolutionary information for SS prediction. Tested on the CB513 and RS126 data sets, our method achieves Q8 accuracy of 64.9 and 64.7%, respectively, which are much better than the SSpro8 web server (51.0 and 48.0%, respectively). Our method can also be used to predict other structure properties (e.g. solvent accessibility) of a protein or the SS of RNA. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Structure prediction of AlnOm clusters

International Nuclear Information System (INIS)

Smok, P

2011-01-01

Genetic algorithm simulations, using Buckingham potential to represent the anion-anion and cation-anion short-range interactions, were performed in order to predict the equilibrium positions of the Al and O ions in Al n O m clusters. In order to find the equilibrium structures of compounds a self-organizing genetic algorithm were constructed. The calculation were carried out for several clusters Al n O m , with different numbers of aluminium and oxygen atoms.

Application of Tryptophan Fluorescence Bandwidth-Maximum Plot in Analysis of Monoclonal Antibody Structure.

Science.gov (United States)

Huang, Cheng-Yen; Hsieh, Ming-Ching; Zhou, Qinwei

2017-04-01

Monoclonal antibodies have become the fastest growing protein therapeutics in recent years. The stability and heterogeneity pertaining to its physical and chemical structures remain a big challenge. Tryptophan fluorescence has been proven to be a versatile tool to monitor protein tertiary structure. By modeling the tryptophan fluorescence emission envelope with log-normal distribution curves, the quantitative measure can be exercised for the routine characterization of monoclonal antibody overall tertiary structure. Furthermore, the log-normal deconvolution results can be presented as a two-dimensional plot with tryptophan emission bandwidth vs. emission maximum to enhance the resolution when comparing samples or as a function of applied perturbations. We demonstrate this by studying four different monoclonal antibodies, which show the distinction on emission bandwidth-maximum plot despite their similarity in overall amino acid sequences and tertiary structures. This strategy is also used to demonstrate the tertiary structure comparability between different lots manufactured for one of the monoclonal antibodies (mAb2). In addition, in the unfolding transition studies of mAb2 as a function of guanidine hydrochloride concentration, the evolution of the tertiary structure can be clearly traced in the emission bandwidth-maximum plot.

Protein Secondary Structure Prediction Using AutoEncoder Network and Bayes Classifier

Science.gov (United States)

Wang, Leilei; Cheng, Jinyong

2018-03-01

Protein secondary structure prediction is belong to bioinformatics,and it's important in research area. In this paper, we propose a new prediction way of protein using bayes classifier and autoEncoder network. Our experiments show some algorithms including the construction of the model, the classification of parameters and so on. The data set is a typical CB513 data set for protein. In terms of accuracy, the method is the cross validation based on the 3-fold. Then we can get the Q3 accuracy. Paper results illustrate that the autoencoder network improved the prediction accuracy of protein secondary structure.

Structural health monitoring for fatigue life prediction of orthotropic brdige decks

NARCIS (Netherlands)

Pijpers, R.J.M.; Pahlavan, P.L.; Paulissen, J.H.; Hakkesteegt, H.C.; Jansen, T.H.

2013-01-01

Infrastructure asset owners are more and more confronted with structures reaching the end of their structural life. Structural Health Monitoring (SHM) systems should provide up-to-date information about the actual condition, as well predict the structural life and required maintenance of the assets

Solvent effects on the magnetic shielding of tertiary butyl alcohol

African Journals Online (AJOL)

)4 and tetramethyl ammonium cation N(CH3)4(+) have also been presented. KEY WORDS: Solvent effects, Magnetic shielding, Tertiary butyl alcohol, Tertiary butyl amine, Continuum solvation calculations, Chemical shift estimation methods

Ensuring Effective Mentoring in Tertiary Institutions in Anambra State ...

African Journals Online (AJOL)

This paper concerns itself only with ascertaining the strategies that could ensure effective mentoring in tertiary institutions. The survey method was employed. The study population comprised 78 teacher educators in tertiary institutions in Anambra State. One research question guided the study while one null hypothesis was ...

A Case Series of the Probability Density and Cumulative Distribution of Laryngeal Disease in a Tertiary Care Voice Center.

Science.gov (United States)

de la Fuente, Jaime; Garrett, C Gaelyn; Ossoff, Robert; Vinson, Kim; Francis, David O; Gelbard, Alexander

2017-11-01

To examine the distribution of clinic and operative pathology in a tertiary care laryngology practice. Probability density and cumulative distribution analyses (Pareto analysis) was used to rank order laryngeal conditions seen in an outpatient tertiary care laryngology practice and those requiring surgical intervention during a 3-year period. Among 3783 new clinic consultations and 1380 operative procedures, voice disorders were the most common primary diagnostic category seen in clinic (n = 3223), followed by airway (n = 374) and swallowing (n = 186) disorders. Within the voice strata, the most common primary ICD-9 code used was dysphonia (41%), followed by unilateral vocal fold paralysis (UVFP) (9%) and cough (7%). Among new voice patients, 45% were found to have a structural abnormality. The most common surgical indications were laryngotracheal stenosis (37%), followed by recurrent respiratory papillomatosis (18%) and UVFP (17%). Nearly 55% of patients presenting to a tertiary referral laryngology practice did not have an identifiable structural abnormality in the larynx on direct or indirect examination. The distribution of ICD-9 codes requiring surgical intervention was disparate from that seen in clinic. Application of the Pareto principle may improve resource allocation in laryngology, but these initial results require confirmation across multiple institutions.

Technological, Pedagogical, and Content Knowledge (TPACK): An Educational Landscape for Tertiary Science Faculty

Science.gov (United States)

Lavadia, Linda

Earlier studies concluded that technology's strength is in supporting student learning rather than as an instrument for content delivery (Angeli & Valanides, 2014). Current research espouses the merits of the Technological Pedagogical Content Knowledge (TPACK) framework as a guide for educators' reflections about technology integration within the context of content and instructional practice. Grounded by two theoretical frameworks, TPACK (Mishra & Koehler, 2006; 2008) and Rogers' (1983, 1995) theory of diffusion of innovation, the purpose of this mixed-methods research was two-fold: to explore the perceived competencies of tertiary science faculty at higher education institutions with respect to their integration of technology within the constructs of pedagogical practice and content learning and to analyze whether these perceived competencies may serve as predictive factors for technology adoption level. The literature review included past research that served as models for the Sci-TPACK instrument. Twenty-nine professors of tertiary science courses participated in an online Likert survey, and four professors provided in-depth interviews on their TPACK practices. Quantitative analysis of data consisted of descriptive and reliability statistics, calculations of means for each of the seven scales or domains of TPACK, and regression analysis. Open-ended questions on the Likert survey and individual interviews provided recurrent themes of the qualitative data. Final results revealed that the participants integrate technology into pedagogy and content through a myriad of TPACK practices. Regression analysis supported perceived TPACK competencies as predictive factors for technology adoption level.

Application of Functional Use Predictions to Aid in Structure ...

Science.gov (United States)

Humans are potentially exposed to thousands of anthropogenic chemicals in commerce. Recent work has shown that the bulk of this exposure may occur in near-field indoor environments (e.g., home, school, work, etc.). Advances in suspect screening analyses (SSA) now allow an improved understanding of the chemicals present in these environments. However, due to the nature of suspect screening techniques, investigators are often left with chemical formula predictions, with the possibility of many chemical structures matching to each formula. Here, newly developed quantitative structure-use relationship (QSUR) models are used to identify potential exposure sources for candidate structures. Previously, a suspect screening workflow was introduced and applied to house dust samples collected from the U.S. Department of Housing and Urban Development’s American Healthy Homes Survey (AHHS) [Rager, et al., Env. Int. 88 (2016)]. This workflow utilized the US EPA’s Distributed Structure-Searchable Toxicity (DSSTox) Database to link identified molecular features to molecular formulas, and ultimately chemical structures. Multiple QSUR models were applied to support the evaluation of candidate structures. These QSURs predict the likelihood of a chemical having a functional use commonly associated with consumer products having near-field use. For 3,228 structures identified as possible chemicals in AHHS house dust samples, we were able to obtain the required descriptors to appl

Three-dimensional protein structure prediction: Methods and computational strategies.

Science.gov (United States)

Dorn, Márcio; E Silva, Mariel Barbachan; Buriol, Luciana S; Lamb, Luis C

2014-10-12

A long standing problem in structural bioinformatics is to determine the three-dimensional (3-D) structure of a protein when only a sequence of amino acid residues is given. Many computational methodologies and algorithms have been proposed as a solution to the 3-D Protein Structure Prediction (3-D-PSP) problem. These methods can be divided in four main classes: (a) first principle methods without database information; (b) first principle methods with database information; (c) fold recognition and threading methods; and (d) comparative modeling methods and sequence alignment strategies. Deterministic computational techniques, optimization techniques, data mining and machine learning approaches are typically used in the construction of computational solutions for the PSP problem. Our main goal with this work is to review the methods and computational strategies that are currently used in 3-D protein prediction. Copyright © 2014 Elsevier Ltd. All rights reserved.

Protein structure predictions with Monte Carlo simulated annealing: Case for the β-sheet

Science.gov (United States)

Okamoto, Y.; Fukugita, M.; Kawai, H.; Nakazawa, T.

Work is continued for a prediction of three-dimensional structure of peptides and proteins with Monte Carlo simulated annealing using only a generic energy function and amino acid sequence as input. We report that β-sheet like structure is successfully predicted for a fragment of bovine pancreatic trypsin inhibitor which is known to have the β-sheet structure in nature. Together with the results for α-helix structure reported earlier, this means that a successful prediction can be made, at least at a qualitative level, for two dominant building blocks of proteins, α-helix and β-sheet, from the information of amino acid sequence alone.

Parathyroid carcinoma in tertiary hyperparathyroidism.

Science.gov (United States)

Kim, Byung Seup; Ryu, Han Suk; Kang, Kyung Ho; Park, Sung Jun

2016-10-01

Parathyroid carcinoma is a rare disease of unknown etiology. This study presents a case of parathyroid carcinoma in a patient with tertiary hyperparathyroidism. Despite a successful kidney transplantation, the intact parathyroid hormone (iPTH) level of the patient was elevated consistently and could not be controlled by medical therapy. Due to the development of tertiary hyperparathyroidism with bone pain and osteoporosis, subtotal parathyroidectomy was performed 4 months after the kidney transplantation. Histological evaluation revealed that one of four parathyroid lesions was a parathyroid carcinoma, while the others were diffuse hyperplasia. Postoperative laboratory studies indicated a decreased level of iPTH. A positron emission tomography-computed tomography performed 6 months after the operation revealed no evidence of local recurrence or distant metastasis. Copyright © 2013. Published by Elsevier Taiwan.

Risk Factors Predicting Mortality in Patients with Lung Abscess in a Public Tertiary Care Center in Karachi, Pakistan

OpenAIRE

Shaista Ghazal; Ashok Kumar; Binav Shrestha; Sana Sajid; Maria Malik; Nadeen Rizvi

2013-01-01

Introduction: Lung abscess is a commonly encountered entity in South-East Asia but not much data regarding its outcome is available. The objective of this study was to identify the factors associated with increased mortality in patients diagnosed with lung abscess in a tertiary care center of Karachi, Pakistan. Methods: A retrospective case analysis was performed via hospital records, on patients admitted with lung abscess between January 2009 and January 2011 at the largest state...

MEGADOCK-Web: an integrated database of high-throughput structure-based protein-protein interaction predictions.

Science.gov (United States)

Hayashi, Takanori; Matsuzaki, Yuri; Yanagisawa, Keisuke; Ohue, Masahito; Akiyama, Yutaka

2018-05-08

Protein-protein interactions (PPIs) play several roles in living cells, and computational PPI prediction is a major focus of many researchers. The three-dimensional (3D) structure and binding surface are important for the design of PPI inhibitors. Therefore, rigid body protein-protein docking calculations for two protein structures are expected to allow elucidation of PPIs different from known complexes in terms of 3D structures because known PPI information is not explicitly required. We have developed rapid PPI prediction software based on protein-protein docking, called MEGADOCK. In order to fully utilize the benefits of computational PPI predictions, it is necessary to construct a comprehensive database to gather prediction results and their predicted 3D complex structures and to make them easily accessible. Although several databases exist that provide predicted PPIs, the previous databases do not contain a sufficient number of entries for the purpose of discovering novel PPIs. In this study, we constructed an integrated database of MEGADOCK PPI predictions, named MEGADOCK-Web. MEGADOCK-Web provides more than 10 times the number of PPI predictions than previous databases and enables users to conduct PPI predictions that cannot be found in conventional PPI prediction databases. In MEGADOCK-Web, there are 7528 protein chains and 28,331,628 predicted PPIs from all possible combinations of those proteins. Each protein structure is annotated with PDB ID, chain ID, UniProt AC, related KEGG pathway IDs, and known PPI pairs. Additionally, MEGADOCK-Web provides four powerful functions: 1) searching precalculated PPI predictions, 2) providing annotations for each predicted protein pair with an experimentally known PPI, 3) visualizing candidates that may interact with the query protein on biochemical pathways, and 4) visualizing predicted complex structures through a 3D molecular viewer. MEGADOCK-Web provides a huge amount of comprehensive PPI predictions based on

Determinants of propensity of tertiary agricultural students in Ghana ...

African Journals Online (AJOL)

The study aimed to identify factors that affect the decision of tertiary agricultural students in Ghana to enter agribusiness as a self-employment venture after graduation. The results showed that tertiary agricultural students in Ghana were predominantly males with little or no farming background. They had a rather moderate ...

Virality Prediction and Community Structure in Social Networks

Science.gov (United States)

Weng, Lilian; Menczer, Filippo; Ahn, Yong-Yeol

2013-08-01

How does network structure affect diffusion? Recent studies suggest that the answer depends on the type of contagion. Complex contagions, unlike infectious diseases (simple contagions), are affected by social reinforcement and homophily. Hence, the spread within highly clustered communities is enhanced, while diffusion across communities is hampered. A common hypothesis is that memes and behaviors are complex contagions. We show that, while most memes indeed spread like complex contagions, a few viral memes spread across many communities, like diseases. We demonstrate that the future popularity of a meme can be predicted by quantifying its early spreading pattern in terms of community concentration. The more communities a meme permeates, the more viral it is. We present a practical method to translate data about community structure into predictive knowledge about what information will spread widely. This connection contributes to our understanding in computational social science, social media analytics, and marketing applications.

Use of read-across and computer-based predictive analysis for the safety assessment of PEG cocamines.

Science.gov (United States)

Skare, Julie A; Blackburn, Karen; Wu, Shengde; Re, Thomas A; Duche, Daniel; Ringeissen, Stephanie; Bjerke, Donald L; Srinivasan, Viny; Eisenmann, Carol

2015-04-01

In the European Union animal testing has been eliminated for cosmetic ingredients while the US Cosmetic Ingredient Review Expert Panel may request data from animal studies. The use of read-across and predictive toxicology provides a path for filling data gaps without additional animal testing. The PEG cocamines are tertiary amines with an alkyl group derived from coconut fatty acids and two PEG chains of varying length. Toxicology data gaps for the PEG cocamines can be addressed by read-across based on structure-activity relationship using the framework described by Wu et al. (2010) for identifying suitable structural analogs. Data for structural analogs supports the conclusion that the PEG cocamines are non-genotoxic and not expected to exhibit systemic or developmental/reproductive toxicity with use in cosmetics. Due to lack of reliable dermal sensitization data for suitable analogs, this endpoint was addressed using predictive software (TIMES SS) as a first step (Laboratory of Mathematical Chemistry). The prediction for PEG cocamines was the same as that for PEGs, which have been concluded to not present a significant concern for dermal sensitization. This evaluation for PEG cocamines demonstrates the utility of read-across and predictive toxicology tools to assess the safety of cosmetic ingredients. Copyright © 2015 Elsevier Inc. All rights reserved.

Polymer physics predicts the effects of structural variants on chromatin architecture.

Science.gov (United States)

Bianco, Simona; Lupiáñez, Darío G; Chiariello, Andrea M; Annunziatella, Carlo; Kraft, Katerina; Schöpflin, Robert; Wittler, Lars; Andrey, Guillaume; Vingron, Martin; Pombo, Ana; Mundlos, Stefan; Nicodemi, Mario

2018-05-01

Structural variants (SVs) can result in changes in gene expression due to abnormal chromatin folding and cause disease. However, the prediction of such effects remains a challenge. Here we present a polymer-physics-based approach (PRISMR) to model 3D chromatin folding and to predict enhancer-promoter contacts. PRISMR predicts higher-order chromatin structure from genome-wide chromosome conformation capture (Hi-C) data. Using the EPHA4 locus as a model, the effects of pathogenic SVs are predicted in silico and compared to Hi-C data generated from mouse limb buds and patient-derived fibroblasts. PRISMR deconvolves the folding complexity of the EPHA4 locus and identifies SV-induced ectopic contacts and alterations of 3D genome organization in homozygous or heterozygous states. We show that SVs can reconfigure topologically associating domains, thereby producing extensive rewiring of regulatory interactions and causing disease by gene misexpression. PRISMR can be used to predict interactions in silico, thereby providing a tool for analyzing the disease-causing potential of SVs.

Prediction of coronal structure of the solar eclipse of October 23, 1976

International Nuclear Information System (INIS)

Schatten, K.H.

1976-01-01

Earlier work on the prediction of solar eclipse coronal structures is briefly summarised. A computer drawn plot made on October 18 1976 showed the field time structure predicted for the time of the solar eclipse on October 23. A very dipolar coronal field was indicated, and a very large equatorial streamer was predicted for both the east and west limbs of the Sun, due to the lack of very strong active regions near either limb. Nested coronal arches were seen within this equatorial streamer, and many small arches were also seen on both limbs. The main feature, however, is the prediction of the two large bright streamers marking the solar equator, with polar plumes in a characteristic dipole fashion. At the time of the eclipse it is hoped that a high resolution photograph will allow much of the structure to be discovered. (U.K.)

American Tertiary mollusks of the genus Clementia

Science.gov (United States)

Woodring, W.P.

1927-01-01

Aside from its value as an aid in determining the age of Tertiary beds, the chief interest of the genus Clementia lies in the anomalous features of its present and former distribution. An attempt is made in this paper to trace its geologic history, to point out its paleobiologic significance, and to describe all the known American Tertiary species. The fossils from Colombia used in preparing this report were collected during explorations made under the direction of Dr. 0. B. Hopkins, chief geologist of the Imperial Oil Co. (Ltd.), who kindly donated them to the United States National Museum. Dr. T. Wayland Vaughan, of the Scripps Institution of Oceanography, furnished information relating to specimens collected by him in Mexico. Dr. Bruce L. Clark, of the University of California; Dr. G. Dallas Hanna, of the California Academy of Sciences; Dr. H. A. Pilsbry, of the Philadelphia Academy of Natural Sciences; and Dr. W. D. Matthew, of the American Museum of Natural History, generously loaned type specimens and other material. Doctor Clark and Doctor Hanna also gave information concerning the Tertiary species from California. Mr. Ralph B. Stewart, of the University of California, read the manuscript, and I have taken advantage of his suggestions. I am also indebted to Mr. L. R. Cox, of the British Museum, for information relating to the fossil species from Persia, Zanzibar, and Burma, and to Dr. Axel A. Olsson, of the International Petroleum Co., for data concerning undescribed Tertiary species from Peru.

From structure prediction to genomic screens for novel non-coding RNAs

DEFF Research Database (Denmark)

Gorodkin, Jan; Hofacker, Ivo L.

2011-01-01

Abstract: Non-coding RNAs (ncRNAs) are receiving more and more attention not only as an abundant class of genes, but also as regulatory structural elements (some located in mRNAs). A key feature of RNA function is its structure. Computational methods were developed early for folding and prediction....... This and the increased amount of available genomes have made it possible to employ structure-based methods for genomic screens. The field has moved from folding prediction of single sequences to computational screens for ncRNAs in genomic sequence using the RNA structure as the main characteristic feature. Whereas early...... upon some of the concepts in current methods that have been applied in genomic screens for de novo RNA structures in searches for novel ncRNA genes and regulatory RNA structure on mRNAs. We discuss the strengths and weaknesses of the different strategies and how they can complement each other....

RANDOM FUNCTIONS AND INTERVAL METHOD FOR PREDICTING THE RESIDUAL RESOURCE OF BUILDING STRUCTURES

Directory of Open Access Journals (Sweden)

Shmelev Gennadiy Dmitrievich

2017-11-01

Full Text Available Subject: possibility of using random functions and interval prediction method for estimating the residual life of building structures in the currently used buildings. Research objectives: coordination of ranges of values to develop predictions and random functions that characterize the processes being predicted. Materials and methods: when performing this research, the method of random functions and the method of interval prediction were used. Results: in the course of this work, the basic properties of random functions, including the properties of families of random functions, are studied. The coordination of time-varying impacts and loads on building structures is considered from the viewpoint of their influence on structures and representation of the structures’ behavior in the form of random functions. Several models of random functions are proposed for predicting individual parameters of structures. For each of the proposed models, its scope of application is defined. The article notes that the considered approach of forecasting has been used many times at various sites. In addition, the available results allowed the authors to develop a methodology for assessing the technical condition and residual life of building structures for the currently used facilities. Conclusions: we studied the possibility of using random functions and processes for the purposes of forecasting the residual service lives of structures in buildings and engineering constructions. We considered the possibility of using an interval forecasting approach to estimate changes in defining parameters of building structures and their technical condition. A comprehensive technique for forecasting the residual life of building structures using the interval approach is proposed.

MASTR: multiple alignment and structure prediction of non-coding RNAs using simulated annealing

DEFF Research Database (Denmark)

Lindgreen, Stinus; Gardner, Paul P; Krogh, Anders

2007-01-01

function that considers sequence conservation, covariation and basepairing probabilities. The results show that the method is very competitive to similar programs available today, both in terms of accuracy and computational efficiency. AVAILABILITY: Source code available from http://mastr.binf.ku.dk/......MOTIVATION: As more non-coding RNAs are discovered, the importance of methods for RNA analysis increases. Since the structure of ncRNA is intimately tied to the function of the molecule, programs for RNA structure prediction are necessary tools in this growing field of research. Furthermore......, it is known that RNA structure is often evolutionarily more conserved than sequence. However, few existing methods are capable of simultaneously considering multiple sequence alignment and structure prediction. RESULT: We present a novel solution to the problem of simultaneous structure prediction...

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...

TMDIM: an improved algorithm for the structure prediction of transmembrane domains of bitopic dimers

Science.gov (United States)

Cao, Han; Ng, Marcus C. K.; Jusoh, Siti Azma; Tai, Hio Kuan; Siu, Shirley W. I.

2017-09-01

α-Helical transmembrane proteins are the most important drug targets in rational drug development. However, solving the experimental structures of these proteins remains difficult, therefore computational methods to accurately and efficiently predict the structures are in great demand. We present an improved structure prediction method TMDIM based on Park et al. (Proteins 57:577-585, 2004) for predicting bitopic transmembrane protein dimers. Three major algorithmic improvements are introduction of the packing type classification, the multiple-condition decoy filtering, and the cluster-based candidate selection. In a test of predicting nine known bitopic dimers, approximately 78% of our predictions achieved a successful fit (RMSD PHP, MySQL and Apache, with all major browsers supported.

Amphibian and reptile road-kills on tertiary roads in relation to landscape structure: using a citizen science approach with open-access land cover data.

Science.gov (United States)

Heigl, Florian; Horvath, Kathrin; Laaha, Gregor; Zaller, Johann G

2017-06-26

Amphibians and reptiles are among the most endangered vertebrate species worldwide. However, little is known how they are affected by road-kills on tertiary roads and whether the surrounding landscape structure can explain road-kill patterns. The aim of our study was to examine the applicability of open-access remote sensing data for a large-scale citizen science approach to describe spatial patterns of road-killed amphibians and reptiles on tertiary roads. Using a citizen science app we monitored road-kills of amphibians and reptiles along 97.5 km of tertiary roads covering agricultural, municipal and interurban roads as well as cycling paths in eastern Austria over two seasons. Surrounding landscape was assessed using open access land cover classes for the region (Coordination of Information on the Environment, CORINE). Hotspot analysis was performed using kernel density estimation (KDE+). Relations between land cover classes and amphibian and reptile road-kills were analysed with conditional probabilities and general linear models (GLM). We also estimated the potential cost-efficiency of a large scale citizen science monitoring project. We recorded 180 amphibian and 72 reptile road-kills comprising eight species mainly occurring on agricultural roads. KDE+ analyses revealed a significant clustering of road-killed amphibians and reptiles, which is an important information for authorities aiming to mitigate road-kills. Overall, hotspots of amphibian and reptile road-kills were next to the land cover classes arable land, suburban areas and vineyards. Conditional probabilities and GLMs identified road-kills especially next to preferred habitats of green toad, common toad and grass snake, the most often found road-killed species. A citizen science approach appeared to be more cost-efficient than monitoring by professional researchers only when more than 400 km of road are monitored. Our findings showed that freely available remote sensing data in combination with a

Structure life prediction at high temperature: present and future capabilities

International Nuclear Information System (INIS)

Chaboche, J.L.

1987-01-01

The life prediction techniques for high temperature conditions include several aspects which are considered successively in this article. Crack initiation criteria themselves, defined for the isolated volume element (the tension-compression specimen for example), including parametric relationships and continuous damage approaches and calculation of local stress and strain fields in the structure and their evolution under cyclic plasticity, which poses several difficult problems to obtain stabilized cyclic solutions are examined. The use of crack initiation criteria or damage rules from the result of the cyclic inelastic analysis and the prediction of crack growth in the structure are considered. Different levels are considered for the predictive tools: the classical approach, future methods presently under development and intermediate rules, which are already in use. Several examples are given on materials and components used either in the nuclear industry or in gas turbine engines. (author)

Predicting adverse drug reaction profiles by integrating protein interaction networks with drug structures.

Science.gov (United States)

Huang, Liang-Chin; Wu, Xiaogang; Chen, Jake Y

2013-01-01

The prediction of adverse drug reactions (ADRs) has become increasingly important, due to the rising concern on serious ADRs that can cause drugs to fail to reach or stay in the market. We proposed a framework for predicting ADR profiles by integrating protein-protein interaction (PPI) networks with drug structures. We compared ADR prediction performances over 18 ADR categories through four feature groups-only drug targets, drug targets with PPI networks, drug structures, and drug targets with PPI networks plus drug structures. The results showed that the integration of PPI networks and drug structures can significantly improve the ADR prediction performance. The median AUC values for the four groups were 0.59, 0.61, 0.65, and 0.70. We used the protein features in the best two models, "Cardiac disorders" (median-AUC: 0.82) and "Psychiatric disorders" (median-AUC: 0.76), to build ADR-specific PPI networks with literature supports. For validation, we examined 30 drugs withdrawn from the U.S. market to see if our approach can predict their ADR profiles and explain why they were withdrawn. Except for three drugs having ADRs in the categories we did not predict, 25 out of 27 withdrawn drugs (92.6%) having severe ADRs were successfully predicted by our approach. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

LoopIng: a template-based tool for predicting the structure of protein loops.

KAUST Repository

Messih, Mario Abdel

2015-08-06

Predicting the structure of protein loops is very challenging, mainly because they are not necessarily subject to strong evolutionary pressure. This implies that, unlike the rest of the protein, standard homology modeling techniques are not very effective in modeling their structure. However, loops are often involved in protein function, hence inferring their structure is important for predicting protein structure as well as function.We describe a method, LoopIng, based on the Random Forest automated learning technique, which, given a target loop, selects a structural template for it from a database of loop candidates. Compared to the most recently available methods, LoopIng is able to achieve similar accuracy for short loops (4-10 residues) and significant enhancements for long loops (11-20 residues). The quality of the predictions is robust to errors that unavoidably affect the stem regions when these are modeled. The method returns a confidence score for the predicted template loops and has the advantage of being very fast (on average: 1 min/loop).www.biocomputing.it/loopinganna.tramontano@uniroma1.itSupplementary data are available at Bioinformatics online.

Yb(OTf){sub 3}-catalyzed one-pot three component synthesis for tertiary amines

Energy Technology Data Exchange (ETDEWEB)

Lee, Bum Seok; Kim, Ji Hye; Nam, Tae Kyu; Jang, Doo Ok [Dept. of Chemistry, Yonsei University, Wonju (Korea, Republic of)

2015-07-15

Tertiary amine functionality is found in many natural bioactive products such as alkaloids, amino acids, nucleic acids, pharmaceuticals, and agrochemicals. Tertiary amines have also been used as building blocks for nitrogen-containing organic compounds and synthetic polymers. A one-pot method for direct reductive amination of aldehydes has been developed to synthesize tertiary amines using HMDS as a nitrogen source in the presence of Yb(OTf ){sub 3}. With a stoichiometric amount of HMDS, the reaction afforded the desired tertiary amines without competitive reduction of the parent carbonyl compounds. This reaction offers a convenient and efficient protocol for synthesizing aromatic and aliphatic tertiary amines under mild reaction conditions.

Curriculum Development in Outdoor Education: Tasmanian Teachers' Perspectives on the New Pre-Tertiary Outdoor Leadership Course

Science.gov (United States)

Dyment, Janet; Morse, Marcus; Shaw, Simon; Smith, Heidi

2014-01-01

The paper examines how outdoor education teachers in Tasmania, Australia have implemented and perceive a new pre-tertiary Outdoor Leadership curriculum document. It draws on an analysis of in-depth semi-structured interviews with 11 outdoor education teachers. The results revealed that teachers were generally welcoming of the new higher-order…

Electronic structure prediction via data-mining the empirical pseudopotential method

Energy Technology Data Exchange (ETDEWEB)

Zenasni, H; Aourag, H [LEPM, URMER, Departement of Physics, University Abou Bakr Belkaid, Tlemcen 13000 (Algeria); Broderick, S R; Rajan, K [Department of Materials Science and Engineering, Iowa State University, Ames, Iowa 50011-2230 (United States)

2010-01-15

We introduce a new approach for accelerating the calculation of the electronic structure of new materials by utilizing the empirical pseudopotential method combined with data mining tools. Combining data mining with the empirical pseudopotential method allows us to convert an empirical approach to a predictive approach. Here we consider tetrahedrally bounded III-V Bi semiconductors, and through the prediction of form factors based on basic elemental properties we can model the band structure and charge density for these semi-conductors, for which limited results exist. This work represents a unique approach to modeling the electronic structure of a material which may be used to identify new promising semi-conductors and is one of the few efforts utilizing data mining at an electronic level. (Abstract Copyright [2010], Wiley Periodicals, Inc.)

Predictive modeling of neuroanatomic structures for brain atrophy detection

Science.gov (United States)

Hu, Xintao; Guo, Lei; Nie, Jingxin; Li, Kaiming; Liu, Tianming

2010-03-01

In this paper, we present an approach of predictive modeling of neuroanatomic structures for the detection of brain atrophy based on cross-sectional MRI image. The underlying premise of applying predictive modeling for atrophy detection is that brain atrophy is defined as significant deviation of part of the anatomy from what the remaining normal anatomy predicts for that part. The steps of predictive modeling are as follows. The central cortical surface under consideration is reconstructed from brain tissue map and Regions of Interests (ROI) on it are predicted from other reliable anatomies. The vertex pair-wise distance between the predicted vertex and the true one within the abnormal region is expected to be larger than that of the vertex in normal brain region. Change of white matter/gray matter ratio within a spherical region is used to identify the direction of vertex displacement. In this way, the severity of brain atrophy can be defined quantitatively by the displacements of those vertices. The proposed predictive modeling method has been evaluated by using both simulated atrophies and MRI images of Alzheimer's disease.

Critical assessment of methods of protein structure prediction (CASP) - round x

KAUST Repository

Moult, John; Fidelis, Krzysztof; Kryshtafovych, Andriy; Schwede, Torsten; Tramontano, Anna

2013-01-01

This article is an introduction to the special issue of the journal PROTEINS, dedicated to the tenth Critical Assessment of Structure Prediction (CASP) experiment to assess the state of the art in protein structure modeling. The article describes the conduct of the experiment, the categories of prediction included, and outlines the evaluation and assessment procedures. The 10 CASP experiments span almost 20 years of progress in the field of protein structure modeling, and there have been enormous advances in methods and model accuracy in that period. Notable in this round is the first sustained improvement of models with refinement methods, using molecular dynamics. For the first time, we tested the ability of modeling methods to make use of sparse experimental three-dimensional contact information, such as may be obtained from new experimental techniques, with encouraging results. On the other hand, new contact prediction methods, though holding considerable promise, have yet to make an impact in CASP testing. The nature of CASP targets has been changing in recent CASPs, reflecting shifts in experimental structural biology, with more irregular structures, more multi-domain and multi-subunit structures, and less standard versions of known folds. When allowance is made for these factors, we continue to see steady progress in the overall accuracy of models, particularly resulting from improvement of non-template regions.

Critical assessment of methods of protein structure prediction (CASP) - round x

KAUST Repository

Moult, John

2013-12-17

This article is an introduction to the special issue of the journal PROTEINS, dedicated to the tenth Critical Assessment of Structure Prediction (CASP) experiment to assess the state of the art in protein structure modeling. The article describes the conduct of the experiment, the categories of prediction included, and outlines the evaluation and assessment procedures. The 10 CASP experiments span almost 20 years of progress in the field of protein structure modeling, and there have been enormous advances in methods and model accuracy in that period. Notable in this round is the first sustained improvement of models with refinement methods, using molecular dynamics. For the first time, we tested the ability of modeling methods to make use of sparse experimental three-dimensional contact information, such as may be obtained from new experimental techniques, with encouraging results. On the other hand, new contact prediction methods, though holding considerable promise, have yet to make an impact in CASP testing. The nature of CASP targets has been changing in recent CASPs, reflecting shifts in experimental structural biology, with more irregular structures, more multi-domain and multi-subunit structures, and less standard versions of known folds. When allowance is made for these factors, we continue to see steady progress in the overall accuracy of models, particularly resulting from improvement of non-template regions.

FuncPatch: a web server for the fast Bayesian inference of conserved functional patches in protein 3D structures.

Science.gov (United States)

Huang, Yi-Fei; Golding, G Brian

2015-02-15

A number of statistical phylogenetic methods have been developed to infer conserved functional sites or regions in proteins. Many methods, e.g. Rate4Site, apply the standard phylogenetic models to infer site-specific substitution rates and totally ignore the spatial correlation of substitution rates in protein tertiary structures, which may reduce their power to identify conserved functional patches in protein tertiary structures when the sequences used in the analysis are highly similar. The 3D sliding window method has been proposed to infer conserved functional patches in protein tertiary structures, but the window size, which reflects the strength of the spatial correlation, must be predefined and is not inferred from data. We recently developed GP4Rate to solve these problems under the Bayesian framework. Unfortunately, GP4Rate is computationally slow. Here, we present an intuitive web server, FuncPatch, to perform a fast approximate Bayesian inference of conserved functional patches in protein tertiary structures. Both simulations and four case studies based on empirical data suggest that FuncPatch is a good approximation to GP4Rate. However, FuncPatch is orders of magnitudes faster than GP4Rate. In addition, simulations suggest that FuncPatch is potentially a useful tool complementary to Rate4Site, but the 3D sliding window method is less powerful than FuncPatch and Rate4Site. The functional patches predicted by FuncPatch in the four case studies are supported by experimental evidence, which corroborates the usefulness of FuncPatch. The software FuncPatch is freely available at the web site, http://info.mcmaster.ca/yifei/FuncPatch golding@mcmaster.ca Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

CentroidFold: a web server for RNA secondary structure prediction

OpenAIRE

Sato, Kengo; Hamada, Michiaki; Asai, Kiyoshi; Mituyama, Toutai

2009-01-01

The CentroidFold web server (http://www.ncrna.org/centroidfold/) is a web application for RNA secondary structure prediction powered by one of the most accurate prediction engine. The server accepts two kinds of sequence data: a single RNA sequence and a multiple alignment of RNA sequences. It responses with a prediction result shown as a popular base-pair notation and a graph representation. PDF version of the graph representation is also available. For a multiple alignment sequence, the ser...

Predicting Consensus Structures for RNA Alignments Via Pseudo-Energy Minimization

Directory of Open Access Journals (Sweden)

Junilda Spirollari

2009-01-01

Full Text Available Thermodynamic processes with free energy parameters are often used in algorithms that solve the free energy minimization problem to predict secondary structures of single RNA sequences. While results from these algorithms are promising, an observation is that single sequence-based methods have moderate accuracy and more information is needed to improve on RNA secondary structure prediction, such as covariance scores obtained from multiple sequence alignments. We present in this paper a new approach to predicting the consensus secondary structure of a set of aligned RNA sequences via pseudo-energy minimization. Our tool, called RSpredict, takes into account sequence covariation and employs effective heuristics for accuracy improvement. RSpredict accepts, as input data, a multiple sequence alignment in FASTA or ClustalW format and outputs the consensus secondary structure of the input sequences in both the Vienna style Dot Bracket format and the Connectivity Table format. Our method was compared with some widely used tools including KNetFold, Pfold and RNAalifold. A comprehensive test on different datasets including Rfam sequence alignments and a multiple sequence alignment obtained from our study on the Drosophila X chromosome reveals that RSpredict is competitive with the existing tools on the tested datasets. RSpredict is freely available online as a web server and also as a jar file for download at http:// datalab.njit.edu/biology/RSpredict.

Characteristics of patients presenting to the vascular emergency department of a tertiary care hospital: a 2-year study

Directory of Open Access Journals (Sweden)

Kotsikoris Ioannis

2011-11-01

Full Text Available Abstract Background The structure of health care in Greece is receiving increased attention to improve its cost-effectiveness. We sought to examine the epidemiological characteristics of patients presenting to the vascular emergency department of a Greek tertiary care hospital during a 2-year period. We studied all patients presenting to the emergency department of vascular surgery at Red Cross Hospital, Athens, Greece between 1st January 2009 and 31st December 2010. Results Overall, 2452 (49.4% out of 4961 patients suffered from pathologies that should have been treated in primary health care. Only 2509 (50.6% needed vascular surgical intervention. Conclusions The emergency department of vascular surgery in a Greek tertiary care hospital has to treat a remarkably high percentage of patients suitable for the primary health care level. These results suggest that an improvement in the structure of health care is needed in Greece.

On the relevance of sophisticated structural annotations for disulfide connectivity pattern prediction.

Directory of Open Access Journals (Sweden)

Julien Becker

Full Text Available Disulfide bridges strongly constrain the native structure of many proteins and predicting their formation is therefore a key sub-problem of protein structure and function inference. Most recently proposed approaches for this prediction problem adopt the following pipeline: first they enrich the primary sequence with structural annotations, second they apply a binary classifier to each candidate pair of cysteines to predict disulfide bonding probabilities and finally, they use a maximum weight graph matching algorithm to derive the predicted disulfide connectivity pattern of a protein. In this paper, we adopt this three step pipeline and propose an extensive study of the relevance of various structural annotations and feature encodings. In particular, we consider five kinds of structural annotations, among which three are novel in the context of disulfide bridge prediction. So as to be usable by machine learning algorithms, these annotations must be encoded into features. For this purpose, we propose four different feature encodings based on local windows and on different kinds of histograms. The combination of structural annotations with these possible encodings leads to a large number of possible feature functions. In order to identify a minimal subset of relevant feature functions among those, we propose an efficient and interpretable feature function selection scheme, designed so as to avoid any form of overfitting. We apply this scheme on top of three supervised learning algorithms: k-nearest neighbors, support vector machines and extremely randomized trees. Our results indicate that the use of only the PSSM (position-specific scoring matrix together with the CSP (cysteine separation profile are sufficient to construct a high performance disulfide pattern predictor and that extremely randomized trees reach a disulfide pattern prediction accuracy of [Formula: see text] on the benchmark dataset SPX[Formula: see text], which corresponds to

Adaptive Neuro-Fuzzy Inference System Models for Force Prediction of a Mechatronic Flexible Structure

DEFF Research Database (Denmark)

Achiche, S.; Shlechtingen, M.; Raison, M.

2016-01-01

This paper presents the results obtained from a research work investigating the performance of different Adaptive Neuro-Fuzzy Inference System (ANFIS) models developed to predict excitation forces on a dynamically loaded flexible structure. For this purpose, a flexible structure is equipped...... obtained from applying a random excitation force on the flexible structure. The performance of the developed models is evaluated by analyzing the prediction capabilities based on a normalized prediction error. The frequency domain is considered to analyze the similarity of the frequencies in the predicted...... of the sampling frequency and sensor location on the model performance is investigated. The results obtained in this paper show that ANFIS models can be used to set up reliable force predictors for dynamical loaded flexible structures, when a certain degree of inaccuracy is accepted. Furthermore, the comparison...

Are clinical features able to predict Helicobacter pylori gastritis patterns? Evidence from tertiary centers.

Science.gov (United States)

Carabotti, Marilia; Lahner, Edith; Porowska, Barbara; Colacci, Enzo; Trentino, Paolo; Annibale, Bruno; Severi, Carola

2014-12-01

Outcome of Helicobacter pylori infection is different according to gastritis extension (i.e. antrum-restricted gastritis or pangastritis). The aim of this study is to evaluate whether different gastritis patterns are associated with specific gastrointestinal symptoms or clinical signs that could be suggestive of the topography of gastritis. 236 consecutive symptomatic outpatients were recruited in two tertiary centers. They filled in a validated and self-administered Rome III modular symptomatic questionnaire, and underwent gastroscopy with histological sampling. 154 patients with Helicobacter pylori infection were included. Clinical presentation did not differ between antrum-restricted gastritis and pangastritis, gastro-esophageal reflux disease being present in 48.2 and 54.1 % of patients and dyspepsia in 51.8 and 45.9 %, respectively. However, pangastritis statistically differed from antrum-restricted gastritis in that the presence of clinical signs (p gastritis pattern whereas their association with signs, accurately detected, is indicative for the presence of pangastritis.

De novo protein structure prediction by dynamic fragment assembly and conformational space annealing.

Science.gov (United States)

Lee, Juyong; Lee, Jinhyuk; Sasaki, Takeshi N; Sasai, Masaki; Seok, Chaok; Lee, Jooyoung

2011-08-01

Ab initio protein structure prediction is a challenging problem that requires both an accurate energetic representation of a protein structure and an efficient conformational sampling method for successful protein modeling. In this article, we present an ab initio structure prediction method which combines a recently suggested novel way of fragment assembly, dynamic fragment assembly (DFA) and conformational space annealing (CSA) algorithm. In DFA, model structures are scored by continuous functions constructed based on short- and long-range structural restraint information from a fragment library. Here, DFA is represented by the full-atom model by CHARMM with the addition of the empirical potential of DFIRE. The relative contributions between various energy terms are optimized using linear programming. The conformational sampling was carried out with CSA algorithm, which can find low energy conformations more efficiently than simulated annealing used in the existing DFA study. The newly introduced DFA energy function and CSA sampling algorithm are implemented into CHARMM. Test results on 30 small single-domain proteins and 13 template-free modeling targets of the 8th Critical Assessment of protein Structure Prediction show that the current method provides comparable and complementary prediction results to existing top methods. Copyright © 2011 Wiley-Liss, Inc.

Structural Dynamic Analyses And Test Predictions For Spacecraft Structures With Non-Linearities

Science.gov (United States)

Vergniaud, Jean-Baptiste; Soula, Laurent; Newerla, Alfred

2012-07-01

The overall objective of the mechanical development and verification process is to ensure that the spacecraft structure is able to sustain the mechanical environments encountered during launch. In general the spacecraft structures are a-priori assumed to behave linear, i.e. the responses to a static load or dynamic excitation, respectively, will increase or decrease proportionally to the amplitude of the load or excitation induced. However, past experiences have shown that various non-linearities might exist in spacecraft structures and the consequences of their dynamic effects can significantly affect the development and verification process. Current processes are mainly adapted to linear spacecraft structure behaviour. No clear rules exist for dealing with major structure non-linearities. They are handled outside the process by individual analysis and margin policy, and analyses after tests to justify the CLA coverage. Non-linearities can primarily affect the current spacecraft development and verification process on two aspects. Prediction of flights loads by launcher/satellite coupled loads analyses (CLA): only linear satellite models are delivered for performing CLA and no well-established rules exist how to properly linearize a model when non- linearities are present. The potential impact of the linearization on the results of the CLA has not yet been properly analyzed. There are thus difficulties to assess that CLA results will cover actual flight levels. Management of satellite verification tests: the CLA results generated with a linear satellite FEM are assumed flight representative. If the internal non- linearities are present in the tested satellite then there might be difficulties to determine which input level must be passed to cover satellite internal loads. The non-linear behaviour can also disturb the shaker control, putting the satellite at risk by potentially imposing too high levels. This paper presents the results of a test campaign performed in

Literacy Skills Development for Tertiary Institutions: A Case Study of ...

African Journals Online (AJOL)

Literacy Skills Development for Tertiary Institutions: A Case Study of the University of Calabar. ... These were drawn from five faculties, namely Education, Social Sciences, Law, Arts and Agriculture. The study observed that there is a ... more literacy skills. Key Words: Literacy skills, university, Nigeria, tertiary institution ...

Aromatic claw: A new fold with high aromatic content that evades structural prediction: Aromatic Claw

Energy Technology Data Exchange (ETDEWEB)

Sachleben, Joseph R. [Biomolecular NMR Core Facility, University of Chicago, Chicago Illinois; Adhikari, Aashish N. [Department of Chemistry, University of Chicago, Chicago Illinois; Gawlak, Grzegorz [Department of Biochemistry and Molecular Biology, University of Chicago, Chicago Illinois; Hoey, Robert J. [Department of Biochemistry and Molecular Biology, University of Chicago, Chicago Illinois; Liu, Gaohua [Northeast Structural Genomics Consortium (NESG), Department of Molecular Biology and Biochemistry, School of Arts and Sciences, and Department of Biochemistry and Molecular Biology, Robert Wood Johnson Medical School, and Center for Advanced Biotechnology and Medicine, Rutgers, The State University of New Jersey, Piscataway New Jersey; Joachimiak, Andrzej [Department of Biochemistry and Molecular Biology, University of Chicago, Chicago Illinois; Biological Sciences Division, Argonne National Laboratory, Argonne Illinois; Montelione, Gaetano T. [Northeast Structural Genomics Consortium (NESG), Department of Molecular Biology and Biochemistry, School of Arts and Sciences, and Department of Biochemistry and Molecular Biology, Robert Wood Johnson Medical School, and Center for Advanced Biotechnology and Medicine, Rutgers, The State University of New Jersey, Piscataway New Jersey; Sosnick, Tobin R. [Department of Biochemistry and Molecular Biology, University of Chicago, Chicago Illinois; Koide, Shohei [Department of Biochemistry and Molecular Biology, University of Chicago, Chicago Illinois; Department of Biochemistry and Molecular Pharmacology and the Perlmutter Cancer Center, New York University School of Medicine, New York New York

2016-11-10

We determined the NMR structure of a highly aromatic (13%) protein of unknown function, Aq1974 from Aquifex aeolicus (PDB ID: 5SYQ). The unusual sequence of this protein has a tryptophan content five times the normal (six tryptophan residues of 114 or 5.2% while the average tryptophan content is 1.0%) with the tryptophans occurring in a WXW motif. It has no detectable sequence homology with known protein structures. Although its NMR spectrum suggested that the protein was rich in β-sheet, upon resonance assignment and solution structure determination, the protein was found to be primarily α-helical with a small two-stranded β-sheet with a novel fold that we have termed an Aromatic Claw. As this fold was previously unknown and the sequence unique, we submitted the sequence to CASP10 as a target for blind structural prediction. At the end of the competition, the sequence was classified a hard template based model; the structural relationship between the template and the experimental structure was small and the predictions all failed to predict the structure. CSRosetta was found to predict the secondary structure and its packing; however, it was found that there was little correlation between CSRosetta score and the RMSD between the CSRosetta structure and the NMR determined one. This work demonstrates that even in relatively small proteins, we do not yet have the capacity to accurately predict the fold for all primary sequences. The experimental discovery of new folds helps guide the improvement of structural prediction methods.

Corot 310266512: A Light Curve With Primary, Secondary And Tertiary Eclipses

Directory of Open Access Journals (Sweden)

Fernández Fernández Javier

2015-01-01

Full Text Available We present the photometric study of an interesting target in the CoRoT exoplanet database: CoRoT 310266512. Its light curve shows primary, secondary and tertiary eclipses that suggests the presence of at least three celestial bodies. The primary and secondary eclipses have the same orbital period, 7.42 days, and the tertiary eclipse has an orbital period of 3.27 days. Two of the tertiary eclipses fall within a primary eclipse and a secondary eclipse. The properties of the light curve indicate the presence of two physically separated systems. The primary and secondary eclipses corresponds to a binary system (System I. The tertiary eclipses correspond to a star-planet system or a star-dwarf system (System II. Some parameters of these two systems are obtained from JKTEBOP [1] program.

Critical assessment of methods of protein structure prediction (CASP)-round IX

KAUST Repository

Moult, John; Fidelis, Krzysztof; Kryshtafovych, Andriy; Tramontano, Anna

2011-01-01

This article is an introduction to the special issue of the journal PROTEINS, dedicated to the ninth Critical Assessment of Structure Prediction (CASP) experiment to assess the state of the art in protein structure modeling. The article describes the conduct of the experiment, the categories of prediction included, and outlines the evaluation and assessment procedures. Methods for modeling protein structure continue to advance, although at a more modest pace than in the early CASP experiments. CASP developments of note are indications of improvement in model accuracy for some classes of target, an improved ability to choose the most accurate of a set of generated models, and evidence of improvement in accuracy for short "new fold" models. In addition, a new analysis of regions of models not derivable from the most obvious template structure has revealed better performance than expected.

Protein secondary structure prediction using modular reciprocal bidirectional recurrent neural networks.

Science.gov (United States)

Babaei, Sepideh; Geranmayeh, Amir; Seyyedsalehi, Seyyed Ali

2010-12-01

The supervised learning of recurrent neural networks well-suited for prediction of protein secondary structures from the underlying amino acids sequence is studied. Modular reciprocal recurrent neural networks (MRR-NN) are proposed to model the strong correlations between adjacent secondary structure elements. Besides, a multilayer bidirectional recurrent neural network (MBR-NN) is introduced to capture the long-range intramolecular interactions between amino acids in formation of the secondary structure. The final modular prediction system is devised based on the interactive integration of the MRR-NN and the MBR-NN structures to arbitrarily engage the neighboring effects of the secondary structure types concurrent with memorizing the sequential dependencies of amino acids along the protein chain. The advanced combined network augments the percentage accuracy (Q₃) to 79.36% and boosts the segment overlap (SOV) up to 70.09% when tested on the PSIPRED dataset in three-fold cross-validation. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Effects of Primary, Secondary and Tertiary Education on Conflict Intensity in Africa

Directory of Open Access Journals (Sweden)

Julius A. Agbor

2015-10-01

Full Text Available This study investigates the impact of different schooling dimensions (primary, secondary and tertiary on the intensity of intra-state conflicts in 25 African states during the period 1989–2008. It uses fixed-effects and Generalized Methods of Moments (GMM estimators in an annualized panel data framework. Parameter estimates suggest the following (1 primary schooling broadly mitigates conflicts in Africa. However, in environments with high natural resource rents, it could ignite conflicts; (2 there is evidence, although not overwhelming, that secondary schooling potentially drives conflicts in Africa. There is also evidence that urbanization potentially drives conflicts in Africa. However, although secondary schooling and urbanization potentially drives conflicts, in environments where secondary schooling (urbanization is high, urbanization (secondary schooling mitigates conflicts; (3 there is no evidence of a strong direct positive impact of tertiary education on conflicts and conditioning on tertiary schooling, income inequality potentially drives conflicts in African states. However, in contexts where income inequality (tertiary schooling is high, tertiary schooling (inequality mitigates conflict. Two important policy implications follow from this study. First, in contexts where income inequality is high (for instance, in South Africa, governments should strive to foster tertiary education in order to reduce conflict. Second, where urbanization rates are high, they should foster both secondary and tertiary education. This study contributes to existing knowledge by clearly demonstrating the utility of distinguishing between different educational dimensions and the contexts wherein they matter for conflict mitigation in Africa.

Deep Learning and Applications in Computational Biology

KAUST Repository

Zeng, Jianyang

2016-01-26

RNA-binding proteins (RBPs) play important roles in the post-transcriptional control of RNAs. Identifying RBP binding sites and characterizing RBP binding preferences are key steps toward understanding the basic mechanisms of the post-transcriptional gene regulation. Though numerous computational methods have been developed for modeling RBP binding preferences, discovering a complete structural representation of the RBP targets by integrating their available structural features in all three dimensions is still a challenging task. In this work, we develop a general and flexible deep learning framework for modeling structural binding preferences and predicting binding sites of RBPs, which takes (predicted) RNA tertiary structural information into account for the first time. Our framework constructs a unified representation that characterizes the structural specificities of RBP targets in all three dimensions, which can be further used to predict novel candidate binding sites and discover potential binding motifs. Through testing on the real CLIP-seq datasets, we have demonstrated that our deep learning framework can automatically extract effective hidden structural features from the encoded raw sequence and structural profiles, and predict accurate RBP binding sites. In addition, we have conducted the first study to show that integrating the additional RNA tertiary structural features can improve the model performance in predicting RBP binding sites, especially for the polypyrimidine tract-binding protein (PTB), which also provides a new evidence to support the view that RBPs may own specific tertiary structural binding preferences. In particular, the tests on the internal ribosome entry site (IRES) segments yield satisfiable results with experimental support from the literature and further demonstrate the necessity of incorporating RNA tertiary structural information into the prediction model. The source code of our approach can be found in https://github.com/thucombio/deepnet-rbp.

Protein secondary structure prediction for a single-sequence using hidden semi-Markov models

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Borodovsky Mark

2006-03-01

Full Text Available Abstract Background The accuracy of protein secondary structure prediction has been improving steadily towards the 88% estimated theoretical limit. There are two types of prediction algorithms: Single-sequence prediction algorithms imply that information about other (homologous proteins is not available, while algorithms of the second type imply that information about homologous proteins is available, and use it intensively. The single-sequence algorithms could make an important contribution to studies of proteins with no detected homologs, however the accuracy of protein secondary structure prediction from a single-sequence is not as high as when the additional evolutionary information is present. Results In this paper, we further refine and extend the hidden semi-Markov model (HSMM initially considered in the BSPSS algorithm. We introduce an improved residue dependency model by considering the patterns of statistically significant amino acid correlation at structural segment borders. We also derive models that specialize on different sections of the dependency structure and incorporate them into HSMM. In addition, we implement an iterative training method to refine estimates of HSMM parameters. The three-state-per-residue accuracy and other accuracy measures of the new method, IPSSP, are shown to be comparable or better than ones for BSPSS as well as for PSIPRED, tested under the single-sequence condition. Conclusions We have shown that new dependency models and training methods bring further improvements to single-sequence protein secondary structure prediction. The results are obtained under cross-validation conditions using a dataset with no pair of sequences having significant sequence similarity. As new sequences are added to the database it is possible to augment the dependency structure and obtain even higher accuracy. Current and future advances should contribute to the improvement of function prediction for orphan proteins inscrutable

Structural prediction and analysis of VIH-related peptides from selected crustacean species.

Science.gov (United States)

Nagaraju, Ganji Purna Chandra; Kumari, Nunna Siva; Prasad, Ganji Lakshmi Vara; Rajitha, Balney; Meenu, Madan; Rao, Manam Sreenivasa; Naik, Bannoth Reddya

2009-08-17

The tentative elucidation of the 3D-structure of vitellogenesis inhibiting hormone (VIH) peptides is conversely underprivileged by difficulties in gaining enough peptide or protein, diffracting crystals, and numerous extra technical aspects. As a result, no structural information is available for VIH peptide sequences registered in the Genbank. In this situation, it is not surprising that predictive methods have achieved great interest. Here, in this study the molt-inhibiting hormone (MIH) of the kuruma prawn (Marsupenaeus japonicus) is used, to predict the structure of four VIHrelated peptides in the crustacean species. The high similarity of the 3D-structures and the calculated physiochemical characteristics of these peptides suggest a common fold for the entire family.

Towards a unified fatigue life prediction method for marine structures

CERN Document Server

Cui, Weicheng; Wang, Fang

2014-01-01

In order to apply the damage tolerance design philosophy to design marine structures, accurate prediction of fatigue crack growth under service conditions is required. Now, more and more people have realized that only a fatigue life prediction method based on fatigue crack propagation (FCP) theory has the potential to explain various fatigue phenomena observed. In this book, the issues leading towards the development of a unified fatigue life prediction (UFLP) method based on FCP theory are addressed. Based on the philosophy of the UFLP method, the current inconsistency between fatigue design and inspection of marine structures could be resolved. This book presents the state-of-the-art and recent advances, including those by the authors, in fatigue studies. It is designed to lead the future directions and to provide a useful tool in many practical applications. It is intended to address to engineers, naval architects, research staff, professionals and graduates engaged in fatigue prevention design and survey ...

FACTORS PREDICTING MORBIDITY IN PATIENTS WITH DENGUE FEVER IN A TERTIARY CARE HOSPITAL

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Muhammad Imran Hasan Khan

2013-02-01

Full Text Available Introduction: Dengue virus (DENV affects over half the world’s population in 112 countries, and dengue fever (DF is the second largest arthropod borne infectious global hazard after malaria with complications like Dengue Hemorrhagic Fever (DHF and Dengue Shock Syndrome (DSS accounting for significant morbidity and mortality world over. Pakistan is significantly affected with DENV infection and to-date no study identifying risk factors associated with complications of DF has been done. Methods: 997 confirmed cases of DF were collected in a tertiary care hospital in Lahore, Pakistan and their clinical and biochemical data were collected. Univariate, multivariate and logistics regression analysis was performed to identify risk factors associated with development of DHF and DSS. Results: Bleeding OR 70.7 (CI 38.4-129.9, deranged liver function test OR 1.9 (CI 0.97-0.99, platelet count on admission less than 50,000 x109/L OR 0.16 (CI 0.13-0.19, presence of urinary red blood cells OR 1.4 (CI 0.179-0.900 and presence of urinary protein OR 1.1 (CI 0.191-0.974 were related to development of DHF and DSS.

LiveBench-1: continuous benchmarking of protein structure prediction servers.

Science.gov (United States)

Bujnicki, J M; Elofsson, A; Fischer, D; Rychlewski, L

2001-02-01

We present a novel, continuous approach aimed at the large-scale assessment of the performance of available fold-recognition servers. Six popular servers were investigated: PDB-Blast, FFAS, T98-lib, GenTHREADER, 3D-PSSM, and INBGU. The assessment was conducted using as prediction targets a large number of selected protein structures released from October 1999 to April 2000. A target was selected if its sequence showed no significant similarity to any of the proteins previously available in the structural database. Overall, the servers were able to produce structurally similar models for one-half of the targets, but significantly accurate sequence-structure alignments were produced for only one-third of the targets. We further classified the targets into two sets: easy and hard. We found that all servers were able to find the correct answer for the vast majority of the easy targets if a structurally similar fold was present in the server's fold libraries. However, among the hard targets--where standard methods such as PSI-BLAST fail--the most sensitive fold-recognition servers were able to produce similar models for only 40% of the cases, half of which had a significantly accurate sequence-structure alignment. Among the hard targets, the presence of updated libraries appeared to be less critical for the ranking. An "ideally combined consensus" prediction, where the results of all servers are considered, would increase the percentage of correct assignments by 50%. Each server had a number of cases with a correct assignment, where the assignments of all the other servers were wrong. This emphasizes the benefits of considering more than one server in difficult prediction tasks. The LiveBench program (http://BioInfo.PL/LiveBench) is being continued, and all interested developers are cordially invited to join.

Academic mentoring and the future of tertiary education in Nigeria ...

African Journals Online (AJOL)

Tertiary education is a major outlet for the provision of high manpower for national development. This paper therefore highlighted the challenges of tertiary education in Nigeria, early perspectives of mentoring undergraduates, the rationale for academic mentoring, the role of a mentor, and the role of library as catalyst in the ...

West Hackberry Tertiary Project. Annual report, September 3, 1997--September 2, 1998

Energy Technology Data Exchange (ETDEWEB)

Gillham, T.H.

1997-09-10

The following report is the Project Management Plan for the fifth year of the West Hackberry Tertiary Project. The West Hackberry Tertiary Project is one of four mid-term projects selected by the United States Department of Energy (DOE) as part of the DOE`s Class 1 Program for the development of advance recovery technologies in fluvial dominated deltaic reservoirs. The West Hackberry Tertiary Project is a field test of the idea that air injection can be combined with the Double Displacement Process to produce a low cost tertiary recovery process which is economic at current oil prices. The Double Displacement Process is the gas displacement of a water invaded oil column for the purpose of recovering tertiary oil by gravity drainage. The Double Displacement Process is based upon the concept that in fields such as West Hackberry waterdrive recoveries are typically 50%-60% of the original oil in place while gravity drainage recoveries average 80%-90% of the original oil in place. Therefore, by injecting a gas into a watered out reservoir, a gas cap will form an additional oil can be recovered due to gravity drainage. Although the Double Displacement Process has been shown to be successful in recovering tertiary oil in other fields, this project will be the first to utilize air injection in the Double Displacement Process. The use of air injection in this process combines the benefits of air`s low cost and universal accessibility with the potential for accelerated oil recovery due to the combustion process. If successful, this project will demonstrate that the use of air injection in the Double Displacement Process will result in an economically viable tertiary process in reservoirs where tertiary oil recovery is presently uneconomical.

MUFOLD-SS: New deep inception-inside-inception networks for protein secondary structure prediction.

Science.gov (United States)

Fang, Chao; Shang, Yi; Xu, Dong

2018-05-01

Protein secondary structure prediction can provide important information for protein 3D structure prediction and protein functions. Deep learning offers a new opportunity to significantly improve prediction accuracy. In this article, a new deep neural network architecture, named the Deep inception-inside-inception (Deep3I) network, is proposed for protein secondary structure prediction and implemented as a software tool MUFOLD-SS. The input to MUFOLD-SS is a carefully designed feature matrix corresponding to the primary amino acid sequence of a protein, which consists of a rich set of information derived from individual amino acid, as well as the context of the protein sequence. Specifically, the feature matrix is a composition of physio-chemical properties of amino acids, PSI-BLAST profile, and HHBlits profile. MUFOLD-SS is composed of a sequence of nested inception modules and maps the input matrix to either eight states or three states of secondary structures. The architecture of MUFOLD-SS enables effective processing of local and global interactions between amino acids in making accurate prediction. In extensive experiments on multiple datasets, MUFOLD-SS outperformed the best existing methods and other deep neural networks significantly. MUFold-SS can be downloaded from http://dslsrv8.cs.missouri.edu/~cf797/MUFoldSS/download.html. © 2018 Wiley Periodicals, Inc.

A probabilistic fragment-based protein structure prediction algorithm.

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David Simoncini

Full Text Available Conformational sampling is one of the bottlenecks in fragment-based protein structure prediction approaches. They generally start with a coarse-grained optimization where mainchain atoms and centroids of side chains are considered, followed by a fine-grained optimization with an all-atom representation of proteins. It is during this coarse-grained phase that fragment-based methods sample intensely the conformational space. If the native-like region is sampled more, the accuracy of the final all-atom predictions may be improved accordingly. In this work we present EdaFold, a new method for fragment-based protein structure prediction based on an Estimation of Distribution Algorithm. Fragment-based approaches build protein models by assembling short fragments from known protein structures. Whereas the probability mass functions over the fragment libraries are uniform in the usual case, we propose an algorithm that learns from previously generated decoys and steers the search toward native-like regions. A comparison with Rosetta AbInitio protocol shows that EdaFold is able to generate models with lower energies and to enhance the percentage of near-native coarse-grained decoys on a benchmark of [Formula: see text] proteins. The best coarse-grained models produced by both methods were refined into all-atom models and used in molecular replacement. All atom decoys produced out of EdaFold's decoy set reach high enough accuracy to solve the crystallographic phase problem by molecular replacement for some test proteins. EdaFold showed a higher success rate in molecular replacement when compared to Rosetta. Our study suggests that improving low resolution coarse-grained decoys allows computational methods to avoid subsequent sampling issues during all-atom refinement and to produce better all-atom models. EdaFold can be downloaded from http://www.riken.jp/zhangiru/software.html [corrected].

Bitter or not? BitterPredict, a tool for predicting taste from chemical structure.

Science.gov (United States)

Dagan-Wiener, Ayana; Nissim, Ido; Ben Abu, Natalie; Borgonovo, Gigliola; Bassoli, Angela; Niv, Masha Y

2017-09-21

Bitter taste is an innately aversive taste modality that is considered to protect animals from consuming toxic compounds. Yet, bitterness is not always noxious and some bitter compounds have beneficial effects on health. Hundreds of bitter compounds were reported (and are accessible via the BitterDB http://bitterdb.agri.huji.ac.il/dbbitter.php ), but numerous additional bitter molecules are still unknown. The dramatic chemical diversity of bitterants makes bitterness prediction a difficult task. Here we present a machine learning classifier, BitterPredict, which predicts whether a compound is bitter or not, based on its chemical structure. BitterDB was used as the positive set, and non-bitter molecules were gathered from literature to create the negative set. Adaptive Boosting (AdaBoost), based on decision trees machine-learning algorithm was applied to molecules that were represented using physicochemical and ADME/Tox descriptors. BitterPredict correctly classifies over 80% of the compounds in the hold-out test set, and 70-90% of the compounds in three independent external sets and in sensory test validation, providing a quick and reliable tool for classifying large sets of compounds into bitter and non-bitter groups. BitterPredict suggests that about 40% of random molecules, and a large portion (66%) of clinical and experimental drugs, and of natural products (77%) are bitter.

Tertiary-amine-containing thermo- and pH-sensitive hydrophilic ABA triblock copolymers: effect of different tertiary amines on thermally induced sol-gel transitions.

Science.gov (United States)

Henn, Daniel M; Wright, Roger A E; Woodcock, Jeremiah W; Hu, Bin; Zhao, Bin

2014-03-11

This Article reports on the synthesis of a series of well-defined, tertiary-amine-containing ABA triblock copolymers, composed of a poly(ethylene oxide) (PEO) central block and thermo- and pH-sensitive outer blocks, and the study of the effect of different tertiary amines on thermally induced sol-gel transition temperatures (T(sol-gel)) of their 10 wt % aqueous solutions. The doubly responsive ABA triblock copolymers were prepared from a difunctional PEO macroinitiator by atom transfer radical polymerization of methoxydi(ethylene glycol) methacrylate and ethoxydi(ethylene glycol) methacrylate at a feed molar ratio of 30:70 with ∼5 mol % of either N,N-diethylaminoethyl methacrylate (DEAEMA), N,N-diisopropylaminoethyl methacrylate, or N,N-di(n-butyl)aminoethyl methacrylate. The chain lengths of thermosensitive outer blocks and the molar contents of tertiary amines were very similar for all copolymers. Using rheological measurements, we determined the pH dependences of T(sol-gel) of 10 wt % aqueous solutions of these copolymers in a phosphate buffer. The T(sol-gel) versus pH curves of all polymers exhibited a sigmoidal shape. The T(sol-gel) increased with decreasing pH; the changes were small on both high and low pH sides. At a specific pH, the T(sol-gel) decreased with increasing the hydrophobicity of the tertiary amine, and upon decreasing pH the onset pH value for the T(sol-gel) to begin to increase noticeably was lower for the more hydrophobic tertiary amine-containing copolymer. In addition, we studied the effect of different tertiary amines on the release behavior of FITC-dextran from 10 wt % micellar gels in an acidic medium at 37 and 27 °C. The release profiles for three studied hydrogels at 37 °C were essentially the same, suggesting that the release was dominated by the diffusion of FITC-dextran. At 27 °C, the release was significantly faster for the DEAEMA-containing copolymer, indicating that both diffusion and gel dissolution contributed to the

Hospital-acquired infections in a Nigerian tertiary health facility: An ...

African Journals Online (AJOL)

Hospital-acquired infections in a Nigerian tertiary health facility: An audit of surveillance reports. ... This study evaluated the occurrence of HAI in a foremost tertiary health facility over a 5-year period for the purpose of reinforcing control efforts. Materials and Methods: A retrospective survey of records from the infection control ...

Study on effect of mean stress on fatigue life prediction of thin film structure

Energy Technology Data Exchange (ETDEWEB)

Shin, Myung Soo [Ahtti Co., Seongnam (Korea, Republic of); Park, Jun Hyu [Tongmyong University, Busan (Korea, Republic of); Kim, Jung Yup [Korea Institute of Machinery and Materials, Daejeon (Korea, Republic of)

2016-04-15

This paper describes the effect of mean stress on fatigue life prediction of structure made with thin film. It is well known that the mean stress influences fatigue life prediction of mechanical structure. We investigated a reasonable method for considering mean stress when fatigue strength assessment of micro structure of thin film should be performed. Fatigue tests of smooth specimen of beryllium-copper (BeCu) thin film were performed in ambient air at R = 0.1 with 5 Hz. A micro probe was designed and made with BeCu thin film by the precision press process. Fatigue tests of micro structure were performed with 5 Hz frequency, in ambient air to verify the fatigue life predicted by computer simulation through FE analysis. The fatigue life predicted by the Sa -N curve modified by Goodman method with principal stress through FE analysis shows a more reasonable result than other methods.

Study on effect of mean stress on fatigue life prediction of thin film structure

International Nuclear Information System (INIS)

Shin, Myung Soo; Park, Jun Hyu; Kim, Jung Yup

2016-01-01

This paper describes the effect of mean stress on fatigue life prediction of structure made with thin film. It is well known that the mean stress influences fatigue life prediction of mechanical structure. We investigated a reasonable method for considering mean stress when fatigue strength assessment of micro structure of thin film should be performed. Fatigue tests of smooth specimen of beryllium-copper (BeCu) thin film were performed in ambient air at R = 0.1 with 5 Hz. A micro probe was designed and made with BeCu thin film by the precision press process. Fatigue tests of micro structure were performed with 5 Hz frequency, in ambient air to verify the fatigue life predicted by computer simulation through FE analysis. The fatigue life predicted by the Sa -N curve modified by Goodman method with principal stress through FE analysis shows a more reasonable result than other methods

Phocid seal leptin: tertiary structure and hydrophobic receptor binding site preservation during distinct leptin gene evolution.

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John A Hammond

Full Text Available The cytokine hormone leptin is a key signalling molecule in many pathways that control physiological functions. Although leptin demonstrates structural conservation in mammals, there is evidence of positive selection in primates, lagomorphs and chiropterans. We previously reported that the leptin genes of the grey and harbour seals (phocids have significantly diverged from other mammals. Therefore we further investigated the diversification of leptin in phocids, other marine mammals and terrestrial taxa by sequencing the leptin genes of representative species. Phylogenetic reconstruction revealed that leptin diversification was pronounced within the phocid seals with a high dN/dS ratio of 2.8, indicating positive selection. We found significant evidence of positive selection along the branch leading to the phocids, within the phocid clade, but not over the dataset as a whole. Structural predictions indicate that the individual residues under selection are away from the leptin receptor (LEPR binding site. Predictions of the surface electrostatic potential indicate that phocid seal leptin is notably different to other mammalian leptins, including the otariids. Cloning the grey seal leptin binding domain of LEPR confirmed that this was structurally conserved. These data, viewed in toto, support a hypothesis that phocid leptin divergence is unlikely to have arisen by random mutation. Based upon these phylogenetic and structural assessments, and considering the comparative physiology and varying life histories among species, we postulate that the unique phocid diving behaviour has produced this selection pressure. The Phocidae includes some of the deepest diving species, yet have the least modified lung structure to cope with pressure and volume changes experienced at depth. Therefore, greater surfactant production is required to facilitate rapid lung re-inflation upon surfacing, while maintaining patent airways. We suggest that this additional

Structural MRI-Based Predictions in Patients with Treatment-Refractory Depression (TRD.

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Blair A Johnston

Full Text Available The application of machine learning techniques to psychiatric neuroimaging offers the possibility to identify robust, reliable and objective disease biomarkers both within and between contemporary syndromal diagnoses that could guide routine clinical practice. The use of quantitative methods to identify psychiatric biomarkers is consequently important, particularly with a view to making predictions relevant to individual patients, rather than at a group-level. Here, we describe predictions of treatment-refractory depression (TRD diagnosis using structural T1-weighted brain scans obtained from twenty adult participants with TRD and 21 never depressed controls. We report 85% accuracy of individual subject diagnostic prediction. Using an automated feature selection method, the major brain regions supporting this significant classification were in the caudate, insula, habenula and periventricular grey matter. It was not, however, possible to predict the degree of 'treatment resistance' in individual patients, at least as quantified by the Massachusetts General Hospital (MGH-S clinical staging method; but the insula was again identified as a region of interest. Structural brain imaging data alone can be used to predict diagnostic status, but not MGH-S staging, with a high degree of accuracy in patients with TRD.

Interactive Intranet Portal for effective Management in Tertiary Institution

OpenAIRE

Idogho O. Philipa; Akpado Kenneth; James Agajo

2011-01-01

Interactive Intranet Portal for effective management in Tertiary Institution is an enhanced and interactive method of managing and processing key issues in Tertiary Institution, Problems of result processing, tuition fee payment, library resources management are analyzed in this work. An interface was generated to handle this problem; the software is an interactive one. Several modules are involved in the paper, like: LIBRARY CONSOLE, ADMIN, STAFF, COURSE REGISTRATION, CHECKING OF RESULTS and...

Assessment Quality in Tertiary Education: An Integrative Literature Review

OpenAIRE

Gerritsen-van Leeuwenkamp, Karin; Joosten-ten Brinke, Desirée; Kester, Liesbeth

2018-01-01

In tertiary education, inferior assessment quality is a problem that has serious consequences for students, teachers, government, and society. A lack of a clear and overarching conceptualization of assessment quality can cause difficulties in guaranteeing assessment quality in practice. Thus, the aim of this study is to conceptualize assessment quality in tertiary education by providing an overview of the assessment quality criteria, their influences, the evaluation of the assessment quality ...

Rapid fold and structure determination of the archaeal translation elongation factor 1{beta} from Methanobacterium thermoautotrophicum

Energy Technology Data Exchange (ETDEWEB)

Kozlov, Guennadi [McGill University, Department of Biochemistry (Canada); Ekiel, Irena [National Research Council of Canada, Biomolecular NMR Group, Sector of Pharmaceutical Biotechnology, Biotechnology Research Institute (Canada); Beglova, Natalia [McGill University, Department of Biochemistry (Canada); Yee, Adelinda; Dharamsi, Akil; Engel, Asaph [University of Toronto, Department of Medical Biophysics (Canada); Siddiqui, Nadeem; Nong, Andrew; Gehring, Kalle [McGill University, Department of Biochemistry (Canada)

2000-07-15

The tertiary fold of the elongation factor, aEF-1{beta}, from Methanobacterium thermoautotrophicum was determined in a high-throughput fashion using a minimal set of NMR experiments. NMR secondary structure prediction, deuterium exchange experiments and the analysis of chemical shift perturbations were combined to identify the protein fold as an alpha-beta sandwich typical of many RNA binding proteins including EF-G. Following resolution of the tertiary fold, a high resolution structure of aEF-1{beta} was determined using heteronuclear and homonuclear NMR experiments and a semi-automated NOESY assignment strategy. Analysis of the aEF-1{beta} structure revealed close similarity to its human analogue, eEF-1{beta}. In agreement with studies on EF-Ts and human EF-1{beta}, a functional mechanism for nucleotide exchange is proposed wherein Phe46 on an exposed loop acts as a lever to eject GDP from the associated elongation factor G-protein, aEF-1{alpha}. aEF-1{beta} was also found to bind calcium in the groove between helix {alpha}2 and strand {beta}4. This novel feature was not observed previously and may serve a structural function related to protein stability or may play a functional role in archaeal protein translation.

Rapid fold and structure determination of the archaeal translation elongation factor 1β from Methanobacterium thermoautotrophicum

International Nuclear Information System (INIS)

Kozlov, Guennadi; Ekiel, Irena; Beglova, Natalia; Yee, Adelinda; Dharamsi, Akil; Engel, Asaph; Siddiqui, Nadeem; Nong, Andrew; Gehring, Kalle

2000-01-01

The tertiary fold of the elongation factor, aEF-1β, from Methanobacterium thermoautotrophicum was determined in a high-throughput fashion using a minimal set of NMR experiments. NMR secondary structure prediction, deuterium exchange experiments and the analysis of chemical shift perturbations were combined to identify the protein fold as an alpha-beta sandwich typical of many RNA binding proteins including EF-G. Following resolution of the tertiary fold, a high resolution structure of aEF-1β was determined using heteronuclear and homonuclear NMR experiments and a semi-automated NOESY assignment strategy. Analysis of the aEF-1β structure revealed close similarity to its human analogue, eEF-1β. In agreement with studies on EF-Ts and human EF-1β, a functional mechanism for nucleotide exchange is proposed wherein Phe46 on an exposed loop acts as a lever to eject GDP from the associated elongation factor G-protein, aEF-1α. aEF-1β was also found to bind calcium in the groove between helix α2 and strand β4. This novel feature was not observed previously and may serve a structural function related to protein stability or may play a functional role in archaeal protein translation

Deep Learning and Applications in Computational Biology

KAUST Repository

Zeng, Jianyang

2016-01-01

In this work, we develop a general and flexible deep learning framework for modeling structural binding preferences and predicting binding sites of RBPs, which takes (predicted) RNA tertiary structural information

Tertiary Treatment Process of Preserved Wastewater

Directory of Open Access Journals (Sweden)

Wang Qingyu

2016-01-01

Full Text Available The effects of the composite coagulants on coagulation sedimentation for the preserved wastewater was investigated by changing the composite coagulant dosages, and the coagulant was composed of polymeric ferric sulfate (PFS, polyaluminium chloride (PAC, and polyaluminum ferric silicate (PAFSC, while the effect of the tertiary treatment process on the preserved wastewater was tested, which was exceeded the standard seriously. The results showed that 400 mg/L was the optimum composite coagulant dosage. The removal rates of salt and sugar were as high as 99.1% and 99.5% respectively, and the removal rates of CODCr and SS were 99.3% and 96.0%, respectively after the preserved wastewater was treated by the tertiary treatment technology, which both reached the primary standard of “The Integrated Wastewater Discharge Standard” (GB8978-1996.

Crystal structure prediction of flexible molecules using parallel genetic algorithms with a standard force field.

Science.gov (United States)

Kim, Seonah; Orendt, Anita M; Ferraro, Marta B; Facelli, Julio C

2009-10-01

This article describes the application of our distributed computing framework for crystal structure prediction (CSP) the modified genetic algorithms for crystal and cluster prediction (MGAC), to predict the crystal structure of flexible molecules using the general Amber force field (GAFF) and the CHARMM program. The MGAC distributed computing framework includes a series of tightly integrated computer programs for generating the molecule's force field, sampling crystal structures using a distributed parallel genetic algorithm and local energy minimization of the structures followed by the classifying, sorting, and archiving of the most relevant structures. Our results indicate that the method can consistently find the experimentally known crystal structures of flexible molecules, but the number of missing structures and poor ranking observed in some crystals show the need for further improvement of the potential. Copyright 2009 Wiley Periodicals, Inc.

Antibody modeling using the prediction of immunoglobulin structure (PIGS) web server [corrected].

Science.gov (United States)

Marcatili, Paolo; Olimpieri, Pier Paolo; Chailyan, Anna; Tramontano, Anna

2014-12-01

Antibodies (or immunoglobulins) are crucial for defending organisms from pathogens, but they are also key players in many medical, diagnostic and biotechnological applications. The ability to predict their structure and the specific residues involved in antigen recognition has several useful applications in all of these areas. Over the years, we have developed or collaborated in developing a strategy that enables researchers to predict the 3D structure of antibodies with a very satisfactory accuracy. The strategy is completely automated and extremely fast, requiring only a few minutes (∼10 min on average) to build a structural model of an antibody. It is based on the concept of canonical structures of antibody loops and on our understanding of the way light and heavy chains pack together.

Favorability for uranium in tertiary sedimentary rocks, southwestern Montana

International Nuclear Information System (INIS)

Wopat, M.A.; Curry, W.E.; Robins, J.W.; Marjaniemi, D.K.

1977-10-01

Tertiary sedimentary rocks in the basins of southwestern Montana were studied to determine their favorability for potential uranium resources. Uranium in the Tertiary sedimentary rocks was probably derived from the Boulder batholith and from silicic volcanic material. The batholith contains numerous uranium occurrences and is the most favorable plutonic source for uranium in the study area. Subjective favorability categories of good, moderate, and poor, based on the number and type of favorable criteria present, were used to classify the rock sequences studied. Rocks judged to have good favorability for uranium deposits are (1) Eocene and Oligocene strata and undifferentiated Tertiary rocks in the western Three Forks basin and (2) Oligocene rocks in the Helena basin. Rocks having moderate favorability consist of (1) Eocene and Oligocene strata in the Jefferson River, Beaverhead River, and lower Ruby River basins, (2) Oligocene rocks in the Townsend and Clarkston basins, (3) Miocene and Pliocene rocks in the Upper Ruby River basin, and (4) all Tertiary sedimentary formations in the eastern Three Forks basin, and in the Grasshopper Creek, Horse Prairie, Medicine Lodge Creek, Big Sheep Creek, Deer Lodge, Big Hole River, and Bull Creek basins. The following have poor favorability: (1) the Beaverhead Conglomerate in the Red Rock and Centennial basins, (2) Eocene and Oligocene rocks in the Upper Ruby River basin, (3) Miocene and Pliocene rocks in the Townsend, Clarkston, Smith River, and Divide Creek basins, (4) Miocene through Pleistocene rocks in the Jefferson River, Beaverhead River, and Lower Ruby River basins, and (5) all Tertiary sedimentary rocks in the Boulder River, Sage Creek, Muddy Creek, Madison River, Flint Creek, Gold Creek, and Bitterroot basins

Tertiary syphilis in the lumbar spine: a case report.

Science.gov (United States)

Bai, Yang; Niu, Feng; Liu, Lidi; Sha, Hui; Wang, Yimei; Zhao, Song

2017-07-24

The incidence of tertiary syphilis involvement in the spinal column with destructive bone lesions is very rare. It is difficult to establish the correct diagnosis from radiographs and histological examination alone. Limited data are available on surgical treatment to tertiary syphilitic spinal lesions. In this article, we report a case of tertiary syphilis in the lumbar spine with osteolytic lesions causing cauda equina compression. A 44-year-old man who suffered with low back pain for 6 months and progressive radiating pain at lower extremity for 1 week. Radiologic findings showed osteolytic lesion and new bone formation in the parts of the bodies of L4 and L5. Serum treponema pallidum hemagglutination (TPHA) test was positive. A surgery of posterior debridement, interbody and posterolateral allograft bone fusion with instrumentation from L3 to S1 was performed. The low back pain and numbness abated after operation. But the follow-up radiographs showed absorption of the bone grafts and failure of instrumentation. A Charcot's arthropathy was formed between L4 and L5. It is challenging to diagnose the tertiary syphilis in the spine. Surgery is a reasonable auxiliary method to antibiotic therapy for patients who suffered with neuropathy. Charcot's arthropathy should be considered as an operative complication.

Structural syntactic prediction measured with ELAN: evidence from ERPs.

Science.gov (United States)

Fonteneau, Elisabeth

2013-02-08

The current study used event-related potentials (ERPs) to investigate how and when argument structure information is used during the processing of sentences with a filler-gap dependency. We hypothesize that one specific property - animacy (living vs. non-living) - is used by the parser during the building of the syntactic structure. Participants heard sentences that were rated off-line as having an expected noun (Who did the Lion King chase the caravan with?) or an unexpected noun (Who did Lion King chase the animal with?). This prediction is based on the animacy properties relation between the wh-word and the noun in the object position. ERPs from the noun in the unexpected condition (animal) elicited a typical Early Left Anterior Negativity (ELAN)/P600 complex compared to the noun in the expected condition (caravan). Firstly, these results demonstrate that the ELAN reflects not only grammatical category violation but also animacy property expectations in filler-gap dependency. Secondly, our data suggests that the language comprehension system is able to make detailed predictions about aspects of the upcoming words to build up the syntactic structure. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Analysis of colonoscopic perforations at a local clinic and a tertiary hospital.

Science.gov (United States)

Sagawa, Toshihiko; Kakizaki, Satoru; Iizuka, Haruhisa; Onozato, Yasuhiro; Sohara, Naondo; Okamura, Shinichi; Mori, Masatomo

2012-09-21

To define the clinical characteristics, and to assess the management of colonoscopic complications at a local clinic. A retrospective review of the medical records was performed for the patients with iatrogenic colon perforations after endoscopy at a local clinic between April 2006 and December 2010. Data obtained from a tertiary hospital in the same region were also analyzed. The underlying conditions, clinical presentations, perforation locations, treatment types (operative or conservative) and outcome data for patients at the local clinic and the tertiary hospital were compared. A total of 10  826 colonoscopies, and 2625 therapeutic procedures were performed at a local clinic and 32  148 colonoscopies, and 7787 therapeutic procedures were performed at the tertiary hospital. The clinic had no perforations during diagnostic colonoscopy and 8 (0.3%) perforations were determined to be related to therapeutic procedures. The perforation rates in each therapeutic procedure were 0.06% (1/1609) in polypectomy, 0.2% (2/885) in endoscopic mucosal resection (EMR), and 3.8% (5/131) in endoscopic submucosal dissection (ESD). Perforation rates for ESD were significantly higher than those for polypectomy or EMR (P hospital. Six perforations occurred with therapeutic endoscopy (perforation rate, 0.08%; 1 per 1298 procedures). Perforation rates for specific procedure types were 0.02% (1 per 5500) for polypectomy, 0.17% (1 per 561) for EMR, 2.3% (1 per 43) for ESD in the tertiary hospital. There were no differences in the perforation rates for each therapeutic procedure between the clinic and the tertiary hospital. The incidence of iatrogenic perforation requiring surgical treatment was quite low in both the clinic and the tertiary hospital. No procedure-related mortalities occurred. Performing closure with endoscopic clipping reduced the C-reactive protein (CRP) titers. The mean maximum CRP titer was 2.9 ± 1.6 mg/dL with clipping and 9.7 ± 6.2 mg/dL without clipping

RNA Secondary Structure Prediction by Using Discrete Mathematics: An Interdisciplinary Research Experience for Undergraduate Students

Science.gov (United States)

Ellington, Roni; Wachira, James; Nkwanta, Asamoah

2010-01-01

The focus of this Research Experience for Undergraduates (REU) project was on RNA secondary structure prediction by using a lattice walk approach. The lattice walk approach is a combinatorial and computational biology method used to enumerate possible secondary structures and predict RNA secondary structure from RNA sequences. The method uses…

Tertiary colleges: a study of perspectives on organizational innovation

OpenAIRE

Preedy, Margaret

1998-01-01

The purpose of this research study was to explore organisational innovation in education with reference to one particular type of organisation - the tertiary college. The research sought to examine the extent to which the intended objectives for new educational organisations are realised in practice, and how far the goals and ethos which organisational leaders seek to promote are shared by organisational members. The study focused on eleven tertiary colleges, comparing the 'official' view of ...

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.

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.

Identification of residue pairing in interacting β-strands from a predicted residue contact map.

Science.gov (United States)

Mao, Wenzhi; Wang, Tong; Zhang, Wenxuan; Gong, Haipeng

2018-04-19

Despite the rapid progress of protein residue contact prediction, predicted residue contact maps frequently contain many errors. However, information of residue pairing in β strands could be extracted from a noisy contact map, due to the presence of characteristic contact patterns in β-β interactions. This information may benefit the tertiary structure prediction of mainly β proteins. In this work, we propose a novel ridge-detection-based β-β contact predictor to identify residue pairing in β strands from any predicted residue contact map. Our algorithm RDb 2 C adopts ridge detection, a well-developed technique in computer image processing, to capture consecutive residue contacts, and then utilizes a novel multi-stage random forest framework to integrate the ridge information and additional features for prediction. Starting from the predicted contact map of CCMpred, RDb 2 C remarkably outperforms all state-of-the-art methods on two conventional test sets of β proteins (BetaSheet916 and BetaSheet1452), and achieves F1-scores of ~ 62% and ~ 76% at the residue level and strand level, respectively. Taking the prediction of the more advanced RaptorX-Contact as input, RDb 2 C achieves impressively higher performance, with F1-scores reaching ~ 76% and ~ 86% at the residue level and strand level, respectively. In a test of structural modeling using the top 1 L predicted contacts as constraints, for 61 mainly β proteins, the average TM-score achieves 0.442 when using the raw RaptorX-Contact prediction, but increases to 0.506 when using the improved prediction by RDb 2 C. Our method can significantly improve the prediction of β-β contacts from any predicted residue contact maps. Prediction results of our algorithm could be directly applied to effectively facilitate the practical structure prediction of mainly β proteins. All source data and codes are available at http://166.111.152.91/Downloads.html or the GitHub address of https://github.com/wzmao/RDb2C .

Prediction of the Fundamental Period of Infilled RC Frame Structures Using Artificial Neural Networks

Directory of Open Access Journals (Sweden)

Panagiotis G. Asteris

2016-01-01

Full Text Available The fundamental period is one of the most critical parameters for the seismic design of structures. There are several literature approaches for its estimation which often conflict with each other, making their use questionable. Furthermore, the majority of these approaches do not take into account the presence of infill walls into the structure despite the fact that infill walls increase the stiffness and mass of structure leading to significant changes in the fundamental period. In the present paper, artificial neural networks (ANNs are used to predict the fundamental period of infilled reinforced concrete (RC structures. For the training and the validation of the ANN, a large data set is used based on a detailed investigation of the parameters that affect the fundamental period of RC structures. The comparison of the predicted values with analytical ones indicates the potential of using ANNs for the prediction of the fundamental period of infilled RC frame structures taking into account the crucial parameters that influence its value.

Analysis of energy-based algorithms for RNA secondary structure prediction

Directory of Open Access Journals (Sweden)

Hajiaghayi Monir

2012-02-01

Full Text Available Abstract Background RNA molecules play critical roles in the cells of organisms, including roles in gene regulation, catalysis, and synthesis of proteins. Since RNA function depends in large part on its folded structures, much effort has been invested in developing accurate methods for prediction of RNA secondary structure from the base sequence. Minimum free energy (MFE predictions are widely used, based on nearest neighbor thermodynamic parameters of Mathews, Turner et al. or those of Andronescu et al. Some recently proposed alternatives that leverage partition function calculations find the structure with maximum expected accuracy (MEA or pseudo-expected accuracy (pseudo-MEA methods. Advances in prediction methods are typically benchmarked using sensitivity, positive predictive value and their harmonic mean, namely F-measure, on datasets of known reference structures. Since such benchmarks document progress in improving accuracy of computational prediction methods, it is important to understand how measures of accuracy vary as a function of the reference datasets and whether advances in algorithms or thermodynamic parameters yield statistically significant improvements. Our work advances such understanding for the MFE and (pseudo-MEA-based methods, with respect to the latest datasets and energy parameters. Results We present three main findings. First, using the bootstrap percentile method, we show that the average F-measure accuracy of the MFE and (pseudo-MEA-based algorithms, as measured on our largest datasets with over 2000 RNAs from diverse families, is a reliable estimate (within a 2% range with high confidence of the accuracy of a population of RNA molecules represented by this set. However, average accuracy on smaller classes of RNAs such as a class of 89 Group I introns used previously in benchmarking algorithm accuracy is not reliable enough to draw meaningful conclusions about the relative merits of the MFE and MEA-based algorithms

Novel structures of oxygen adsorbed on a Zr(0001) surface predicted from first principles

Energy Technology Data Exchange (ETDEWEB)

Gao, Bo [State Key Laboratory of Superhard Materials, Jilin University, Changchun, 130012 (China); Beijing computational science research center, Beijing,100084 (China); Wang, Jianyun [State Key Laboratory of Superhard Materials, Jilin University, Changchun, 130012 (China); Lv, Jian [State Key Laboratory of Superhard Materials, Jilin University, Changchun, 130012 (China); College of Materials Science and Engineering, Jilin University, Changchun, 130012 (China); Gao, Xingyu [Laboratory of Computational Physics, Institute of Applied Physics and Computational Mathematics, Beijing, 100088 (China); CAEP Software Center for High Performance Numerical Simulation, Beijing, 100088 (China); Zhao, Yafan [CAEP Software Center for High Performance Numerical Simulation, Beijing, 100088 (China); Wang, Yanchao, E-mail: wyc@calypso.cn [State Key Laboratory of Superhard Materials, Jilin University, Changchun, 130012 (China); Beijing computational science research center, Beijing,100084 (China); College of Materials Science and Engineering, Jilin University, Changchun, 130012 (China); Song, Haifeng, E-mail: song_haifeng@iapcm.ac.cn [Laboratory of Computational Physics, Institute of Applied Physics and Computational Mathematics, Beijing, 100088 (China); CAEP Software Center for High Performance Numerical Simulation, Beijing, 100088 (China); Ma, Yanming [State Key Laboratory of Superhard Materials, Jilin University, Changchun, 130012 (China); Beijing computational science research center, Beijing,100084 (China)

2017-01-30

Highlights: • Two stable structures of O adsorbed on a Zr(0001) surface are predicted with SLAM. • A stable structure of O adsorbed on a Zr(0001) surface is proposed with MLAM. • The calculated work function change is agreement with experimental value. - Abstract: The structures of O atoms adsorbed on a metal surface influence the metal properties significantly. Thus, studying O chemisorption on a Zr surface is of great interest. We investigated O adsorption on a Zr(0001) surface using our newly developed structure-searching method combined with first-principles calculations. A novel structural prototype with a unique combination of surface face-centered cubic (SFCC) and surface hexagonal close-packed (SHCP) O adsorption sites was predicted using a single-layer adsorption model (SLAM) for a 0.5 and 1.0 monolayer (ML) O coverage. First-principles calculations based on the SLAM revealed that the new predicted structures are energetically favorable compared with the well-known SFCC structures for a low O coverage (0.5 and 1.0 ML). Furthermore, on basis of our predicted SFCC + SHCP structures, a new structure within multi-layer adsorption model (MLAM) was proposed to be more stable at the O coverage of 1.0 ML, in which adsorbed O atoms occupy the SFCC + SHCP sites and the substitutional octahedral sites. The calculated work functions indicate that the SFCC + SHCP configuration has the lowest work function of all known structures at an O coverage of 0.5 ML within the SLAM, which agrees with the experimental trend of work function with variation in O coverage.

Probabilistic approaches to life prediction of nuclear plant structural components

International Nuclear Information System (INIS)

Villain, B.; Pitner, P.; Procaccia, H.

1996-01-01

In the last decade there has been an increasing interest at EDF in developing and applying probabilistic methods for a variety of purposes. In the field of structural integrity and reliability they are used to evaluate the effect of deterioration due to aging mechanisms, mainly on major passive structural components such as steam generators, pressure vessels and piping in nuclear plants. Because there can be numerous uncertainties involved in a assessment of the performance of these structural components, probabilistic methods. The benefits of a probabilistic approach are the clear treatment of uncertainly and the possibility to perform sensitivity studies from which it is possible to identify and quantify the effect of key factors and mitigative actions. They thus provide information to support effective decisions to optimize In-Service Inspection planning and maintenance strategies and for realistic lifetime prediction or reassessment. The purpose of the paper is to discuss and illustrate the methods available at EDF for probabilistic component life prediction. This includes a presentation of software tools in classical, Bayesian and structural reliability, and an application on two case studies (steam generator tube bundle, reactor pressure vessel). (authors)

Probabilistic approaches to life prediction of nuclear plant structural components

International Nuclear Information System (INIS)

Villain, B.; Pitner, P.; Procaccia, H.

1996-01-01

In the last decade there has been an increasing interest at EDF in developing and applying probabilistic methods for a variety of purposes. In the field of structural integrity and reliability they are used to evaluate the effect of deterioration due to aging mechanisms, mainly on major passive structural components such as steam generators, pressure vessels and piping in nuclear plants. Because there can be numerous uncertainties involved in an assessment of the performance of these structural components, probabilistic methods provide an attractive alternative or supplement to more conventional deterministic methods. The benefits of a probabilistic approach are the clear treatment of uncertainty and the possibility to perform sensitivity studies from which it is possible to identify and quantify the effect of key factors and mitigative actions. They thus provide information to support effective decisions to optimize In-Service Inspection planning and maintenance strategies and for realistic lifetime prediction or reassessment. The purpose of the paper is to discuss and illustrate the methods available at EDF for probabilistic component life prediction. This includes a presentation of software tools in classical, Bayesian and structural reliability, and an application on two case studies (steam generator tube bundle, reactor pressure vessel)

A constraint logic programming approach to associate 1D and 3D structural components for large protein complexes.

Science.gov (United States)

Dal Palù, Alessandro; Pontelli, Enrico; He, Jing; Lu, Yonggang

2007-01-01

The paper describes a novel framework, constructed using Constraint Logic Programming (CLP) and parallelism, to determine the association between parts of the primary sequence of a protein and alpha-helices extracted from 3D low-resolution descriptions of large protein complexes. The association is determined by extracting constraints from the 3D information, regarding length, relative position and connectivity of helices, and solving these constraints with the guidance of a secondary structure prediction algorithm. Parallelism is employed to enhance performance on large proteins. The framework provides a fast, inexpensive alternative to determine the exact tertiary structure of unknown proteins.

Rethinking the Tertiary Mathematics Curriculum

Science.gov (United States)

Petocz, Peter; Reid, Anna

2005-01-01

Mathematics curriculum at the tertiary level is located within a range of social and cultural theories, and is often constructed by academics seeking to promulgate a particular view of mathematics. We argue that such a curriculum should incorporate a real acknowledgement of the different ways in which students understand the nature of mathematics…

General Allylic C–H Alkylation with Tertiary Nucleophiles

Science.gov (United States)

2015-01-01

A general method for intermolecular allylic C–H alkylation of terminal olefins with tertiary nucleophiles has been accomplished employing palladium(II)/bis(sulfoxide) catalysis. Allylic C–H alkylation furnishes products in good yields (avg. 64%) with excellent regio- and stereoselectivity (>20:1 linear:branched, >20:1 E:Z). For the first time, the olefin scope encompasses unactivated aliphatic olefins as well as activated aromatic/heteroaromatic olefins and 1,4-dienes. The ease of appending allyl moieties onto complex scaffolds is leveraged to enable this mild and selective allylic C–H alkylation to rapidly diversify phenolic natural products. The tertiary nucleophile scope is broad and includes latent functionality for further elaboration (e.g., aliphatic alcohols, α,β-unsaturated esters). The opportunities to effect synthetic streamlining with such general C–H reactivity are illustrated in an allylic C–H alkylation/Diels–Alder reaction cascade: a reactive diene is generated via intermolecular allylic C–H alkylation and approximated to a dienophile contained within the tertiary nucleophile to furnish a common tricyclic core found in the class I galbulimima alkaloids. PMID:24641574

General allylic C-H alkylation with tertiary nucleophiles.

Science.gov (United States)

Howell, Jennifer M; Liu, Wei; Young, Andrew J; White, M Christina

2014-04-16

A general method for intermolecular allylic C-H alkylation of terminal olefins with tertiary nucleophiles has been accomplished employing palladium(II)/bis(sulfoxide) catalysis. Allylic C-H alkylation furnishes products in good yields (avg. 64%) with excellent regio- and stereoselectivity (>20:1 linear:branched, >20:1 E:Z). For the first time, the olefin scope encompasses unactivated aliphatic olefins as well as activated aromatic/heteroaromatic olefins and 1,4-dienes. The ease of appending allyl moieties onto complex scaffolds is leveraged to enable this mild and selective allylic C-H alkylation to rapidly diversify phenolic natural products. The tertiary nucleophile scope is broad and includes latent functionality for further elaboration (e.g., aliphatic alcohols, α,β-unsaturated esters). The opportunities to effect synthetic streamlining with such general C-H reactivity are illustrated in an allylic C-H alkylation/Diels-Alder reaction cascade: a reactive diene is generated via intermolecular allylic C-H alkylation and approximated to a dienophile contained within the tertiary nucleophile to furnish a common tricyclic core found in the class I galbulimima alkaloids.

Improving protein fold recognition and structural class prediction accuracies using physicochemical properties of amino acids.

Science.gov (United States)

Raicar, Gaurav; Saini, Harsh; Dehzangi, Abdollah; Lal, Sunil; Sharma, Alok

2016-08-07

Predicting the three-dimensional (3-D) structure of a protein is an important task in the field of bioinformatics and biological sciences. However, directly predicting the 3-D structure from the primary structure is hard to achieve. Therefore, predicting the fold or structural class of a protein sequence is generally used as an intermediate step in determining the protein's 3-D structure. For protein fold recognition (PFR) and structural class prediction (SCP), two steps are required - feature extraction step and classification step. Feature extraction techniques generally utilize syntactical-based information, evolutionary-based information and physicochemical-based information to extract features. In this study, we explore the importance of utilizing the physicochemical properties of amino acids for improving PFR and SCP accuracies. For this, we propose a Forward Consecutive Search (FCS) scheme which aims to strategically select physicochemical attributes that will supplement the existing feature extraction techniques for PFR and SCP. An exhaustive search is conducted on all the existing 544 physicochemical attributes using the proposed FCS scheme and a subset of physicochemical attributes is identified. Features extracted from these selected attributes are then combined with existing syntactical-based and evolutionary-based features, to show an improvement in the recognition and prediction performance on benchmark datasets. Copyright © 2016 Elsevier Ltd. All rights reserved.

Predicting Reactive Transport Dynamics in Carbonates using Initial Pore Structure

Science.gov (United States)

Menke, H. P.; Nunes, J. P. P.; Blunt, M. J.

2017-12-01

Understanding rock-fluid interaction at the pore-scale is imperative for accurate predictive modelling of carbon storage permanence. However, coupled reactive transport models are computationally expensive, requiring either a sacrifice of resolution or high performance computing to solve relatively simple geometries. Many recent studies indicate that initial pore structure many be the dominant mechanism in determining the dissolution regime. Here we investigate how well the initial pore structure is predictive of distribution and amount of dissolution during reactive flow using particle tracking on the initial image. Two samples of carbonate rock with varying initial pore space heterogeneity were reacted with reservoir condition CO2-saturated brine and scanned dynamically during reactive flow at a 4-μm resolution between 4 and 40 times using 4D X-ray micro-tomography over the course of 1.5 hours using μ-CT. Flow was modelled on the initial binarized image using a Navier-Stokes solver. Particle tracking was then run on the velocity fields, the streamlines were traced, and the streamline density was calculated both on a voxel-by-voxel and a channel-by-channel basis. The density of streamlines was then compared to the amount of dissolution in subsequent time steps during reaction. It was found that for the flow and transport regimes studied, the streamline density distribution in the initial image accurately predicted the dominant pathways of dissolution and gave good indicators of the type of dissolution regime that would later develop. This work suggests that the eventual reaction-induced changes in pore structure are deterministic rather than stochastic and can be predicted with high resolution imaging of unreacted rock.

Molecular phylogeny and predicted 3D structure of plant beta-D-N-acetylhexosaminidase.

Science.gov (United States)

Hossain, Md Anowar; Roslan, Hairul Azman

2014-01-01

beta-D-N-Acetylhexosaminidase, a family 20 glycosyl hydrolase, catalyzes the removal of β-1,4-linked N-acetylhexosamine residues from oligosaccharides and their conjugates. We constructed phylogenetic tree of β-hexosaminidases to analyze the evolutionary history and predicted functions of plant hexosaminidases. Phylogenetic analysis reveals the complex history of evolution of plant β-hexosaminidase that can be described by gene duplication events. The 3D structure of tomato β-hexosaminidase (β-Hex-Sl) was predicted by homology modeling using 1now as a template. Structural conformity studies of the best fit model showed that more than 98% of the residues lie inside the favoured and allowed regions where only 0.9% lie in the unfavourable region. Predicted 3D structure contains 531 amino acids residues with glycosyl hydrolase20b domain-I and glycosyl hydrolase20 superfamily domain-II including the (β/α)8 barrel in the central part. The α and β contents of the modeled structure were found to be 33.3% and 12.2%, respectively. Eleven amino acids were found to be involved in ligand-binding site; Asp(330) and Glu(331) could play important roles in enzyme-catalyzed reactions. The predicted model provides a structural framework that can act as a guide to develop a hypothesis for β-Hex-Sl mutagenesis experiments for exploring the functions of this class of enzymes in plant kingdom.

Protein Function Prediction Based on Sequence and Structure Information

KAUST Repository

Smaili, Fatima Z.

2016-05-25

The number of available protein sequences in public databases is increasing exponentially. However, a significant fraction of these sequences lack functional annotation which is essential to our understanding of how biological systems and processes operate. In this master thesis project, we worked on inferring protein functions based on the primary protein sequence. In the approach we follow, 3D models are first constructed using I-TASSER. Functions are then deduced by structurally matching these predicted models, using global and local similarities, through three independent enzyme commission (EC) and gene ontology (GO) function libraries. The method was tested on 250 “hard” proteins, which lack homologous templates in both structure and function libraries. The results show that this method outperforms the conventional prediction methods based on sequence similarity or threading. Additionally, our method could be improved even further by incorporating protein-protein interaction information. Overall, the method we use provides an efficient approach for automated functional annotation of non-homologous proteins, starting from their sequence.

The sequential structure of brain activation predicts skill.

Science.gov (United States)

Anderson, John R; Bothell, Daniel; Fincham, Jon M; Moon, Jungaa

2016-01-29

In an fMRI study, participants were trained to play a complex video game. They were scanned early and then again after substantial practice. While better players showed greater activation in one region (right dorsal striatum) their relative skill was better diagnosed by considering the sequential structure of whole brain activation. Using a cognitive model that played this game, we extracted a characterization of the mental states that are involved in playing a game and the statistical structure of the transitions among these states. There was a strong correspondence between this measure of sequential structure and the skill of different players. Using multi-voxel pattern analysis, it was possible to recognize, with relatively high accuracy, the cognitive states participants were in during particular scans. We used the sequential structure of these activation-recognized states to predict the skill of individual players. These findings indicate that important features about information-processing strategies can be identified from a model-based analysis of the sequential structure of brain activation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Fast computational methods for predicting protein structure from primary amino acid sequence

Science.gov (United States)

Agarwal, Pratul Kumar [Knoxville, TN

2011-07-19

The present invention provides a method utilizing primary amino acid sequence of a protein, energy minimization, molecular dynamics and protein vibrational modes to predict three-dimensional structure of a protein. The present invention also determines possible intermediates in the protein folding pathway. The present invention has important applications to the design of novel drugs as well as protein engineering. The present invention predicts the three-dimensional structure of a protein independent of size of the protein, overcoming a significant limitation in the prior art.

From structure prediction to genomic screens for novel non-coding RNAs.

Science.gov (United States)

Gorodkin, Jan; Hofacker, Ivo L

2011-08-01

Non-coding RNAs (ncRNAs) are receiving more and more attention not only as an abundant class of genes, but also as regulatory structural elements (some located in mRNAs). A key feature of RNA function is its structure. Computational methods were developed early for folding and prediction of RNA structure with the aim of assisting in functional analysis. With the discovery of more and more ncRNAs, it has become clear that a large fraction of these are highly structured. Interestingly, a large part of the structure is comprised of regular Watson-Crick and GU wobble base pairs. This and the increased amount of available genomes have made it possible to employ structure-based methods for genomic screens. The field has moved from folding prediction of single sequences to computational screens for ncRNAs in genomic sequence using the RNA structure as the main characteristic feature. Whereas early methods focused on energy-directed folding of single sequences, comparative analysis based on structure preserving changes of base pairs has been efficient in improving accuracy, and today this constitutes a key component in genomic screens. Here, we cover the basic principles of RNA folding and touch upon some of the concepts in current methods that have been applied in genomic screens for de novo RNA structures in searches for novel ncRNA genes and regulatory RNA structure on mRNAs. We discuss the strengths and weaknesses of the different strategies and how they can complement each other.

Bayesian Inference using Neural Net Likelihood Models for Protein Secondary Structure Prediction

Directory of Open Access Journals (Sweden)

Seong-Gon Kim

2011-06-01

Full Text Available Several techniques such as Neural Networks, Genetic Algorithms, Decision Trees and other statistical or heuristic methods have been used to approach the complex non-linear task of predicting Alpha-helicies, Beta-sheets and Turns of a proteins secondary structure in the past. This project introduces a new machine learning method by using an offline trained Multilayered Perceptrons (MLP as the likelihood models within a Bayesian Inference framework to predict secondary structures proteins. Varying window sizes are used to extract neighboring amino acid information and passed back and forth between the Neural Net models and the Bayesian Inference process until there is a convergence of the posterior secondary structure probability.

bilingualism in the english of tertiary students: a sine-qua-non

African Journals Online (AJOL)

REV YOUNG EZENWA OBIOHA

questions were used to investigate the effects of Bilingualism on the English of tertiary students. A total of three hundred students from two tertiary institutions were used. ... thoughts, inner feelings, personal psychological ... Chinese migration to the U.S.A (Akindele & ... child is taught Mathematical multiplication and division ...

Kinematics of Post-obduction Deformation of the Tertiary Ridge at Al-Khod Village (Muscat, Oman

Directory of Open Access Journals (Sweden)

Andreas Scharf

2016-11-01

Full Text Available Structural investigations in post-obductional Paleocene to Eocene limestones of the Tertiary Ridge reveal a ~1 km long WNW-ESE striking strike-slip fault system within the ridge, consisting of two main sub-parallel, strike-slip faults. Considering the geometry of the Harding Strain Ellipse, the orientation of structures between the two strike-slip faults (e.g., Riedel shears, folds, reverse faults point to left-lateral motion. The abundance of large-scale folds (up to 100 m in wave length and amplitude between the two strike-slip faults led us to the interpretation of transpressive conditions in a first approximation. Moreover, the Tertiary Ridge of the study area consists of three distinct structural domains. The faults of Domain A and C are oriented WNW-ESE, but the trend of the faults in the central Domain B differs by ~10°. The left-lateral strike-slip fault system exists only in Domain B. We propose that the direction of greatest stress during Miocene plate convergence (sigma 1 was oriented 032°/212°. Considering the trend of the strike-slip zone and the orientation of sigma 1, the left-lateral motion must have been transpressive. Sigma 1 is perpendicularly oriented to the domains A and C. Prior to the Miocene D2 compressional event the study area was affected by a D1 extensional event, related to the opening of the Red Sea and the Gulf of Aden or to gravity-driven normal faulting. The D2 compressional/transpressional structures of the Miocene are reactivating the D1 structures of the Oligocene.

The prediction and discovery of Rayleigh line fine structure

International Nuclear Information System (INIS)

Fabelinskii, Immanuil L

2000-01-01

The history of the theoretical prediction and experimental discovery of the Rayleigh line fine structure (which belongs to one of the most important phenomena in optics and physics of condensed matter) is discussed along with the history of first publications concerning this topic. (from the history of physics)

Model Predictive Vibration Control Efficient Constrained MPC Vibration Control for Lightly Damped Mechanical Structures

CERN Document Server

Takács, Gergely

2012-01-01

Real-time model predictive controller (MPC) implementation in active vibration control (AVC) is often rendered difficult by fast sampling speeds and extensive actuator-deformation asymmetry. If the control of lightly damped mechanical structures is assumed, the region of attraction containing the set of allowable initial conditions requires a large prediction horizon, making the already computationally demanding on-line process even more complex. Model Predictive Vibration Control provides insight into the predictive control of lightly damped vibrating structures by exploring computationally efficient algorithms which are capable of low frequency vibration control with guaranteed stability and constraint feasibility. In addition to a theoretical primer on active vibration damping and model predictive control, Model Predictive Vibration Control provides a guide through the necessary steps in understanding the founding ideas of predictive control applied in AVC such as: ·         the implementation of ...

Epilepsy in Ireland: towards the primary-tertiary care continuum.

Science.gov (United States)

Varley, Jarlath; Delanty, Norman; Normand, Charles; Coyne, Imelda; McQuaid, Louise; Collins, Claire; Boland, Michael; Grimson, Jane; Fitzsimons, Mary

2010-01-01

Epilepsy is a chronic neurological disease affecting people of every age, gender, race and socio-economic background. The diagnosis and optimal management relies on contribution from a number of healthcare disciplines in a variety of healthcare settings. To explore the interface between primary care and specialist epilepsy services in Ireland. Using appreciative inquiry, focus groups were held with healthcare professionals (n=33) from both primary and tertiary epilepsy specialist services in Ireland. There are significant challenges to delivering a consistent high standard of epilepsy care in Ireland. The barriers that were identified are: the stigma of epilepsy, unequal access to care services, insufficient human resources, unclear communication between primary-tertiary services and lack of knowledge. Improving the management of people with epilepsy requires reconfiguration of the primary-tertiary interface and establishing clearly defined roles and formalised clinical pathways. Such initiatives require resources in the form of further education and training and increased usage of information communication technology (ICT). Epilepsy services across the primary-tertiary interface can be significantly enhanced through the implementation of a shared model of care underpinned by an electronic patient record (EPR) system and information communication technology (ICT). Better chronic disease management has the potential to halt the progression of epilepsy with ensuing benefits for patients and the healthcare system. Copyright 2009 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

First Principles Prediction of Structure, Structure Selectivity, and Thermodynamic Stability under Realistic Conditions

Energy Technology Data Exchange (ETDEWEB)

Ceder, Gerbrand [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States). Dept. of Materials and Engineering

2018-01-28

Novel materials are often the enabler for new energy technologies. In ab-initio computational materials science, method are developed to predict the behavior of materials starting from the laws of physics, so that properties can be predicted before compounds have to be synthesized and tested. As such, a virtual materials laboratory can be constructed, saving time and money. The objectives of this program were to develop first-principles theory to predict the structure and thermodynamic stability of materials. Since its inception the program focused on the development of the cluster expansion to deal with the increased complexity of complex oxides. This research led to the incorporation of vibrational degrees of freedom in ab-initio thermodynamics, developed methods for multi-component cluster expansions, included the explicit configurational degrees of freedom of localized electrons, developed the formalism for stability in aqueous environments, and culminated in the first ever approach to produce exact ground state predictions of the cluster expansion. Many of these methods have been disseminated to the larger theory community through the Materials Project, pymatgen software, or individual codes. We summarize three of the main accomplishments.

Predicting and validating protein interactions using network structure.

Directory of Open Access Journals (Sweden)

Pao-Yang Chen

2008-07-01

Full Text Available Protein interactions play a vital part in the function of a cell. As experimental techniques for detection and validation of protein interactions are time consuming, there is a need for computational methods for this task. Protein interactions appear to form a network with a relatively high degree of local clustering. In this paper we exploit this clustering by suggesting a score based on triplets of observed protein interactions. The score utilises both protein characteristics and network properties. Our score based on triplets is shown to complement existing techniques for predicting protein interactions, outperforming them on data sets which display a high degree of clustering. The predicted interactions score highly against test measures for accuracy. Compared to a similar score derived from pairwise interactions only, the triplet score displays higher sensitivity and specificity. By looking at specific examples, we show how an experimental set of interactions can be enriched and validated. As part of this work we also examine the effect of different prior databases upon the accuracy of prediction and find that the interactions from the same kingdom give better results than from across kingdoms, suggesting that there may be fundamental differences between the networks. These results all emphasize that network structure is important and helps in the accurate prediction of protein interactions. The protein interaction data set and the program used in our analysis, and a list of predictions and validations, are available at http://www.stats.ox.ac.uk/bioinfo/resources/PredictingInteractions.

Cooperative activity and its potential for learning in tertiary education

Directory of Open Access Journals (Sweden)

Cirila Peklaj

2007-01-01

Full Text Available A learning situation can be structured in different ways, as an individual, competitive, or cooperative activity. Each of these structures can be used for different purposes and can lead to different learning outcomes. This paper focuses on cooperative activity and its potential for learning in tertiary education. After defining cooperative activity (or, in a broader sense, learning in interaction and introducing the CAMS theoretical framework to analyse cooperative activity, the main discussion focuses on the theoretical reasons for the usefulness of group learning and on the research of effects of cooperative learning on cognitive (metacognitive, affective-motivational and social processes in university students. The key elements that should be established for successful cooperation are also discussed. At the end, a new direction in using cooperative activity in learning—computer supported collaborative learning (CSCL, which emerged with rapid technology development in the last two decades—is presented and discussed.

Artificial Intelligence in Prediction of Secondary Protein Structure Using CB513 Database

Science.gov (United States)

Avdagic, Zikrija; Purisevic, Elvir; Omanovic, Samir; Coralic, Zlatan

2009-01-01

In this paper we describe CB513 a non-redundant dataset, suitable for development of algorithms for prediction of secondary protein structure. A program was made in Borland Delphi for transforming data from our dataset to make it suitable for learning of neural network for prediction of secondary protein structure implemented in MATLAB Neural-Network Toolbox. Learning (training and testing) of neural network is researched with different sizes of windows, different number of neurons in the hidden layer and different number of training epochs, while using dataset CB513. PMID:21347158

Prediction of protein–protein interactions: unifying evolution and structure at protein interfaces

International Nuclear Information System (INIS)

Tuncbag, Nurcan; Gursoy, Attila; Keskin, Ozlem

2011-01-01

The vast majority of the chores in the living cell involve protein–protein interactions. Providing details of protein interactions at the residue level and incorporating them into protein interaction networks are crucial toward the elucidation of a dynamic picture of cells. Despite the rapid increase in the number of structurally known protein complexes, we are still far away from a complete network. Given experimental limitations, computational modeling of protein interactions is a prerequisite to proceed on the way to complete structural networks. In this work, we focus on the question 'how do proteins interact?' rather than 'which proteins interact?' and we review structure-based protein–protein interaction prediction approaches. As a sample approach for modeling protein interactions, PRISM is detailed which combines structural similarity and evolutionary conservation in protein interfaces to infer structures of complexes in the protein interaction network. This will ultimately help us to understand the role of protein interfaces in predicting bound conformations

The Prediction of Botulinum Toxin Structure Based on in Silico and in Vitro Analysis

Science.gov (United States)

Suzuki, Tomonori; Miyazaki, Satoru

2011-01-01

Many of biological system mediated through protein-protein interactions. Knowledge of protein-protein complex structure is required for understanding the function. The determination of huge size and flexible protein-protein complex structure by experimental studies remains difficult, costly and five-consuming, therefore computational prediction of protein structures by homolog modeling and docking studies is valuable method. In addition, MD simulation is also one of the most powerful methods allowing to see the real dynamics of proteins. Here, we predict protein-protein complex structure of botulinum toxin to analyze its property. These bioinformatics methods are useful to report the relation between the flexibility of backbone structure and the activity.

Recruitment Of International Students Into Cameroon Tertiary ...

African Journals Online (AJOL)

Recruitment Of International Students Into Cameroon Tertiary Institutions In The Absence Of International Offices. ... The present system of recruiting international students is haphazardly been handled by ... AJOL African Journals Online.

Less-structured time in children's daily lives predicts self-directed executive functioning.

Science.gov (United States)

Barker, Jane E; Semenov, Andrei D; Michaelson, Laura; Provan, Lindsay S; Snyder, Hannah R; Munakata, Yuko

2014-01-01

Executive functions (EFs) in childhood predict important life outcomes. Thus, there is great interest in attempts to improve EFs early in life. Many interventions are led by trained adults, including structured training activities in the lab, and less-structured activities implemented in schools. Such programs have yielded gains in children's externally-driven executive functioning, where they are instructed on what goal-directed actions to carry out and when. However, it is less clear how children's experiences relate to their development of self-directed executive functioning, where they must determine on their own what goal-directed actions to carry out and when. We hypothesized that time spent in less-structured activities would give children opportunities to practice self-directed executive functioning, and lead to benefits. To investigate this possibility, we collected information from parents about their 6-7 year-old children's daily, annual, and typical schedules. We categorized children's activities as "structured" or "less-structured" based on categorization schemes from prior studies on child leisure time use. We assessed children's self-directed executive functioning using a well-established verbal fluency task, in which children generate members of a category and can decide on their own when to switch from one subcategory to another. The more time that children spent in less-structured activities, the better their self-directed executive functioning. The opposite was true of structured activities, which predicted poorer self-directed executive functioning. These relationships were robust (holding across increasingly strict classifications of structured and less-structured time) and specific (time use did not predict externally-driven executive functioning). We discuss implications, caveats, and ways in which potential interpretations can be distinguished in future work, to advance an understanding of this fundamental aspect of growing up.

Mesoscopic structure prediction of nanoparticle assembly and coassembly: Theoretical foundation

KAUST Repository

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

2010-01-01

structures and interactions. We validate our approach by comparing its predictions with previous simulation results for model systems. We illustrate the flexibility of our approach by applying it to hybrid systems composed of block copolymers and ligand

A retrospective review of snake bite victims admitted in a tertiary ...

African Journals Online (AJOL)

Objective: Snake bite remains major public health problem worldwide. We present our experience with cases of snake bites managed in our tertiary care teaching center of South India. Materials and Methods: The details of all patients with snake bite admitted to a tertiary teaching care hospital from 2010 to 2012 were ...

Internships enhancing entrepreneurial intent and self-efficacy: Investigating tertiary-level entrepreneurship education programmes

Directory of Open Access Journals (Sweden)

Melodi Botha

2016-09-01

Full Text Available Background: Entrepreneurship education interventions are deemed effective when they enhance interns’ entrepreneurial intent (EI and entrepreneurial self-efficacy (ESE. Notwithstanding the emergence of internship as an experiential learning approach in entrepreneurship education, evidence about their potential to foster EI and ESE lacks systemisation. Aim: The aim of this study was to determine whether internships enhance EI and ESE. Furthermore, to what extent South African tertiary institutions include internships in their entrepreneurship and management curricula and the obstacles to such inclusion. Setting: South Africa has made a concerted effort to insert an entrepreneurship component across tertiary curricula. The evolution of this entrepreneurship component to experiential learning approaches is, however, unclear. Methods: A qualitative research approach was followed. Firstly, it reviewed empirical evidence for the positive relationship between internships and EI and ESE. Secondly, it conducted a survey of entrepreneurship and business management programmes at all 23 South African tertiary institutions and content analysed the retrieved information to determine whether such programmes include internships. Finally, 10 experts were interviewed to unveil the constraints inhibiting the inclusion of internships in tertiary curricula. Results: The results revealed empirical support for the positive influence of internships on both EI and ESE. Significant lack of inclusion of internships in tertiary curricula in South Africa emerged, owing mainly to administrative issues, curriculum re-design challenges, and lack of mentoring capacity. Conclusion: Tertiary-level entrepreneurship education programmes should include an internship component. The paper suggested that tertiary institutions pilot-test the inclusion of internships with a small number of students and a selected cohort of small business owners.

Molecular Phylogeny and Predicted 3D Structure of Plant beta-D-N-Acetylhexosaminidase

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Md. Anowar Hossain

2014-01-01

Full Text Available beta-D-N-Acetylhexosaminidase, a family 20 glycosyl hydrolase, catalyzes the removal of β-1,4-linked N-acetylhexosamine residues from oligosaccharides and their conjugates. We constructed phylogenetic tree of β-hexosaminidases to analyze the evolutionary history and predicted functions of plant hexosaminidases. Phylogenetic analysis reveals the complex history of evolution of plant β-hexosaminidase that can be described by gene duplication events. The 3D structure of tomato β-hexosaminidase (β-Hex-Sl was predicted by homology modeling using 1now as a template. Structural conformity studies of the best fit model showed that more than 98% of the residues lie inside the favoured and allowed regions where only 0.9% lie in the unfavourable region. Predicted 3D structure contains 531 amino acids residues with glycosyl hydrolase20b domain-I and glycosyl hydrolase20 superfamily domain-II including the (β/α8 barrel in the central part. The α and β contents of the modeled structure were found to be 33.3% and 12.2%, respectively. Eleven amino acids were found to be involved in ligand-binding site; Asp(330 and Glu(331 could play important roles in enzyme-catalyzed reactions. The predicted model provides a structural framework that can act as a guide to develop a hypothesis for β-Hex-Sl mutagenesis experiments for exploring the functions of this class of enzymes in plant kingdom.

Characteristics and risk factors of preterm births in a tertiary center in ...

African Journals Online (AJOL)

Characteristics and risk factors of preterm births in a tertiary center in Lagos, Nigeria. ... Introduction: preterm birth is a dire complication of pregnancy that poses ... to a tertiary center for prenatal care in order to significantly reduce adverse birth ...

Computational-based structural, functional and phylogenetic analysis of Enterobacter phytases.

Science.gov (United States)

Pramanik, Krishnendu; Kundu, Shreyasi; Banerjee, Sandipan; Ghosh, Pallab Kumar; Maiti, Tushar Kanti

2018-06-01

Myo-inositol hexakisphosphate phosphohydrolases (i.e., phytases) are known to be a very important enzyme responsible for solubilization of insoluble phosphates. In the present study, Enterobacter phytases have characterized by different phylogenetic, structural and functional parameters using some standard bio-computational tools. Results showed that majority of the Enterobacter phytases are acidic in nature as most of the isoelectric points were under 7.0. The aliphatic indices predicted for the selected proteins were below 40 indicating their thermostable nature. The average molecular weight of the proteins was 48 kDa. The lower values of GRAVY of the said proteins implied that they have better interactions with water. Secondary structure prediction revealed that alpha-helical content was highest among the other forms such as sheets, coils, etc. Moreover, the predicted 3D structure of Enterobacter phytases divulged that the proteins consisted of four monomeric polypeptide chains i.e., it was a tetrameric protein. The predicted tertiary model of E. aerogenes (A0A0M3HCJ2) was deposited in Protein Model Database (Acc. No.: PM0080561) for further utilization after a thorough quality check from QMEAN and SAVES server. Functional analysis supported their classification as histidine acid phosphatases. Besides, multiple sequence alignment revealed that "DG-DP-LG" was the most highly conserved residues within the Enterobacter phytases. Thus, the present study will be useful in selecting suitable phytase-producing microbe exclusively for using in the animal food industry as a food additive.

Improved hybrid optimization algorithm for 3D protein structure prediction.

Science.gov (United States)

Zhou, Changjun; Hou, Caixia; Wei, Xiaopeng; Zhang, Qiang

2014-07-01

A new improved hybrid optimization algorithm - PGATS algorithm, which is based on toy off-lattice model, is presented for dealing with three-dimensional protein structure prediction problems. The algorithm combines the particle swarm optimization (PSO), genetic algorithm (GA), and tabu search (TS) algorithms. Otherwise, we also take some different improved strategies. The factor of stochastic disturbance is joined in the particle swarm optimization to improve the search ability; the operations of crossover and mutation that are in the genetic algorithm are changed to a kind of random liner method; at last tabu search algorithm is improved by appending a mutation operator. Through the combination of a variety of strategies and algorithms, the protein structure prediction (PSP) in a 3D off-lattice model is achieved. The PSP problem is an NP-hard problem, but the problem can be attributed to a global optimization problem of multi-extremum and multi-parameters. This is the theoretical principle of the hybrid optimization algorithm that is proposed in this paper. The algorithm combines local search and global search, which overcomes the shortcoming of a single algorithm, giving full play to the advantage of each algorithm. In the current universal standard sequences, Fibonacci sequences and real protein sequences are certified. Experiments show that the proposed new method outperforms single algorithms on the accuracy of calculating the protein sequence energy value, which is proved to be an effective way to predict the structure of proteins.

Causes and Predictive Factors Associated with "Diagnosis Changed" Outcomes in Patients Notified as Tuberculosis Cases in a Private Tertiary Hospital

OpenAIRE

Kang, Byung Ju; Jo, Kyung-Wook; Park, Tai Sun; Yoo, Jung-Wan; Lee, Sei Won; Choi, Chang-Min; Oh, Yeon-Mok; Lee, Sang-Do; Kim, Woo Sung; Kim, Dong Soon; Shim, Tae Sun

2013-01-01

Background The aim of our study was to evaluate the "diagnosis changed" rate in patients notified as tuberculosis (TB) on the Korean TB surveillance system (KTBS). Methods A total of 1,273 patients notified as TB cases on the KTBS in one private tertiary hospital in 2011 were enrolled in the present study. Patients were classified into three groups: "diagnosis maintained", "diagnosis changed" (initially notified as TB, but ultimately diagnosed as non-TB), and "administrative error" (notified ...

CompaRNA: a server for continuous benchmarking of automated methods for RNA secondary structure prediction

Science.gov (United States)

Puton, Tomasz; Kozlowski, Lukasz P.; Rother, Kristian M.; Bujnicki, Janusz M.

2013-01-01

We present a continuous benchmarking approach for the assessment of RNA secondary structure prediction methods implemented in the CompaRNA web server. As of 3 October 2012, the performance of 28 single-sequence and 13 comparative methods has been evaluated on RNA sequences/structures released weekly by the Protein Data Bank. We also provide a static benchmark generated on RNA 2D structures derived from the RNAstrand database. Benchmarks on both data sets offer insight into the relative performance of RNA secondary structure prediction methods on RNAs of different size and with respect to different types of structure. According to our tests, on the average, the most accurate predictions obtained by a comparative approach are generated by CentroidAlifold, MXScarna, RNAalifold and TurboFold. On the average, the most accurate predictions obtained by single-sequence analyses are generated by CentroidFold, ContextFold and IPknot. The best comparative methods typically outperform the best single-sequence methods if an alignment of homologous RNA sequences is available. This article presents the results of our benchmarks as of 3 October 2012, whereas the rankings presented online are continuously updated. We will gladly include new prediction methods and new measures of accuracy in the new editions of CompaRNA benchmarks. PMID:23435231

CompaRNA: a server for continuous benchmarking of automated methods for RNA secondary structure prediction.

Science.gov (United States)

Puton, Tomasz; Kozlowski, Lukasz P; Rother, Kristian M; Bujnicki, Janusz M

2013-04-01

We present a continuous benchmarking approach for the assessment of RNA secondary structure prediction methods implemented in the CompaRNA web server. As of 3 October 2012, the performance of 28 single-sequence and 13 comparative methods has been evaluated on RNA sequences/structures released weekly by the Protein Data Bank. We also provide a static benchmark generated on RNA 2D structures derived from the RNAstrand database. Benchmarks on both data sets offer insight into the relative performance of RNA secondary structure prediction methods on RNAs of different size and with respect to different types of structure. According to our tests, on the average, the most accurate predictions obtained by a comparative approach are generated by CentroidAlifold, MXScarna, RNAalifold and TurboFold. On the average, the most accurate predictions obtained by single-sequence analyses are generated by CentroidFold, ContextFold and IPknot. The best comparative methods typically outperform the best single-sequence methods if an alignment of homologous RNA sequences is available. This article presents the results of our benchmarks as of 3 October 2012, whereas the rankings presented online are continuously updated. We will gladly include new prediction methods and new measures of accuracy in the new editions of CompaRNA benchmarks.

CMsearch: simultaneous exploration of protein sequence space and structure space improves not only protein homology detection but also protein structure prediction

KAUST Repository

Cui, Xuefeng

2016-06-15

Motivation: Protein homology detection, a fundamental problem in computational biology, is an indispensable step toward predicting protein structures and understanding protein functions. Despite the advances in recent decades on sequence alignment, threading and alignment-free methods, protein homology detection remains a challenging open problem. Recently, network methods that try to find transitive paths in the protein structure space demonstrate the importance of incorporating network information of the structure space. Yet, current methods merge the sequence space and the structure space into a single space, and thus introduce inconsistency in combining different sources of information. Method: We present a novel network-based protein homology detection method, CMsearch, based on cross-modal learning. Instead of exploring a single network built from the mixture of sequence and structure space information, CMsearch builds two separate networks to represent the sequence space and the structure space. It then learns sequence–structure correlation by simultaneously taking sequence information, structure information, sequence space information and structure space information into consideration. Results: We tested CMsearch on two challenging tasks, protein homology detection and protein structure prediction, by querying all 8332 PDB40 proteins. Our results demonstrate that CMsearch is insensitive to the similarity metrics used to define the sequence and the structure spaces. By using HMM–HMM alignment as the sequence similarity metric, CMsearch clearly outperforms state-of-the-art homology detection methods and the CASP-winning template-based protein structure prediction methods.

Pain symptoms and stooling patterns do not drive diagnostic costs for children with functional abdominal pain and irritable bowel syndrome in primary or tertiary care.

Science.gov (United States)

Lane, Mariella M; Weidler, Erica M; Czyzewski, Danita I; Shulman, Robert J

2009-03-01

The objectives of this study were to (1) compare the cost of medical evaluation for children with functional abdominal pain or irritable bowel syndrome brought to a pediatric gastroenterologist versus children who remained in the care of their pediatrician, (2) compare symptom characteristics for the children in primary versus tertiary care, and (3) examine if symptom characteristics predicted the cost of medical evaluation. Eighty-nine children aged 7 to 10 years with functional abdominal pain or irritable bowel syndrome seen by a gastroenterologist (n = 46) or seen only by a pediatrician (n = 43) completed daily pain and stool diaries for 2 weeks. Mothers provided retrospective reports of their children's symptoms in the previous year. Cost of medical evaluation was calculated via chart review of diagnostic tests and application of prices as if the patients were self-pay. Child-reported diary data reflected no significant group differences with respect to pain, interference with activities, or stool characteristics. In contrast, mothers of children evaluated by a gastroenterologist viewed their children as having higher maximum pain intensity in the previous year. Excluding endoscopy costs, cost of medical evaluation was fivefold higher for children evaluated by a gastroenterologist, with higher cost across blood work, stool studies, breath testing, and diagnostic imaging. Symptom characteristics did not predict cost of care for either group. Despite the lack of difference in symptom characteristics between children in primary and tertiary care, a notable differential in cost of evaluation exists in accordance with level of care. Symptom characteristics do not seem to drive diagnostic evaluation in either primary or tertiary care. Given the lack of differences in child-reported symptoms and the maternal perspective that children evaluated by a gastroenterologist had more severe pain, we speculate that parent perception of child symptoms may be a primary factor in

From structure prediction to genomic screens for novel non-coding RNAs.

Directory of Open Access Journals (Sweden)

Jan Gorodkin

2011-08-01

Full Text Available Non-coding RNAs (ncRNAs are receiving more and more attention not only as an abundant class of genes, but also as regulatory structural elements (some located in mRNAs. A key feature of RNA function is its structure. Computational methods were developed early for folding and prediction of RNA structure with the aim of assisting in functional analysis. With the discovery of more and more ncRNAs, it has become clear that a large fraction of these are highly structured. Interestingly, a large part of the structure is comprised of regular Watson-Crick and GU wobble base pairs. This and the increased amount of available genomes have made it possible to employ structure-based methods for genomic screens. The field has moved from folding prediction of single sequences to computational screens for ncRNAs in genomic sequence using the RNA structure as the main characteristic feature. Whereas early methods focused on energy-directed folding of single sequences, comparative analysis based on structure preserving changes of base pairs has been efficient in improving accuracy, and today this constitutes a key component in genomic screens. Here, we cover the basic principles of RNA folding and touch upon some of the concepts in current methods that have been applied in genomic screens for de novo RNA structures in searches for novel ncRNA genes and regulatory RNA structure on mRNAs. We discuss the strengths and weaknesses of the different strategies and how they can complement each other.

Phylogeography and genetic structure of a Tertiary relict tree species, Tapiscia sinensis (Tapisciaceae): implications for conservation.

Science.gov (United States)

Zhang, Jinju; Li, Zuozhou; Fritsch, Peter W; Tian, Hua; Yang, Aihong; Yao, Xiaohong

2015-10-01

The phylogeography of plant species in sub-tropical China remains largely unclear. This study used Tapiscia sinensis, an endemic and endangered tree species widely but disjunctly distributed in sub-tropical China, as a model to reveal the patterns of genetic diversity and phylogeographical history of Tertiary relict plant species in this region. The implications of the results are discussed in relation to its conservation management. Samples were taken from 24 populations covering the natural geographical distribution of T. sinensis. Genetic structure was investigated by analysis of molecular variance (AMOVA) and spatial analysis of molecular variance (SAMOVA). Phylogenetic relationships among haplotypes were constructed with maximum parsimony and haplotype network methods. Historical population expansion events were tested with pairwise mismatch distribution analysis and neutrality tests. Species potential range was deduced by ecological niche modelling (ENM). A low level of genetic diversity was detected at the population level. A high level of genetic differentiation and a significant phylogeographical structure were revealed. The mean divergence time of the haplotypes was approx. 1·33 million years ago. Recent range expansion in this species is suggested by a star-like haplotype network and by the results from the mismatch distribution analysis and neutrality tests. Climatic oscillations during the Pleistocene have had pronounced effects on the extant distribution of Tapiscia relative to the Last Glacial Maximum (LGM). Spatial patterns of molecular variation and ENM suggest that T. sinensis may have retreated in south-western and central China and colonized eastern China prior to the LGM. Multiple montane refugia for T. sinense existing during the LGM are inferred in central and western China. The populations adjacent to or within these refugia of T. sinense should be given high priority in the development of conservation policies and management strategies for

Child Support Payment: A Structural Model of Predictive Variables.

Science.gov (United States)

Wright, David W.; Price, Sharon J.

A major area of concern in divorced families is compliance with child support payments. Aspects of the former spouse relationship that are predictive of compliance with court-ordered payment of child support were investigated in a sample of 58 divorced persons all of whom either paid or received child support. Structured interviews and…

Frozen Chirality of Tertiary Aromatic Amides: Access to Enantioenriched Tertiary α-Amino Acid or Amino Alcohol without Chiral Reagent.

Science.gov (United States)

Mai, Thi Thoa; Viswambharan, Baby; Gori, Didier; Guillot, Régis; Naubron, Jean-Valère; Kouklovsky, Cyrille; Alezra, Valérie

2017-04-27

One of the fundamental and intriguing aspects of life is the homochirality of the essential molecules. In this field, the absolute asymmetric synthesis of α-amino acids is a major challenge. Herein, we report access, by chemical means, to tertiary α-amino acid derivatives in up to 96 % ee without using any chiral reagent. In our strategy, the dynamic axial chirality of tertiary aromatic amides is frozen in a crystal and is responsible for the stereoselectivity of the subsequent steps. Furthermore, we could control the configuration of the final product by manually sorting and selecting the initial crystals. Based on vibrational circular dichroism studies, we could rationalize the observed stereoselectivity. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Tertiary Journalism Education: Its Value in Cadet Selection at Metropolitan Media.

Science.gov (United States)

Alysen, Barbara

2001-01-01

Notes tertiary study in journalism has been a feature of the education of Australian journalists for decades, yet many industry representatives remain skeptical of its value. Finds applicants for entry-level jobs with a tertiary journalism qualification can expect to secure, on average, at least half the available positions in any cadet or trainee…

Transition and Tertiary Education: A Case Study of Mzuzu University, Malawi

Science.gov (United States)

Zozie, Paxton Andrew; Kayira, Peter Benwell

2012-01-01

This article reviews the role of guidance and counselling in Malawi in reducing dropout and easing the transition of students to tertiary education, as well as in helping them during their time in tertiary education. It begins by identifying key success factors in guidance and counselling services for learners in both developed and developing…

Hydrogen-bond coordination in organic crystal structures: statistics, predictions and applications.

Science.gov (United States)

Galek, Peter T A; Chisholm, James A; Pidcock, Elna; Wood, Peter A

2014-02-01

Statistical models to predict the number of hydrogen bonds that might be formed by any donor or acceptor atom in a crystal structure have been derived using organic structures in the Cambridge Structural Database. This hydrogen-bond coordination behaviour has been uniquely defined for more than 70 unique atom types, and has led to the development of a methodology to construct hypothetical hydrogen-bond arrangements. Comparing the constructed hydrogen-bond arrangements with known crystal structures shows promise in the assessment of structural stability, and some initial examples of industrially relevant polymorphs, co-crystals and hydrates are described.

Predicting deleterious nsSNPs: an analysis of sequence and structural attributes

Directory of Open Access Journals (Sweden)

Saqi Mansoor AS

2006-04-01

Full Text Available Abstract Background There has been an explosion in the number of single nucleotide polymorphisms (SNPs within public databases. In this study we focused on non-synonymous protein coding single nucleotide polymorphisms (nsSNPs, some associated with disease and others which are thought to be neutral. We describe the distribution of both types of nsSNPs using structural and sequence based features and assess the relative value of these attributes as predictors of function using machine learning methods. We also address the common problem of balance within machine learning methods and show the effect of imbalance on nsSNP function prediction. We show that nsSNP function prediction can be significantly improved by 100% undersampling of the majority class. The learnt rules were then applied to make predictions of function on all nsSNPs within Ensembl. Results The measure of prediction success is greatly affected by the level of imbalance in the training dataset. We found the balanced dataset that included all attributes produced the best prediction. The performance as measured by the Matthews correlation coefficient (MCC varied between 0.49 and 0.25 depending on the imbalance. As previously observed, the degree of sequence conservation at the nsSNP position is the single most useful attribute. In addition to conservation, structural predictions made using a balanced dataset can be of value. Conclusion The predictions for all nsSNPs within Ensembl, based on a balanced dataset using all attributes, are available as a DAS annotation. Instructions for adding the track to Ensembl are at http://www.brightstudy.ac.uk/das_help.html

Offspring social network structure predicts fitness in families.

Science.gov (United States)

Royle, Nick J; Pike, Thomas W; Heeb, Philipp; Richner, Heinz; Kölliker, Mathias

2012-12-22

Social structures such as families emerge as outcomes of behavioural interactions among individuals, and can evolve over time if families with particular types of social structures tend to leave more individuals in subsequent generations. The social behaviour of interacting individuals is typically analysed as a series of multiple dyadic (pair-wise) interactions, rather than a network of interactions among multiple individuals. However, in species where parents feed dependant young, interactions within families nearly always involve more than two individuals simultaneously. Such social networks of interactions at least partly reflect conflicts of interest over the provision of costly parental investment. Consequently, variation in family network structure reflects variation in how conflicts of interest are resolved among family members. Despite its importance in understanding the evolution of emergent properties of social organization such as family life and cooperation, nothing is currently known about how selection acts on the structure of social networks. Here, we show that the social network structure of broods of begging nestling great tits Parus major predicts fitness in families. Although selection at the level of the individual favours large nestlings, selection at the level of the kin-group primarily favours families that resolve conflicts most effectively.

Sexual harassment in tertiary institutions: A comparative perspective

Directory of Open Access Journals (Sweden)

Joseph Janice

2015-01-01

Full Text Available Sexual harassment is not a new phenomenon in tertiary institutions. It has been receiving considerable attention in research and the media and public awareness has increased dramatically. However, the term sexual harassment is not used uniformly across the globe because countries have defined it differently. Consequently, prevalence of sexual harassment in education varies across cultures. This paper examines sexual harassment from a comparative perspective. It specifically focuses on the definition of sexual harassment, incidence of sexual harassment of students in tertiary institutions, effects of sexual harassment on victims; and victims’ responses to sexual harassment. It also offers suggestions for curtailing sexual harassment in these institutions.

RNA 3D modules in genome-wide predictions of RNA 2D structure

DEFF Research Database (Denmark)

Theis, Corinna; Zirbel, Craig L; Zu Siederdissen, Christian Höner

2015-01-01

. These modules can, for example, occur inside structural elements which in RNA 2D predictions appear as internal loops. Hence one question is if the use of such RNA 3D information can improve the prediction accuracy of RNA secondary structure at a genome-wide level. Here, we use RNAz in combination with 3D......Recent experimental and computational progress has revealed a large potential for RNA structure in the genome. This has been driven by computational strategies that exploit multiple genomes of related organisms to identify common sequences and secondary structures. However, these computational...... approaches have two main challenges: they are computationally expensive and they have a relatively high false discovery rate (FDR). Simultaneously, RNA 3D structure analysis has revealed modules composed of non-canonical base pairs which occur in non-homologous positions, apparently by independent evolution...

The equity imperative in tertiary education: Promoting fairness and efficiency

Science.gov (United States)

Salmi, Jamil; Bassett, Roberta Malee

2014-06-01

While the share of the tertiary education age cohort (19-25) which is being given the opportunity to study has increased worldwide over the past two decades, this does not in fact translate into reduced inequality. For many young people, especially in the developing world, major obstacles such as disparities in terms of gender, minority population membership or disabilities as well as academic and financial barriers are still standing in their way. The authors of this article propose a conceptual framework to analyse equity issues in tertiary education and document the scope, significance and consequences of disparities in tertiary education opportunities. They throw some light on the main determinants of these inequalities and offer suggestions about effective equity promotion policies directed towards widening participation and improving the chances of success of underprivileged youths in order to create societies which uphold humanistic values.

Prediction of protein-protein interaction sites in sequences and 3D structures by random forests.

Directory of Open Access Journals (Sweden)

Mile Sikić

2009-01-01

Full Text Available Identifying interaction sites in proteins provides important clues to the function of a protein and is becoming increasingly relevant in topics such as systems biology and drug discovery. Although there are numerous papers on the prediction of interaction sites using information derived from structure, there are only a few case reports on the prediction of interaction residues based solely on protein sequence. Here, a sliding window approach is combined with the Random Forests method to predict protein interaction sites using (i a combination of sequence- and structure-derived parameters and (ii sequence information alone. For sequence-based prediction we achieved a precision of 84% with a 26% recall and an F-measure of 40%. When combined with structural information, the prediction performance increases to a precision of 76% and a recall of 38% with an F-measure of 51%. We also present an attempt to rationalize the sliding window size and demonstrate that a nine-residue window is the most suitable for predictor construction. Finally, we demonstrate the applicability of our prediction methods by modeling the Ras-Raf complex using predicted interaction sites as target binding interfaces. Our results suggest that it is possible to predict protein interaction sites with quite a high accuracy using only sequence information.

Prediction of material damage in orthotropic metals for virtual structural testing

OpenAIRE

Ravindran, S.

2010-01-01

Models based on the Continuum Damage Mechanics principle are increasingly used for predicting the initiation and growth of damage in materials. The growing reliance on 3-D finite element (FE) virtual structural testing demands implementation and validation of robust material models that can predict the material behaviour accurately. The use of these models within numerical analyses requires suitable material data. EU aerospace companies along with Cranfield University and other similar resear...

Predicting protein structures with a multiplayer online game

OpenAIRE

Cooper, Seth; Khatib, Firas; Treuille, Adrien; Barbero, Janos; Lee, Jeehyung; Beenen, Michael; Leaver-Fay, Andrew; Baker, David; Popović, Zoran

2010-01-01

People exert significant amounts of problem solving effort playing computer games. Simple image- and text-recognition tasks have been successfully crowd-sourced through gamesi, ii, iii, but it is not clear if more complex scientific problems can be similarly solved with human-directed computing. Protein structure prediction is one such problem: locating the biologically relevant native conformation of a protein is a formidable computational challenge given the very large size of the search sp...

Why Is There a Glass Ceiling for Threading Based Protein Structure Prediction Methods?

Science.gov (United States)

Skolnick, Jeffrey; Zhou, Hongyi

2017-04-20

Despite their different implementations, comparison of the best threading approaches to the prediction of evolutionary distant protein structures reveals that they tend to succeed or fail on the same protein targets. This is true despite the fact that the structural template library has good templates for all cases. Thus, a key question is why are certain protein structures threadable while others are not. Comparison with threading results on a set of artificial sequences selected for stability further argues that the failure of threading is due to the nature of the protein structures themselves. Using a new contact map based alignment algorithm, we demonstrate that certain folds are highly degenerate in that they can have very similar coarse grained fractions of native contacts aligned and yet differ significantly from the native structure. For threadable proteins, this is not the case. Thus, contemporary threading approaches appear to have reached a plateau, and new approaches to structure prediction are required.

Advancing viral RNA structure prediction: measuring the thermodynamics of pyrimidine-rich internal loops.

Science.gov (United States)

Phan, Andy; Mailey, Katherine; Saeki, Jessica; Gu, Xiaobo; Schroeder, Susan J

2017-05-01

Accurate thermodynamic parameters improve RNA structure predictions and thus accelerate understanding of RNA function and the identification of RNA drug binding sites. Many viral RNA structures, such as internal ribosome entry sites, have internal loops and bulges that are potential drug target sites. Current models used to predict internal loops are biased toward small, symmetric purine loops, and thus poorly predict asymmetric, pyrimidine-rich loops with >6 nucleotides (nt) that occur frequently in viral RNA. This article presents new thermodynamic data for 40 pyrimidine loops, many of which can form UU or protonated CC base pairs. Uracil and protonated cytosine base pairs stabilize asymmetric internal loops. Accurate prediction rules are presented that account for all thermodynamic measurements of RNA asymmetric internal loops. New loop initiation terms for loops with >6 nt are presented that do not follow previous assumptions that increasing asymmetry destabilizes loops. Since the last 2004 update, 126 new loops with asymmetry or sizes greater than 2 × 2 have been measured. These new measurements significantly deepen and diversify the thermodynamic database for RNA. These results will help better predict internal loops that are larger, pyrimidine-rich, and occur within viral structures such as internal ribosome entry sites. © 2017 Phan et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Assessing the Influence of Advertising on Student Enrolment in Private Tertiary Institutions in Ghana

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Bede Akorige Atarah

2014-03-01

Full Text Available Abstract Private tertiary institutions have increasingly advertised their products in recent years to the general public in Ghana through various media. The desire to find out whether these institutions just copy other business entities blindly or that advertising actually helps in increasing their enrolments led to this study. The main aim of the study was to find out if advertising had an influence on students’ enrolment decision in private tertiary institutions. Two private universities were selected and all the students along with the admission/marketing officers of the institutions were targeted. Structured questionnaires were used to collect data from the students and unstructured interviews were organised to gather data from the admission/marketing officers. Statistical package for social sciences (SPSS was used to analyse the data. The results showed that advertising in addition to serving as a source of information to students also influenced the enrolment decision of some students. There were however other factors that influenced the enrolment decision of students such as family, friends, current students, etc that could be exploited by these institutions to their advantage.

Computational tools for experimental determination and theoretical prediction of protein structure

Energy Technology Data Exchange (ETDEWEB)

O`Donoghue, S.; Rost, B.

1995-12-31

This tutorial was one of eight tutorials selected to be presented at the Third International Conference on Intelligent Systems for Molecular Biology which was held in the United Kingdom from July 16 to 19, 1995. The authors intend to review the state of the art in the experimental determination of protein 3D structure (focus on nuclear magnetic resonance), and in the theoretical prediction of protein function and of protein structure in 1D, 2D and 3D from sequence. All the atomic resolution structures determined so far have been derived from either X-ray crystallography (the majority so far) or Nuclear Magnetic Resonance (NMR) Spectroscopy (becoming increasingly more important). The authors briefly describe the physical methods behind both of these techniques; the major computational methods involved will be covered in some detail. They highlight parallels and differences between the methods, and also the current limitations. Special emphasis will be given to techniques which have application to ab initio structure prediction. Large scale sequencing techniques increase the gap between the number of known proteins sequences and that of known protein structures. They describe the scope and principles of methods that contribute successfully to closing that gap. Emphasis will be given on the specification of adequate testing procedures to validate such methods.

Empirical modeling of information communication technology usage behaviour among business education teachers in tertiary colleges of a developing country

Directory of Open Access Journals (Sweden)

Dauda Dansarki Isiyaku

2015-11-01

Full Text Available This study has empirically tested the fitness of a structural model in explaining the influence of two exogenous variables (perceived enjoyment and attitude towards ICTs on two endogenous variables (behavioural intention and teachers' Information Communication Technology (ICT usage behavior, based on the proposition of Technology Acceptance Model (Davis, 1989a. The sample was 212 teachers from Business Education faculties of 13 tertiary colleges in the northwestern region of Nigeria. As one of the major developing countries in Africa, Nigeria has invested a lot of resources in ICTs for the past several years to ensure the appropriate uptake and integration of technology across the important sectors of the country's economy, especially the education sector. Unfortunately, the country's standard of ICT adoption has remained low for many years. Congruently, its educational sector has remained incapacitated by lack of adequate ICT facilities and lack of skilled ICT-manpower, with school teachers using obsolete tools in the classroom, and some of them buying and using ICTs out of their own volition. Teachers' use of ICTs in tertiary schools' has remained poor in Nigeria, and research initiatives on ICT usage behaviour are rare and predominantly descriptive in nature. Past studies have dwelt on investigating the influence of physical infrastructural facilities on teachers' use of technology in the classroom. The current study has investigated the influence of teachers' perceptive beliefs, attitudes and intentions on their technology usage behaviour, using Structural Equation Modeling (SEM. Findings have shown that teachers' perceived enjoyment of ICTs influences their ICT usage behaviour in the classroom (β = .281, p < .05; teachers' perceived enjoyment of ICTs influences their intention to use ICTs (β = .740, p < .001; teachers' ICT attitude influences their intention to use ICTs (β = .122, p < .05; teachers' ICT attitude influences their ICT

Integrating chemical footprinting data into RNA secondary structure prediction.

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Kourosh Zarringhalam

Full Text Available Chemical and enzymatic footprinting experiments, such as shape (selective 2'-hydroxyl acylation analyzed by primer extension, yield important information about RNA secondary structure. Indeed, since the [Formula: see text]-hydroxyl is reactive at flexible (loop regions, but unreactive at base-paired regions, shape yields quantitative data about which RNA nucleotides are base-paired. Recently, low error rates in secondary structure prediction have been reported for three RNAs of moderate size, by including base stacking pseudo-energy terms derived from shape data into the computation of minimum free energy secondary structure. Here, we describe a novel method, RNAsc (RNA soft constraints, which includes pseudo-energy terms for each nucleotide position, rather than only for base stacking positions. We prove that RNAsc is self-consistent, in the sense that the nucleotide-specific probabilities of being unpaired in the low energy Boltzmann ensemble always become more closely correlated with the input shape data after application of RNAsc. From this mathematical perspective, the secondary structure predicted by RNAsc should be 'correct', in as much as the shape data is 'correct'. We benchmark RNAsc against the previously mentioned method for eight RNAs, for which both shape data and native structures are known, to find the same accuracy in 7 out of 8 cases, and an improvement of 25% in one case. Furthermore, we present what appears to be the first direct comparison of shape data and in-line probing data, by comparing yeast asp-tRNA shape data from the literature with data from in-line probing experiments we have recently performed. With respect to several criteria, we find that shape data appear to be more robust than in-line probing data, at least in the case of asp-tRNA.

GalaxyHomomer: a web server for protein homo-oligomer structure prediction from a monomer sequence or structure.

Science.gov (United States)

Baek, Minkyung; Park, Taeyong; Heo, Lim; Park, Chiwook; Seok, Chaok

2017-07-03

Homo-oligomerization of proteins is abundant in nature, and is often intimately related with the physiological functions of proteins, such as in metabolism, signal transduction or immunity. Information on the homo-oligomer structure is therefore important to obtain a molecular-level understanding of protein functions and their regulation. Currently available web servers predict protein homo-oligomer structures either by template-based modeling using homo-oligomer templates selected from the protein structure database or by ab initio docking of monomer structures resolved by experiment or predicted by computation. The GalaxyHomomer server, freely accessible at http://galaxy.seoklab.org/homomer, carries out template-based modeling, ab initio docking or both depending on the availability of proper oligomer templates. It also incorporates recently developed model refinement methods that can consistently improve model quality. Moreover, the server provides additional options that can be chosen by the user depending on the availability of information on the monomer structure, oligomeric state and locations of unreliable/flexible loops or termini. The performance of the server was better than or comparable to that of other available methods when tested on benchmark sets and in a recent CASP performed in a blind fashion. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Evaluation of multiple protein docking structures using correctly predicted pairwise subunits

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Esquivel-Rodríguez Juan

2012-03-01

Full Text Available Abstract Background Many functionally important proteins in a cell form complexes with multiple chains. Therefore, computational prediction of multiple protein complexes is an important task in bioinformatics. In the development of multiple protein docking methods, it is important to establish a metric for evaluating prediction results in a reasonable and practical fashion. However, since there are only few works done in developing methods for multiple protein docking, there is no study that investigates how accurate structural models of multiple protein complexes should be to allow scientists to gain biological insights. Methods We generated a series of predicted models (decoys of various accuracies by our multiple protein docking pipeline, Multi-LZerD, for three multi-chain complexes with 3, 4, and 6 chains. We analyzed the decoys in terms of the number of correctly predicted pair conformations in the decoys. Results and conclusion We found that pairs of chains with the correct mutual orientation exist even in the decoys with a large overall root mean square deviation (RMSD to the native. Therefore, in addition to a global structure similarity measure, such as the global RMSD, the quality of models for multiple chain complexes can be better evaluated by using the local measurement, the number of chain pairs with correct mutual orientation. We termed the fraction of correctly predicted pairs (RMSD at the interface of less than 4.0Å as fpair and propose to use it for evaluation of the accuracy of multiple protein docking.

De novo prediction of human chromosome structures: Epigenetic marking patterns encode genome architecture.

Science.gov (United States)

Di Pierro, Michele; Cheng, Ryan R; Lieberman Aiden, Erez; Wolynes, Peter G; Onuchic, José N

2017-11-14

Inside the cell nucleus, genomes fold into organized structures that are characteristic of cell type. Here, we show that this chromatin architecture can be predicted de novo using epigenetic data derived from chromatin immunoprecipitation-sequencing (ChIP-Seq). We exploit the idea that chromosomes encode a 1D sequence of chromatin structural types. Interactions between these chromatin types determine the 3D structural ensemble of chromosomes through a process similar to phase separation. First, a neural network is used to infer the relation between the epigenetic marks present at a locus, as assayed by ChIP-Seq, and the genomic compartment in which those loci reside, as measured by DNA-DNA proximity ligation (Hi-C). Next, types inferred from this neural network are used as an input to an energy landscape model for chromatin organization [Minimal Chromatin Model (MiChroM)] to generate an ensemble of 3D chromosome conformations at a resolution of 50 kilobases (kb). After training the model, dubbed Maximum Entropy Genomic Annotation from Biomarkers Associated to Structural Ensembles (MEGABASE), on odd-numbered chromosomes, we predict the sequences of chromatin types and the subsequent 3D conformational ensembles for the even chromosomes. We validate these structural ensembles by using ChIP-Seq tracks alone to predict Hi-C maps, as well as distances measured using 3D fluorescence in situ hybridization (FISH) experiments. Both sets of experiments support the hypothesis of phase separation being the driving process behind compartmentalization. These findings strongly suggest that epigenetic marking patterns encode sufficient information to determine the global architecture of chromosomes and that de novo structure prediction for whole genomes may be increasingly possible. Copyright © 2017 the Author(s). Published by PNAS.

Learning Enhancement in Tertiary Institutions Using Mobile ...

African Journals Online (AJOL)

2012-12-01

Dec 1, 2012 ... model that is still by far the dominant mode of education and learning in tertiary institutions. In addition to identifying ... education has there been a technology that ..... Determinant of Mobile Learning Acceptance: An Empirical.

Reduction in lipophilicity improved the solubility, plasma–protein binding, and permeability of tertiary sulfonamide RORc inverse agonists

Energy Technology Data Exchange (ETDEWEB)

Fauber, Benjamin P.; René, Olivier; de Leon Boenig, Gladys; Burton, Brenda; Deng, Yuzhong; Eidenschenk, Céline; Everett, Christine; Gobbi, Alberto; Hymowitz, Sarah G.; Johnson, Adam R.; La, Hank; Liimatta, Marya; Lockey, Peter; Norman, Maxine; Ouyang, Wenjun; Wang, Weiru; Wong, Harvey (Genentech); (Argenta)

2014-08-01

Using structure-based drug design principles, we identified opportunities to reduce the lipophilicity of our tertiary sulfonamide RORc inverse agonists. The new analogs possessed improved RORc cellular potencies with >77-fold selectivity for RORc over other nuclear receptors in our cell assay suite. The reduction in lipophilicity also led to an increased plasma–protein unbound fraction and improvements in cellular permeability and aqueous solubility.

Structural properties of MHC class II ligands, implications for the prediction of MHC class II epitopes.

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Kasper Winther Jørgensen

2010-12-01

Full Text Available Major Histocompatibility class II (MHC-II molecules sample peptides from the extracellular space allowing the immune system to detect the presence of foreign microbes from this compartment. Prediction of MHC class II ligands is complicated by the open binding cleft of the MHC class II molecule, allowing binding of peptides extending out of the binding groove. Furthermore, only a few HLA-DR alleles have been characterized with a sufficient number of peptides (100-200 peptides per allele to derive accurate description of their binding motif. Little work has been performed characterizing structural properties of MHC class II ligands. Here, we perform one such large-scale analysis. A large set of SYFPEITHI MHC class II ligands covering more than 20 different HLA-DR molecules was analyzed in terms of their secondary structure and surface exposure characteristics in the context of the native structure of the corresponding source protein. We demonstrated that MHC class II ligands are significantly more exposed and have significantly more coil content than other peptides in the same protein with similar predicted binding affinity. We next exploited this observation to derive an improved prediction method for MHC class II ligands by integrating prediction of MHC- peptide binding with prediction of surface exposure and protein secondary structure. This combined prediction method was shown to significantly outperform the state-of-the-art MHC class II peptide binding prediction method when used to identify MHC class II ligands. We also tried to integrate N- and O-glycosylation in our prediction methods but this additional information was found not to improve prediction performance. In summary, these findings strongly suggest that local structural properties influence antigen processing and/or the accessibility of peptides to the MHC class II molecule.

A Collaborative Governance Approach to Improving Tertiary Education in Papua New Guinea

Science.gov (United States)

Eldridge, Kaye; Larry, Lisa; Baird, Jeanette; Kavanamur, David

2018-01-01

Tertiary education in Papua New Guinea (PNG) is in a critical state, as the sector struggles to address increased demand for student places with severely curtailed capacity. Recent thinking about improving public services in PNG has emphasized "whole of sector" or collaborative governance. Such an approach in tertiary education has the…

Prediction of elastic-plastic response of structural elements subjected to cyclic loading

International Nuclear Information System (INIS)

El Haddad, M.H.; Samaan, S.

1985-01-01

A simplified elastic-plastic analysis is developed to predict stress strain and force deformation response of structural metallic elements subjected to irregular cyclic loadings. In this analysis a simple elastic-plastic method for predicting the skeleton force deformation curve is developed. In this method, elastic and fully plastic solutions are first obtained for unknown quantities, such as deflection or local strains. Elastic and fully plastic contributions are then combined to obtain an elastic-plastic solution. The skeleton curve is doubled to establish the shape of the hysteresis loop. The complete force deformation response can therefore be simulated through reversal by reversal in accordance with hysteresis looping and material memory. Several examples of structural elements with various cross sections made from various materials and subjected to irregular cyclic loadings, are analysed. A close agreement is obtained between experimental results found in the literature and present predictions. (orig.)

Inelastic spectra to predict period elongation of structures under earthquake loading

DEFF Research Database (Denmark)

Katsanos, Evangelos; Sextos, A.G.

2015-01-01

Period lengthening, exhibited by structures when subjected to strong ground motions, constitutes an implicit proxy of structural inelasticity and associated damage. However, the reliable prediction of the inelastic period is tedious and a multi-parametric task, which is related to both epistemic ...... for period lengthening as a function of Ry and Tel. These equations may be used in the framework of the earthquake record selection and scaling....

Protein Loop Structure Prediction Using Conformational Space Annealing.

Science.gov (United States)

Heo, Seungryong; Lee, Juyong; Joo, Keehyoung; Shin, Hang-Cheol; Lee, Jooyoung

2017-05-22

We have developed a protein loop structure prediction method by combining a new energy function, which we call E PLM (energy for protein loop modeling), with the conformational space annealing (CSA) global optimization algorithm. The energy function includes stereochemistry, dynamic fragment assembly, distance-scaled finite ideal gas reference (DFIRE), and generalized orientation- and distance-dependent terms. For the conformational search of loop structures, we used the CSA algorithm, which has been quite successful in dealing with various hard global optimization problems. We assessed the performance of E PLM with two widely used loop-decoy sets, Jacobson and RAPPER, and compared the results against the DFIRE potential. The accuracy of model selection from a pool of loop decoys as well as de novo loop modeling starting from randomly generated structures was examined separately. For the selection of a nativelike structure from a decoy set, E PLM was more accurate than DFIRE in the case of the Jacobson set and had similar accuracy in the case of the RAPPER set. In terms of sampling more nativelike loop structures, E PLM outperformed E DFIRE for both decoy sets. This new approach equipped with E PLM and CSA can serve as the state-of-the-art de novo loop modeling method.

Mapping monomeric threading to protein-protein structure prediction.

Science.gov (United States)

Guerler, Aysam; Govindarajoo, Brandon; Zhang, Yang

2013-03-25

The key step of template-based protein-protein structure prediction is the recognition of complexes from experimental structure libraries that have similar quaternary fold. Maintaining two monomer and dimer structure libraries is however laborious, and inappropriate library construction can degrade template recognition coverage. We propose a novel strategy SPRING to identify complexes by mapping monomeric threading alignments to protein-protein interactions based on the original oligomer entries in the PDB, which does not rely on library construction and increases the efficiency and quality of complex template recognitions. SPRING is tested on 1838 nonhomologous protein complexes which can recognize correct quaternary template structures with a TM score >0.5 in 1115 cases after excluding homologous proteins. The average TM score of the first model is 60% and 17% higher than that by HHsearch and COTH, respectively, while the number of targets with an interface RMSD benchmark proteins. Although the relative performance of SPRING and ZDOCK depends on the level of homology filters, a combination of the two methods can result in a significantly higher model quality than ZDOCK at all homology thresholds. These data demonstrate a new efficient approach to quaternary structure recognition that is ready to use for genome-scale modeling of protein-protein interactions due to the high speed and accuracy.

Life Cycle Assessment of urban wastewater reuse with ozonation as tertiary treatment

International Nuclear Information System (INIS)

Munoz, Ivan; Rodriguez, Antonio; Rosal, Roberto; Fernandez-Alba, Amadeo R.

2009-01-01

Life Cycle Assessment has been used to compare different scenarios involving wastewater reuse, with special focus on toxicity-related impact categories. The study is based on bench-scale experiments applying ozone and ozone in combination with hydrogen peroxide to a wastewater effluent from a Spanish sewage treatment plant. Two alternative characterisation models have been used to account for toxicity of chemical substances, namely USES-LCA and EDIP97. Four alternative scenarios have been assessed: wastewater discharge plus desalination supply, wastewater reuse without tertiary treatment, wastewater reuse after applying a tertiary treatment consisting on ozonation, and wastewater reuse after applying ozonation in combination with hydrogen peroxide. The results highlight the importance of including wastewater pollutants in LCA of wastewater systems assessing toxicity, since the contribution of wastewater pollutants to the overall toxicity scores in this case study can be above 90%. Key pollutants here are not only heavy metals and other priority pollutants, but also non-regulated pollutants such as pharmaceuticals and personal care products. Wastewater reuse after applying any of the tertiary treatments considered appears as the best choice from an ecotoxicity perspective. As for human toxicity, differences between scenarios are smaller, and taking into account the experimental and modelling uncertainty, the benefits of tertiary treatment are not so clear. From a global warming potential perspective, tertiary treatments involve a potential 85% reduction of greenhouse gas emissions when compared with desalination

Structure-based function prediction of the expanding mollusk tyrosinase family

Science.gov (United States)

Huang, Ronglian; Li, Li; Zhang, Guofan

2017-11-01

Tyrosinase (Ty) is a common enzyme found in many different animal groups. In our previous study, genome sequencing revealed that the Ty family is expanded in the Pacific oyster ( Crassostrea gigas). Here, we examine the larger number of Ty family members in the Pacific oyster by high-level structure prediction to obtain more information about their function and evolution, especially the unknown role in biomineralization. We verified 12 Ty gene sequences from Crassostrea gigas genome and Pinctada fucata martensii transcriptome. By using phylogenetic analysis of these Tys with functionally known Tys from other molluscan species, eight subgroups were identified (CgTy_s1, CgTy_s2, MolTy_s1, MolTy-s2, MolTy-s3, PinTy-s1, PinTy-s2 and PviTy). Structural data and surface pockets of the dinuclear copper center in the eight subgroups of molluscan Ty were obtained using the latest versions of prediction online servers. Structural comparison with other Ty proteins from the protein databank revealed functionally important residues (HA1, HA2, HA3, HB1, HB2, HB3, Z1-Z9) and their location within these protein structures. The structural and chemical features of these pockets which may related to the substrate binding showed considerable variability among mollusks, which undoubtedly defines Ty substrate binding. Finally, we discuss the potential driving forces of Ty family evolution in mollusks. Based on these observations, we conclude that the Ty family has rapidly evolved as a consequence of substrate adaptation in mollusks.

QuaBingo: A Prediction System for Protein Quaternary Structure Attributes Using Block Composition

Directory of Open Access Journals (Sweden)

Chi-Hua Tung

2016-01-01

Full Text Available Background. Quaternary structures of proteins are closely relevant to gene regulation, signal transduction, and many other biological functions of proteins. In the current study, a new method based on protein-conserved motif composition in block format for feature extraction is proposed, which is termed block composition. Results. The protein quaternary assembly states prediction system which combines blocks with functional domain composition, called QuaBingo, is constructed by three layers of classifiers that can categorize quaternary structural attributes of monomer, homooligomer, and heterooligomer. The building of the first layer classifier uses support vector machines (SVM based on blocks and functional domains of proteins, and the second layer SVM was utilized to process the outputs of the first layer. Finally, the result is determined by the Random Forest of the third layer. We compared the effectiveness of the combination of block composition, functional domain composition, and pseudoamino acid composition of the model. In the 11 kinds of functional protein families, QuaBingo is 23% of Matthews Correlation Coefficient (MCC higher than the existing prediction system. The results also revealed the biological characterization of the top five block compositions. Conclusions. QuaBingo provides better predictive ability for predicting the quaternary structural attributes of proteins.

An Algebro-Topological Description of Protein Domain Structure

Science.gov (United States)

Penner, Robert Clark; Knudsen, Michael; Wiuf, Carsten; Andersen, Jørgen Ellegaard

2011-01-01

The space of possible protein structures appears vast and continuous, and the relationship between primary, secondary and tertiary structure levels is complex. Protein structure comparison and classification is therefore a difficult but important task since structure is a determinant for molecular interaction and function. We introduce a novel mathematical abstraction based on geometric topology to describe protein domain structure. Using the locations of the backbone atoms and the hydrogen bonds, we build a combinatorial object – a so-called fatgraph. The description is discrete yet gives rise to a 2-dimensional mathematical surface. Thus, each protein domain corresponds to a particular mathematical surface with characteristic topological invariants, such as the genus (number of holes) and the number of boundary components. Both invariants are global fatgraph features reflecting the interconnectivity of the domain by hydrogen bonds. We introduce the notion of robust variables, that is variables that are robust towards minor changes in the structure/fatgraph, and show that the genus and the number of boundary components are robust. Further, we invesigate the distribution of different fatgraph variables and show how only four variables are capable of distinguishing different folds. We use local (secondary) and global (tertiary) fatgraph features to describe domain structures and illustrate that they are useful for classification of domains in CATH. In addition, we combine our method with two other methods thereby using primary, secondary, and tertiary structure information, and show that we can identify a large percentage of new and unclassified structures in CATH. PMID:21629687

Mesoscopic structure prediction of nanoparticle assembly and coassembly: Theoretical foundation

KAUST Repository

Hur, Kahyun

2010-01-01

In this work, we present a theoretical framework that unifies polymer field theory and density functional theory in order to efficiently predict ordered nanostructure formation of systems having considerable complexity in terms of molecular structures and interactions. We validate our approach by comparing its predictions with previous simulation results for model systems. We illustrate the flexibility of our approach by applying it to hybrid systems composed of block copolymers and ligand coated nanoparticles. We expect that our approach will enable the treatment of multicomponent self-assembly with a level of molecular complexity that approaches experimental systems. © 2010 American Institute of Physics.

Prediction of Protein Structural Classes for Low-Similarity Sequences Based on Consensus Sequence and Segmented PSSM

Directory of Open Access Journals (Sweden)

Yunyun Liang

2015-01-01

Full Text Available Prediction of protein structural classes for low-similarity sequences is useful for understanding fold patterns, regulation, functions, and interactions of proteins. It is well known that feature extraction is significant to prediction of protein structural class and it mainly uses protein primary sequence, predicted secondary structure sequence, and position-specific scoring matrix (PSSM. Currently, prediction solely based on the PSSM has played a key role in improving the prediction accuracy. In this paper, we propose a novel method called CSP-SegPseP-SegACP by fusing consensus sequence (CS, segmented PsePSSM, and segmented autocovariance transformation (ACT based on PSSM. Three widely used low-similarity datasets (1189, 25PDB, and 640 are adopted in this paper. Then a 700-dimensional (700D feature vector is constructed and the dimension is decreased to 224D by using principal component analysis (PCA. To verify the performance of our method, rigorous jackknife cross-validation tests are performed on 1189, 25PDB, and 640 datasets. Comparison of our results with the existing PSSM-based methods demonstrates that our method achieves the favorable and competitive performance. This will offer an important complementary to other PSSM-based methods for prediction of protein structural classes for low-similarity sequences.

Statistical properties of thermodynamically predicted RNA secondary structures in viral genomes

Science.gov (United States)

Spanò, M.; Lillo, F.; Miccichè, S.; Mantegna, R. N.

2008-10-01

By performing a comprehensive study on 1832 segments of 1212 complete genomes of viruses, we show that in viral genomes the hairpin structures of thermodynamically predicted RNA secondary structures are more abundant than expected under a simple random null hypothesis. The detected hairpin structures of RNA secondary structures are present both in coding and in noncoding regions for the four groups of viruses categorized as dsDNA, dsRNA, ssDNA and ssRNA. For all groups, hairpin structures of RNA secondary structures are detected more frequently than expected for a random null hypothesis in noncoding rather than in coding regions. However, potential RNA secondary structures are also present in coding regions of dsDNA group. In fact, we detect evolutionary conserved RNA secondary structures in conserved coding and noncoding regions of a large set of complete genomes of dsDNA herpesviruses.

Tertiary instability of zonal flows within the Wigner-Moyal formulation of drift turbulence

Science.gov (United States)

Zhu, Hongxuan; Ruiz, D. E.; Dodin, I. Y.

2017-10-01

The stability of zonal flows (ZFs) is analyzed within the generalized-Hasegawa-Mima model. The necessary and sufficient condition for a ZF instability, which is also known as the tertiary instability, is identified. The qualitative physics behind the tertiary instability is explained using the recently developed Wigner-Moyal formulation and the corresponding wave kinetic equation (WKE) in the geometrical-optics (GO) limit. By analyzing the drifton phase space trajectories, we find that the corrections proposed in Ref. to the WKE are critical for capturing the spatial scales characteristic for the tertiary instability. That said, we also find that this instability itself cannot be adequately described within a GO formulation in principle. Using the Wigner-Moyal equations, which capture diffraction, we analytically derive the tertiary-instability growth rate and compare it with numerical simulations. The research was sponsored by the U.S. Department of Energy.

Comparative analysis of QSAR models for predicting pK(a) of organic oxygen acids and nitrogen bases from molecular structure.

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Yu, Haiying; Kühne, Ralph; Ebert, Ralf-Uwe; Schüürmann, Gerrit

2010-11-22

For 1143 organic compounds comprising 580 oxygen acids and 563 nitrogen bases that cover more than 17 orders of experimental pK(a) (from -5.00 to 12.23), the pK(a) prediction performances of ACD, SPARC, and two calibrations of a semiempirical quantum chemical (QC) AM1 approach have been analyzed. The overall root-mean-square errors (rms) for the acids are 0.41, 0.58 (0.42 without ortho-substituted phenols with intramolecular H-bonding), and 0.55 and for the bases are 0.65, 0.70, 1.17, and 1.27 for ACD, SPARC, and both QC methods, respectively. Method-specific performances are discussed in detail for six acid subsets (phenols and aromatic and aliphatic carboxylic acids with different substitution patterns) and nine base subsets (anilines, primary, secondary and tertiary amines, meta/para-substituted and ortho-substituted pyridines, pyrimidines, imidazoles, and quinolines). The results demonstrate an overall better performance for acids than for bases but also a substantial variation across subsets. For the overall best-performing ACD, rms ranges from 0.12 to 1.11 and 0.40 to 1.21 pK(a) units for the acid and base subsets, respectively. With regard to the squared correlation coefficient r², the results are 0.86 to 0.96 (acids) and 0.79 to 0.95 (bases) for ACD, 0.77 to 0.95 (acids) and 0.85 to 0.97 (bases) for SPARC, and 0.64 to 0.87 (acids) and 0.43 to 0.83 (bases) for the QC methods, respectively. Attention is paid to structural and method-specific causes for observed pitfalls. The significant subset dependence of the prediction performances suggests a consensus modeling approach.

MemBrain: An Easy-to-Use Online Webserver for Transmembrane Protein Structure Prediction

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Yin, Xi; Yang, Jing; Xiao, Feng; Yang, Yang; Shen, Hong-Bin

2018-03-01

Membrane proteins are an important kind of proteins embedded in the membranes of cells and play crucial roles in living organisms, such as ion channels, transporters, receptors. Because it is difficult to determinate the membrane protein's structure by wet-lab experiments, accurate and fast amino acid sequence-based computational methods are highly desired. In this paper, we report an online prediction tool called MemBrain, whose input is the amino acid sequence. MemBrain consists of specialized modules for predicting transmembrane helices, residue-residue contacts and relative accessible surface area of α-helical membrane proteins. MemBrain achieves a prediction accuracy of 97.9% of A TMH, 87.1% of A P, 3.2 ± 3.0 of N-score, 3.1 ± 2.8 of C-score. MemBrain-Contact obtains 62%/64.1% prediction accuracy on training and independent dataset on top L/5 contact prediction, respectively. And MemBrain-Rasa achieves Pearson correlation coefficient of 0.733 and its mean absolute error of 13.593. These prediction results provide valuable hints for revealing the structure and function of membrane proteins. MemBrain web server is free for academic use and available at www.csbio.sjtu.edu.cn/bioinf/MemBrain/. [Figure not available: see fulltext.

Understanding Australian Aboriginal Tertiary Student Needs

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Oliver, Rhonda; Rochecouste, Judith; Bennell, Debra; Anderson, Roz; Cooper, Inala; Forrest, Simon; Exell, Mike

2013-01-01

Drawing from a study of the experiences of Australian Aboriginal and Torres Strait Islander university students, this paper presents an overview of the specific needs of these students as they enter and progress through their tertiary education. Extracts from a set of case studies developed from both staff and student interviews and an online…

Structural maturation and brain activity predict future working memory capacity during childhood development.

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Ullman, Henrik; Almeida, Rita; Klingberg, Torkel

2014-01-29

Human working memory capacity develops during childhood and is a strong predictor of future academic performance, in particular, achievements in mathematics and reading. Predicting working memory development is important for the early identification of children at risk for poor cognitive and academic development. Here we show that structural and functional magnetic resonance imaging data explain variance in children's working memory capacity 2 years later, which was unique variance in addition to that predicted using cognitive tests. While current working memory capacity correlated with frontoparietal cortical activity, the future capacity could be inferred from structure and activity in basal ganglia and thalamus. This gives a novel insight into the neural mechanisms of childhood development and supports the idea that neuroimaging can have a unique role in predicting children's cognitive development.

Integration of QUARK and I-TASSER for Ab Initio Protein Structure Prediction in CASP11.

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Zhang, Wenxuan; Yang, Jianyi; He, Baoji; Walker, Sara Elizabeth; Zhang, Hongjiu; Govindarajoo, Brandon; Virtanen, Jouko; Xue, Zhidong; Shen, Hong-Bin; Zhang, Yang

2016-09-01

We tested two pipelines developed for template-free protein structure prediction in the CASP11 experiment. First, the QUARK pipeline constructs structure models by reassembling fragments of continuously distributed lengths excised from unrelated proteins. Five free-modeling (FM) targets have the model successfully constructed by QUARK with a TM-score above 0.4, including the first model of T0837-D1, which has a TM-score = 0.736 and RMSD = 2.9 Å to the native. Detailed analysis showed that the success is partly attributed to the high-resolution contact map prediction derived from fragment-based distance-profiles, which are mainly located between regular secondary structure elements and loops/turns and help guide the orientation of secondary structure assembly. In the Zhang-Server pipeline, weakly scoring threading templates are re-ordered by the structural similarity to the ab initio folding models, which are then reassembled by I-TASSER based structure assembly simulations; 60% more domains with length up to 204 residues, compared to the QUARK pipeline, were successfully modeled by the I-TASSER pipeline with a TM-score above 0.4. The robustness of the I-TASSER pipeline can stem from the composite fragment-assembly simulations that combine structures from both ab initio folding and threading template refinements. Despite the promising cases, challenges still exist in long-range beta-strand folding, domain parsing, and the uncertainty of secondary structure prediction; the latter of which was found to affect nearly all aspects of FM structure predictions, from fragment identification, target classification, structure assembly, to final model selection. Significant efforts are needed to solve these problems before real progress on FM could be made. Proteins 2016; 84(Suppl 1):76-86. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

A 'periodic table' for protein structures.

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Taylor, William R

2002-04-11

Current structural genomics programs aim systematically to determine the structures of all proteins coded in both human and other genomes, providing a complete picture of the number and variety of protein structures that exist. In the past, estimates have been made on the basis of the incomplete sample of structures currently known. These estimates have varied greatly (between 1,000 and 10,000; see for example refs 1 and 2), partly because of limited sample size but also owing to the difficulties of distinguishing one structure from another. This distinction is usually topological, based on the fold of the protein; however, in strict topological terms (neglecting to consider intra-chain cross-links), protein chains are open strings and hence are all identical. To avoid this trivial result, topologies are determined by considering secondary links in the form of intra-chain hydrogen bonds (secondary structure) and tertiary links formed by the packing of secondary structures. However, small additions to or loss of structure can make large changes to these perceived topologies and such subjective solutions are neither robust nor amenable to automation. Here I formalize both secondary and tertiary links to allow the rigorous and automatic definition of protein topology.

RNAspa: a shortest path approach for comparative prediction of the secondary structure of ncRNA molecules

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Michaeli Shulamit

2007-10-01

Full Text Available Abstract Background In recent years, RNA molecules that are not translated into proteins (ncRNAs have drawn a great deal of attention, as they were shown to be involved in many cellular functions. One of the most important computational problems regarding ncRNA is to predict the secondary structure of a molecule from its sequence. In particular, we attempted to predict the secondary structure for a set of unaligned ncRNA molecules that are taken from the same family, and thus presumably have a similar structure. Results We developed the RNAspa program, which comparatively predicts the secondary structure for a set of ncRNA molecules in linear time in the number of molecules. We observed that in a list of several hundred suboptimal minimal free energy (MFE predictions, as provided by the RNAsubopt program of the Vienna package, it is likely that at least one suggested structure would be similar to the true, correct one. The suboptimal solutions of each molecule are represented as a layer of vertices in a graph. The shortest path in this graph is the basis for structural predictions for the molecule. We also show that RNA secondary structures can be compared very rapidly by a simple string Edit-Distance algorithm with a minimal loss of accuracy. We show that this approach allows us to more deeply explore the suboptimal structure space. Conclusion The algorithm was tested on three datasets which include several ncRNA families taken from the Rfam database. These datasets allowed for comparison of the algorithm with other methods. In these tests, RNAspa performed better than four other programs.

Protein structure based prediction of catalytic residues.

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Fajardo, J Eduardo; Fiser, Andras

2013-02-22

Worldwide structural genomics projects continue to release new protein structures at an unprecedented pace, so far nearly 6000, but only about 60% of these proteins have any sort of functional annotation. We explored a range of features that can be used for the prediction of functional residues given a known three-dimensional structure. These features include various centrality measures of nodes in graphs of interacting residues: closeness, betweenness and page-rank centrality. We also analyzed the distance of functional amino acids to the general center of mass (GCM) of the structure, relative solvent accessibility (RSA), and the use of relative entropy as a measure of sequence conservation. From the selected features, neural networks were trained to identify catalytic residues. We found that using distance to the GCM together with amino acid type provide a good discriminant function, when combined independently with sequence conservation. Using an independent test set of 29 annotated protein structures, the method returned 411 of the initial 9262 residues as the most likely to be involved in function. The output 411 residues contain 70 of the annotated 111 catalytic residues. This represents an approximately 14-fold enrichment of catalytic residues on the entire input set (corresponding to a sensitivity of 63% and a precision of 17%), a performance competitive with that of other state-of-the-art methods. We found that several of the graph based measures utilize the same underlying feature of protein structures, which can be simply and more effectively captured with the distance to GCM definition. This also has the added the advantage of simplicity and easy implementation. Meanwhile sequence conservation remains by far the most influential feature in identifying functional residues. We also found that due the rapid changes in size and composition of sequence databases, conservation calculations must be recalibrated for specific reference databases.

Extent and character of early tertiary penetrative deformation, Sonora, Northwest Mexico

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