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Sample records for unique site predicted

  1. Condition evaluation of a unique mining site

    Institute of Scientific and Technical Information of China (English)

    Liu Junsheng; Chen Frank Y.; Ma Yan; Zhang Siya

    2015-01-01

    The primary objective of this study was to evaluate the existing conditions and the stability of a mining site in which the unique features of seismicity, mining activity, hydrological conditions, geological con-ditions, environmental conditions, and future development plans were considered. In particular, the potential subsidence locations near the proposed construction site, the effects of mining boundary profile, and the influence scope of the mining activity on the neighboring areas were investigated using the finite element method. The study results indicate:(1) the overlying sandstone layer to the coal layer is the key to the stability of the mining roof; (2) the broken boundary has the most effect, followed by the arc boundary and linear boundary; (3) the safe distance from the mining boundary should be at least 400 m if the proposed structure is to be built near an active mining site. Other relevant engineering rec-ommendations are also proposed. The concluded results from this study may serve as a guide to other similar sites in the world.

  2. Event Segmentation Ability Uniquely Predicts Event Memory

    Science.gov (United States)

    Sargent, Jesse Q.; Zacks, Jeffrey M.; Hambrick, David Z.; Zacks, Rose T.; Kurby, Christopher A.; Bailey, Heather R.; Eisenberg, Michelle L.; Beck, Taylor M.

    2013-01-01

    Memory for everyday events plays a central role in tasks of daily living, autobiographical memory, and planning. Event memory depends in part on segmenting ongoing activity into meaningful units. This study examined the relationship between event segmentation and memory in a lifespan sample to answer the following question: Is the ability to segment activity into meaningful events a unique predictor of subsequent memory, or is the relationship between event perception and memory accounted for by general cognitive abilities? Two hundred and eight adults ranging from 20 to 79 years old segmented movies of everyday events and attempted to remember the events afterwards. They also completed psychometric ability tests and tests measuring script knowledge for everyday events. Event segmentation and script knowledge both explained unique variance in event memory above and beyond the psychometric measures, and did so as strongly in older as in younger adults. These results suggest that event segmentation is a basic cognitive mechanism, important for memory across the lifespan. PMID:23942350

  3. Morphological Awareness Uniquely Predicts Young Children's Chinese Character Recognition.

    Science.gov (United States)

    McBride-Chang, Catherine; Shu, Hua; Zhou, Aibao; Wat, Chun Pong; Wagner, Richard K.

    2003-01-01

    Two unique measures of morphological awareness were orally administered to kindergarten and 2nd-grade Hong Kong Chinese children. Both tasks of morphological awareness predicted unique variance in Chinese character recognition in these children, after controlling for age, phonological awareness, speeded naming, speed of processing, and vocabulary.…

  4. Unique Construction and Social Experiences in Residential Remediation Sites - 13423

    Energy Technology Data Exchange (ETDEWEB)

    Jung, Paul; Scarborough, Rebecca [Sevenson Environmental Services, Inc. 2749 Lockport Road, Niagara Falls, NY 14305 (United States)

    2013-07-01

    Sevenson Environmental Services, Inc., (Sevenson) has performed several radiological remediation projects located in residential urban areas. Over the course of these projects, there has been a wide variety of experiences encountered from construction related issues to unique social situations. Some of the construction related issues included the remediation of interior basements where contaminated material was located under the footers of the structure or was used in the mortar between cinder block or field stone foundations. Other issues included site security, maintaining furnaces or other utilities, underpinning, backfilling and restoration. In addition to the radiological hazards associated with this work there were occupational safety and industrial hygiene issues that had to be addressed to ensure the safety and health of neighboring properties and residents. The unique social situations at these job sites have included arson, theft/stolen property, assault/battery, prostitution, execution of arrest warrants for residents, discovery of drugs and paraphernalia, blood borne pathogens, and unexploded ordnance. Some of these situations have become a sort of comical urban legend throughout the organization. One situation had historical significance, involving the demolition of a house to save a tree older than the Declaration of Independence. All of these projects typically involve the excavation of early 20. century items such as advertisement signs, various old bottles (milk, Listerine, perfume, whisky) and other miscellaneous common trash items. (authors)

  5. SVM-based prediction of caspase substrate cleavage sites

    Directory of Open Access Journals (Sweden)

    Ranganathan Shoba

    2006-12-01

    Full Text Available Abstract Background Caspases belong to a class of cysteine proteases which function as critical effectors in apoptosis and inflammation by cleaving substrates immediately after unique sites. Prediction of such cleavage sites will complement structural and functional studies on substrates cleavage as well as discovery of new substrates. Recently, different computational methods have been developed to predict the cleavage sites of caspase substrates with varying degrees of success. As the support vector machines (SVM algorithm has been shown to be useful in several biological classification problems, we have implemented an SVM-based method to investigate its applicability to this domain. Results A set of unique caspase substrates cleavage sites were obtained from literature and used for evaluating the SVM method. Datasets containing (i the tetrapeptide cleavage sites, (ii the tetrapeptide cleavage sites, augmented by two adjacent residues, P1' and P2' amino acids and (iii the tetrapeptide cleavage sites with ten additional upstream and downstream flanking sequences (where available were tested. The SVM method achieved an accuracy ranging from 81.25% to 97.92% on independent test sets. The SVM method successfully predicted the cleavage of a novel caspase substrate and its mutants. Conclusion This study presents an SVM approach for predicting caspase substrate cleavage sites based on the cleavage sites and the downstream and upstream flanking sequences. The method shows an improvement over existing methods and may be useful for predicting hitherto undiscovered cleavage sites.

  6. Nematode feeding sites: unique organs in plant roots.

    Science.gov (United States)

    Kyndt, Tina; Vieira, Paulo; Gheysen, Godelieve; de Almeida-Engler, Janice

    2013-11-01

    Although generally unnoticed, nearly all crop plants have one or more species of nematodes that feed on their roots, frequently causing tremendous yield losses. The group of sedentary nematodes, which are among the most damaging plant-parasitic nematodes, cause the formation of special organs called nematode feeding sites (NFS) in the root tissue. In this review we discuss key metabolic and cellular changes correlated with NFS development, and similarities and discrepancies between different types of NFS are highlighted.

  7. Structural Perspectives on the Evolutionary Expansion of Unique Protein-Protein Binding Sites.

    Science.gov (United States)

    Goncearenco, Alexander; Shaytan, Alexey K; Shoemaker, Benjamin A; Panchenko, Anna R

    2015-09-15

    Structures of protein complexes provide atomistic insights into protein interactions. Human proteins represent a quarter of all structures in the Protein Data Bank; however, available protein complexes cover less than 10% of the human proteome. Although it is theoretically possible to infer interactions in human proteins based on structures of homologous protein complexes, it is still unclear to what extent protein interactions and binding sites are conserved, and whether protein complexes from remotely related species can be used to infer interactions and binding sites. We considered biological units of protein complexes and clustered protein-protein binding sites into similarity groups based on their structure and sequence, which allowed us to identify unique binding sites. We showed that the growth rate of the number of unique binding sites in the Protein Data Bank was much slower than the growth rate of the number of structural complexes. Next, we investigated the evolutionary roots of unique binding sites and identified the major phyletic branches with the largest expansion in the number of novel binding sites. We found that many binding sites could be traced to the universal common ancestor of all cellular organisms, whereas relatively few binding sites emerged at the major evolutionary branching points. We analyzed the physicochemical properties of unique binding sites and found that the most ancient sites were the largest in size, involved many salt bridges, and were the most compact and least planar. In contrast, binding sites that appeared more recently in the evolution of eukaryotes were characterized by a larger fraction of polar and aromatic residues, and were less compact and more planar, possibly due to their more transient nature and roles in signaling processes.

  8. Cutoff lensing: predicting catalytic sites in enzymes

    Science.gov (United States)

    Aubailly, Simon; Piazza, Francesco

    2015-10-01

    Predicting function-related amino acids in proteins with unknown function or unknown allosteric binding sites in drug-targeted proteins is a task of paramount importance in molecular biomedicine. In this paper we introduce a simple, light and computationally inexpensive structure-based method to identify catalytic sites in enzymes. Our method, termed cutoff lensing, is a general procedure consisting in letting the cutoff used to build an elastic network model increase to large values. A validation of our method against a large database of annotated enzymes shows that optimal values of the cutoff exist such that three different structure-based indicators allow one to recover a maximum of the known catalytic sites. Interestingly, we find that the larger the structures the greater the predictive power afforded by our method. Possible ways to combine the three indicators into a single figure of merit and into a specific sequential analysis are suggested and discussed with reference to the classic case of HIV-protease. Our method could be used as a complement to other sequence- and/or structure-based methods to narrow the results of large-scale screenings.

  9. Unique prediction of cannabis use severity and behaviors by delay discounting and behavioral economic demand.

    Science.gov (United States)

    Strickland, Justin C; Lile, Joshua A; Stoops, William W

    2017-07-01

    Few studies have simultaneously evaluated delay discounting and behavioral economic demand to determine their unique contribution to drug use. A recent study in cannabis users found that monetary delay discounting uniquely predicted cannabis dependence symptoms, whereas cannabis demand uniquely predicted use frequency. This study sought to replicate and extend this research by evaluating delay discounting and behavioral economic demand measures for multiple commodities and including a use quantity measure. Amazon.com's Mechanical Turk was used to sample individuals reporting recent cannabis use (n=64) and controls (n=72). Participants completed measures of monetary delay discounting as well as alcohol and cannabis delay discounting and demand. Cannabis users and controls did not differ on monetary delay discounting or alcohol delay discounting and demand. Among cannabis users, regression analyses indicated that cannabis delay discounting uniquely predicted use severity, whereas cannabis demand uniquely predicted use frequency and quantity. These effects remained significant after controlling for other delay discounting and demand measures. This research replicates previous outcomes relating delay discounting and demand with cannabis use and extends them by accounting for the contribution of multiple commodities. This research also demonstrates the ability of online crowdsourcing methods to complement traditional human laboratory techniques. Copyright © 2017 Elsevier B.V. All rights reserved.

  10. Predicted metal binding sites for phytoremediation.

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    Sharma, Ashok; Roy, Sudeep; Tripathi, Kumar Parijat; Roy, Pratibha; Mishra, Manoj; Khan, Feroz; Meena, Abha

    2009-09-05

    Metal ion binding domains are found in proteins that mediate transport, buffering or detoxification of metal ions. The objective of the study is to design and analyze metal binding motifs against the genes involved in phytoremediation. This is being done on the basis of certain pre-requisite amino-acid residues known to bind metal ions/metal complexes in medicinal and aromatic plants (MAP's). Earlier work on MAP's have shown that heavy metals accumulated by aromatic and medicinal plants do not appear in the essential oil and that some of these species are able to grow in metal contaminated sites. A pattern search against the UniProtKB/Swiss-Prot and UniProtKB/TrEMBL databases yielded true positives in each case showing the high specificity of the motifs designed for the ions of nickel, lead, molybdenum, manganese, cadmium, zinc, iron, cobalt and xenobiotic compounds. Motifs were also studied against PDB structures. Results of the study suggested the presence of binding sites on the surface of protein molecules involved. PDB structures of proteins were finally predicted for the binding sites functionality in their respective phytoremediation usage. This was further validated through CASTp server to study its physico-chemical properties. Bioinformatics implications would help in designing strategy for developing transgenic plants with increased metal binding capacity. These metal binding factors can be used to restrict metal update by plants. This helps in reducing the possibility of metal movement into the food chain.

  11. Polygamain, a new microtubule depolymerizing agent that occupies a unique pharmacophore in the colchicine site.

    Science.gov (United States)

    Hartley, R M; Peng, J; Fest, G A; Dakshanamurthy, S; Frantz, D E; Brown, M L; Mooberry, S L

    2012-03-01

    Bioassay-guided fractionation was used to isolate the lignan polygamain as the microtubule-active constituent in the crude extract of the Mountain torchwood, Amyris madrensis. Similar to the effects of the crude plant extract, polygamain caused dose-dependent loss of cellular microtubules and the formation of aberrant mitotic spindles that led to G(2)/M arrest. Polygamain has potent antiproliferative activities against a wide range of cancer cell lines, with an average IC(50) of 52.7 nM. Clonogenic studies indicate that polygamain effectively inhibits PC-3 colony formation and has excellent cellular persistence after washout. In addition, polygamain is able to circumvent two clinically relevant mechanisms of drug resistance, the expression of P-glycoprotein and the βIII isotype of tubulin. Studies with purified tubulin show that polygamain inhibits the rate and extent of purified tubulin assembly and displaces colchicine, indicating a direct interaction of polygamain within the colchicine binding site on tubulin. Polygamain has structural similarities to podophyllotoxin, and molecular modeling simulations were conducted to identify the potential orientations of these compounds within the colchicine binding site. These studies suggest that the benzodioxole group of polygamain occupies space similar to the trimethoxyphenyl group of podophyllotoxin but with distinct interactions within the hydrophobic pocket. Our results identify polygamain as a new microtubule destabilizer that seems to occupy a unique pharmacophore within the colchicine site of tubulin. This new pharmacophore will be used to design new colchicine site compounds that might provide advantages over the current agents.

  12. Substitute sweeteners: diverse bacterial oligosaccharyltransferases with unique N-glycosylation site preferences.

    Science.gov (United States)

    Ollis, Anne A; Chai, Yi; Natarajan, Aravind; Perregaux, Emily; Jaroentomeechai, Thapakorn; Guarino, Cassandra; Smith, Jessica; Zhang, Sheng; DeLisa, Matthew P

    2015-10-20

    The central enzyme in the Campylobacter jejuni asparagine-linked glycosylation pathway is the oligosaccharyltransferase (OST), PglB, which transfers preassembled glycans to specific asparagine residues in target proteins. While C. jejuni PglB (CjPglB) can transfer many diverse glycan structures, the acceptor sites that it recognizes are restricted predominantly to those having a negatively charged residue in the -2 position relative to the asparagine. Here, we investigated the acceptor-site preferences for 23 homologs with natural sequence variation compared to CjPglB. Using an ectopic trans-complementation assay for CjPglB function in glycosylation-competent Escherichia coli, we demonstrated in vivo activity for 16 of the candidate OSTs. Interestingly, the OSTs from Campylobacter coli, Campylobacter upsaliensis, Desulfovibrio desulfuricans, Desulfovibrio gigas, and Desulfovibrio vulgaris, exhibited significantly relaxed specificity towards the -2 position compared to CjPglB. These enzymes glycosylated minimal N-X-T motifs in multiple targets and each followed unique, as yet unknown, rules governing acceptor-site preferences. One notable example is D. gigas PglB, which was the only bacterial OST to glycosylate the Fc domain of human immunoglobulin G at its native 'QYNST' sequon. Overall, we find that a subset of bacterial OSTs follow their own rules for acceptor-site specificity, thereby expanding the glycoengineering toolbox with previously unavailable biocatalytic diversity.

  13. Probabilistic prediction models for aggregate quarry siting

    Science.gov (United States)

    Robinson, G.R.; Larkins, P.M.

    2007-01-01

    Weights-of-evidence (WofE) and logistic regression techniques were used in a GIS framework to predict the spatial likelihood (prospectivity) of crushed-stone aggregate quarry development. The joint conditional probability models, based on geology, transportation network, and population density variables, were defined using quarry location and time of development data for the New England States, North Carolina, and South Carolina, USA. The Quarry Operation models describe the distribution of active aggregate quarries, independent of the date of opening. The New Quarry models describe the distribution of aggregate quarries when they open. Because of the small number of new quarries developed in the study areas during the last decade, independent New Quarry models have low parameter estimate reliability. The performance of parameter estimates derived for Quarry Operation models, defined by a larger number of active quarries in the study areas, were tested and evaluated to predict the spatial likelihood of new quarry development. Population density conditions at the time of new quarry development were used to modify the population density variable in the Quarry Operation models to apply to new quarry development sites. The Quarry Operation parameters derived for the New England study area, Carolina study area, and the combined New England and Carolina study areas were all similar in magnitude and relative strength. The Quarry Operation model parameters, using the modified population density variables, were found to be a good predictor of new quarry locations. Both the aggregate industry and the land management community can use the model approach to target areas for more detailed site evaluation for quarry location. The models can be revised easily to reflect actual or anticipated changes in transportation and population features. ?? International Association for Mathematical Geology 2007.

  14. Predicting N-terminal myristoylation sites in plant proteins

    Directory of Open Access Journals (Sweden)

    Podell Sheila

    2004-06-01

    Full Text Available Abstract Background N-terminal myristoylation plays a vital role in membrane targeting and signal transduction in plant responses to environmental stress. Although N-myristoyltransferase enzymatic function is conserved across plant, animal, and fungal kingdoms, exact substrate specificities vary, making it difficult to predict protein myristoylation accurately within specific taxonomic groups. Results A new method for predicting N-terminal myristoylation sites specifically in plants has been developed and statistically tested for sensitivity, specificity, and robustness. Compared to previously available methods, the new model is both more sensitive in detecting known positives, and more selective in avoiding false positives. Scores of myristoylated and non-myristoylated proteins are more widely separated than with other methods, greatly reducing ambiguity and the number of sequences giving intermediate, uninformative results. The prediction model is available at http://plantsp.sdsc.edu/myrist.html. Conclusion Superior performance of the new model is due to the selection of a plant-specific training set, covering 266 unique sequence examples from 40 different species, the use of a probability-based hidden Markov model to obtain predictive scores, and a threshold cutoff value chosen to provide maximum positive-negative discrimination. The new model has been used to predict 589 plant proteins likely to contain N-terminal myristoylation signals, and to analyze the functional families in which these proteins occur.

  15. Text Mining Improves Prediction of Protein Functional Sites

    Science.gov (United States)

    Cohn, Judith D.; Ravikumar, Komandur E.

    2012-01-01

    We present an approach that integrates protein structure analysis and text mining for protein functional site prediction, called LEAP-FS (Literature Enhanced Automated Prediction of Functional Sites). The structure analysis was carried out using Dynamics Perturbation Analysis (DPA), which predicts functional sites at control points where interactions greatly perturb protein vibrations. The text mining extracts mentions of residues in the literature, and predicts that residues mentioned are functionally important. We assessed the significance of each of these methods by analyzing their performance in finding known functional sites (specifically, small-molecule binding sites and catalytic sites) in about 100,000 publicly available protein structures. The DPA predictions recapitulated many of the functional site annotations and preferentially recovered binding sites annotated as biologically relevant vs. those annotated as potentially spurious. The text-based predictions were also substantially supported by the functional site annotations: compared to other residues, residues mentioned in text were roughly six times more likely to be found in a functional site. The overlap of predictions with annotations improved when the text-based and structure-based methods agreed. Our analysis also yielded new high-quality predictions of many functional site residues that were not catalogued in the curated data sources we inspected. We conclude that both DPA and text mining independently provide valuable high-throughput protein functional site predictions, and that integrating the two methods using LEAP-FS further improves the quality of these predictions. PMID:22393388

  16. Text mining improves prediction of protein functional sites.

    Science.gov (United States)

    Verspoor, Karin M; Cohn, Judith D; Ravikumar, Komandur E; Wall, Michael E

    2012-01-01

    We present an approach that integrates protein structure analysis and text mining for protein functional site prediction, called LEAP-FS (Literature Enhanced Automated Prediction of Functional Sites). The structure analysis was carried out using Dynamics Perturbation Analysis (DPA), which predicts functional sites at control points where interactions greatly perturb protein vibrations. The text mining extracts mentions of residues in the literature, and predicts that residues mentioned are functionally important. We assessed the significance of each of these methods by analyzing their performance in finding known functional sites (specifically, small-molecule binding sites and catalytic sites) in about 100,000 publicly available protein structures. The DPA predictions recapitulated many of the functional site annotations and preferentially recovered binding sites annotated as biologically relevant vs. those annotated as potentially spurious. The text-based predictions were also substantially supported by the functional site annotations: compared to other residues, residues mentioned in text were roughly six times more likely to be found in a functional site. The overlap of predictions with annotations improved when the text-based and structure-based methods agreed. Our analysis also yielded new high-quality predictions of many functional site residues that were not catalogued in the curated data sources we inspected. We conclude that both DPA and text mining independently provide valuable high-throughput protein functional site predictions, and that integrating the two methods using LEAP-FS further improves the quality of these predictions.

  17. Text mining improves prediction of protein functional sites.

    Directory of Open Access Journals (Sweden)

    Karin M Verspoor

    Full Text Available We present an approach that integrates protein structure analysis and text mining for protein functional site prediction, called LEAP-FS (Literature Enhanced Automated Prediction of Functional Sites. The structure analysis was carried out using Dynamics Perturbation Analysis (DPA, which predicts functional sites at control points where interactions greatly perturb protein vibrations. The text mining extracts mentions of residues in the literature, and predicts that residues mentioned are functionally important. We assessed the significance of each of these methods by analyzing their performance in finding known functional sites (specifically, small-molecule binding sites and catalytic sites in about 100,000 publicly available protein structures. The DPA predictions recapitulated many of the functional site annotations and preferentially recovered binding sites annotated as biologically relevant vs. those annotated as potentially spurious. The text-based predictions were also substantially supported by the functional site annotations: compared to other residues, residues mentioned in text were roughly six times more likely to be found in a functional site. The overlap of predictions with annotations improved when the text-based and structure-based methods agreed. Our analysis also yielded new high-quality predictions of many functional site residues that were not catalogued in the curated data sources we inspected. We conclude that both DPA and text mining independently provide valuable high-throughput protein functional site predictions, and that integrating the two methods using LEAP-FS further improves the quality of these predictions.

  18. Lack of a unique termination site for the first round of bacteriophage lambda DNA replication

    Energy Technology Data Exchange (ETDEWEB)

    Valenzuela, M.S. (Brandeis Univ., Waltham, MA); Freifelder, D.; Inman, R.B.

    1976-01-01

    From previous data on the first round of bacteriophage lambdacIIcIII DNA replication (Schnos and Inman, 1970) it is possible to estimate, by extrapolation, the position on circular lambda DNA where bidirectional growing points meet. In the present study we have investigated whether this position occurs at a genetically defined site. To this end, replicative intermediates of lambda mutants containing either deletions to the left of the replication origin, or one deletion plus a duplication to the right, were analyzed in the electron microscope. Our results indicate that (i) leftward growing points can traverse the extrapolated termination point calculated from the lambdacIIcIII data, (ii) no discontinuity of either right or leftward growing fork position is observed, and (iii) the extrapolated termination points for these mutants are well removed from those calculated for lambdacIIcIII DNA. From these data we conclude that there is probably no unique termination site for the first round of lambda DNA replication and that termination occurs simply by collision of the growing forks.

  19. Lymphoid organ-resident dendritic cells exhibit unique transcriptional fingerprints based on subset and site.

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    Kutlu G Elpek

    Full Text Available Lymphoid organ-resident DC subsets are thought to play unique roles in determining the fate of T cell responses. Recent studies focusing on a single lymphoid organ identified molecular pathways that are differentially operative in each DC subset and led to the assumption that a given DC subset would more or less exhibit the same genomic and functional profiles throughout the body. Whether the local milieu in different anatomical sites can also influence the transcriptome of DC subsets has remained largely unexplored. Here, we interrogated the transcriptional relationships between lymphoid organ-resident DC subsets from spleen, gut- and skin-draining lymph nodes, and thymus of C57BL/6 mice. For this purpose, major resident DC subsets including CD4 and CD8 DCs were sorted at high purity and gene expression profiles were compared using microarray analysis. This investigation revealed that lymphoid organ-resident DC subsets exhibit divergent genomic programs across lymphoid organs. Interestingly, we also found that transcriptional and biochemical properties of a given DC subset can differ between lymphoid organs for lymphoid organ-resident DC subsets, but not plasmacytoid DCs, suggesting that determinants of the tissue milieu program resident DCs for essential site-specific functions.

  20. Mixing active-site components: a recipe for the unique enzymatic activity of a telomere resolvase.

    Science.gov (United States)

    Bankhead, Troy; Chaconas, George

    2004-09-21

    The ResT protein, a telomere resolvase from Borrelia burgdorferi, processes replication intermediates into linear replicons with hairpin ends by using a catalytic mechanism similar to that for tyrosine recombinases and type IB topoisomerases. We have identified in ResT a hairpin binding region typically found in cut-and-paste transposases. We show that substitution of residues within this region results in a decreased ability of these mutants to catalyze telomere resolution. However, the mutants are capable of resolving heteroduplex DNA substrates designed to allow spontaneous destabilization and prehairpin formation. These findings support the existence of a hairpin binding region in ResT, the only known occurrence outside a transposase. The combination of transposase-like and tyrosine-recombinase-like domains found in ResT indicates the use of a composite active site and helps explain the unique breakage-and-reunion reaction observed with this protein. Comparison of the ResT sequence with other known telomere resolvases suggests that a hairpin binding motif is a common feature in this class of enzyme; the sequence motif also appears in the RAG recombinases. Finally, our data support a mechanism of action whereby ResT induces prehairpin formation before the DNA cleavage step.

  1. Assessment of the Uniqueness of Wind Tunnel Strain-Gage Balance Load Predictions

    Science.gov (United States)

    Ulbrich, N.

    2016-01-01

    A new test was developed to assess the uniqueness of wind tunnel strain-gage balance load predictions that are obtained from regression models of calibration data. The test helps balance users to gain confidence in load predictions of non-traditional balance designs. It also makes it possible to better evaluate load predictions of traditional balances that are not used as originally intended. The test works for both the Iterative and Non-Iterative Methods that are used in the aerospace testing community for the prediction of balance loads. It is based on the hypothesis that the total number of independently applied balance load components must always match the total number of independently measured bridge outputs or bridge output combinations. This hypothesis is supported by a control volume analysis of the inputs and outputs of a strain-gage balance. It is concluded from the control volume analysis that the loads and bridge outputs of a balance calibration data set must separately be tested for linear independence because it cannot always be guaranteed that a linearly independent load component set will result in linearly independent bridge output measurements. Simple linear math models for the loads and bridge outputs in combination with the variance inflation factor are used to test for linear independence. A highly unique and reversible mapping between the applied load component set and the measured bridge output set is guaranteed to exist if the maximum variance inflation factor of both sets is less than the literature recommended threshold of five. Data from the calibration of a six{component force balance is used to illustrate the application of the new test to real-world data.

  2. Predicting active site residue annotations in the Pfam database

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    Finn Robert D

    2007-08-01

    Full Text Available Abstract Background Approximately 5% of Pfam families are enzymatic, but only a small fraction of the sequences within these families ( Description We have created a large database of predicted active site residues. On comparing our active site predictions to those found in UniProtKB, Catalytic Site Atlas, PROSITE and MEROPS we find that we make many novel predictions. On investigating the small subset of predictions made by these databases that are not predicted by us, we found these sequences did not meet our strict criteria for prediction. We assessed the sensitivity and specificity of our methodology and estimate that only 3% of our predicted sequences are false positives. Conclusion We have predicted 606110 active site residues, of which 94% are not found in UniProtKB, and have increased the active site annotations in Pfam by more than 200 fold. Although implemented for Pfam, the tool we have developed for transferring the data can be applied to any alignment with associated experimental active site data and is available for download. Our active site predictions are re-calculated at each Pfam release to ensure they are comprehensive and up to date. They provide one of the largest available databases of active site annotation.

  3. Identification of a uniquely immunodominant, cross-reacting site in the human immunodeficiency virus endonuclease protein.

    Science.gov (United States)

    Björling, E; Utter, G; Stålhandske, P; Norrby, E; Chiodi, F

    1991-01-01

    One of the features of the life cycle of retroviruses is insertion of the proviral DNA into host chromosomes. A protein encoded by the 3' end of the pol gene of the virus genome has been shown to possess endonuclease activity (D. P. Grandgenett, A. C. Vora, and R. D. Schiff, Virology 89:119-132, 1978), which is necessary for DNA integration. Sera from the majority of human immunodeficiency virus (HIV)-infected individuals react with endonuclease protein p31 in serological tests (J. S. Allan, J. E. Coligan, T.-H. Lee, F. Barin, P. J. Kanki, S. M'Boup, M. F. McLane, J. E. Groopman, and M. Essex, Blood 69:331-333, 1987; E. F. Lillehoj, F. H. R. Salazar, R. J. Mervis, M. G. Raum, H. W. Chan, N. Ahmad, and S. Venkatesan, J. Virol. 62:3053-3058, 1988; K. S. Steimer, K. W. Higgins, M. A. Powers, J. C. Stephans, A. Gyenes, G. George-Nascimento, P. A. Liciw, P. J. Barr, R. A. Hallewell, and R. Sanchez-Pescador, J. Virol. 58:9-16, 1986). It is not known, however, which part of the protein represents the target(s) for antibody response. To study this, we synthesized peptides and used them in an enzyme-linked immunosorbent assay system to map the reactivity of human immunodeficiency virus type 1 (HIV-1) antibody-positive sera to the different regions of the HIV endonuclease. A uniquely antigenic, HIV-1- and HIV-2-cross-reacting site was identified in the central part of this protein from Phe-663 to Trp-670. PMID:2072463

  4. Prediction of Solar Flares Using Unique Signatures of Magnetic Field Images

    Science.gov (United States)

    Raboonik, Abbas; Safari, Hossein; Alipour, Nasibe; Wheatland, Michael S.

    2017-01-01

    Prediction of solar flares is an important task in solar physics. The occurrence of solar flares is highly dependent on the structure and topology of solar magnetic fields. A new method for predicting large (M- and X-class) flares is presented, which uses machine learning methods applied to the Zernike moments (ZM) of magnetograms observed by the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory for a period of six years from 2010 June 2 to 2016 August 1. Magnetic field images consisting of the radial component of the magnetic field are converted to finite sets of ZMs and fed to the support vector machine classifier. ZMs have the capability to elicit unique features from any 2D image, which may allow more accurate classification. The results indicate whether an arbitrary active region has the potential to produce at least one large flare. We show that the majority of large flares can be predicted within 48 hr before their occurrence, with only 10 false negatives out of 385 flaring active region magnetograms and 21 false positives out of 179 non-flaring active region magnetograms. Our method may provide a useful tool for the prediction of solar flares, which can be employed alongside other forecasting methods.

  5. Prediction of Solar Flares Using Unique Signatures of Magnetic Field Images

    CERN Document Server

    Raboonik, Abbas; Alipour, Nasibe; Wheatland, Michael S

    2016-01-01

    Prediction of solar flares is an important task in solar physics. The occurrence of solar flares is highly dependent on the structure and the topology of solar magnetic fields. A new method for predicting large (M and X class) flares is presented, which uses machine learning methods applied to the Zernike moments of magnetograms observed by the Helioseismic and Magnetic Imager (HMI) onboard the Solar Dynamics Observatory (SDO) for a period of six years from 2 June 2010 to 1 August 2016. Magnetic field images consisting of the radial component of the magnetic field are converted to finite sets of Zernike moments and fed to the Support Vector Machine (SVM) classifier. Zernike moments have the capability to elicit unique features from any 2-D image, which may allow more accurate classification. The results indicate whether an arbitrary active region has the potential to produce at least one large flare. We show that the majority of large flares can be predicted within 48 hours before their occurrence, with only ...

  6. Positive-Unlabeled Learning for Pupylation Sites Prediction

    Directory of Open Access Journals (Sweden)

    Ming Jiang

    2016-01-01

    Full Text Available Pupylation plays a key role in regulating various protein functions as a crucial posttranslational modification of prokaryotes. In order to understand the molecular mechanism of pupylation, it is important to identify pupylation substrates and sites accurately. Several computational methods have been developed to identify pupylation sites because the traditional experimental methods are time-consuming and labor-sensitive. With the existing computational methods, the experimentally annotated pupylation sites are used as the positive training set and the remaining nonannotated lysine residues as the negative training set to build classifiers to predict new pupylation sites from the unknown proteins. However, the remaining nonannotated lysine residues may contain pupylation sites which have not been experimentally validated yet. Unlike previous methods, in this study, the experimentally annotated pupylation sites were used as the positive training set whereas the remaining nonannotated lysine residues were used as the unlabeled training set. A novel method named PUL-PUP was proposed to predict pupylation sites by using positive-unlabeled learning technique. Our experimental results indicated that PUL-PUP outperforms the other methods significantly for the prediction of pupylation sites. As an application, PUL-PUP was also used to predict the most likely pupylation sites in nonannotated lysine sites.

  7. Unique associations among emotion dysregulation dimensions and aggressive tendencies : A multi-site study.

    NARCIS (Netherlands)

    Velotti, Patrizia; Casselman, Robert B.; Garofalo, C.; McKenzie, Melissa D.

    2017-01-01

    While problems with emotion regulation (ER) have long been associated with internalizing symptoms, only recently has an ER framework been applied to the study of aggression. Therefore, little is known about the unique and independent associations between specific domains of the ER construct and diff

  8. A grammar inference approach for predicting kinase specific phosphorylation sites.

    Science.gov (United States)

    Datta, Sutapa; Mukhopadhyay, Subhasis

    2015-01-01

    Kinase mediated phosphorylation site detection is the key mechanism of post translational mechanism that plays an important role in regulating various cellular processes and phenotypes. Many diseases, like cancer are related with the signaling defects which are associated with protein phosphorylation. Characterizing the protein kinases and their substrates enhances our ability to understand the mechanism of protein phosphorylation and extends our knowledge of signaling network; thereby helping us to treat such diseases. Experimental methods for predicting phosphorylation sites are labour intensive and expensive. Also, manifold increase of protein sequences in the databanks over the years necessitates the improvement of high speed and accurate computational methods for predicting phosphorylation sites in protein sequences. Till date, a number of computational methods have been proposed by various researchers in predicting phosphorylation sites, but there remains much scope of improvement. In this communication, we present a simple and novel method based on Grammatical Inference (GI) approach to automate the prediction of kinase specific phosphorylation sites. In this regard, we have used a popular GI algorithm Alergia to infer Deterministic Stochastic Finite State Automata (DSFA) which equally represents the regular grammar corresponding to the phosphorylation sites. Extensive experiments on several datasets generated by us reveal that, our inferred grammar successfully predicts phosphorylation sites in a kinase specific manner. It performs significantly better when compared with the other existing phosphorylation site prediction methods. We have also compared our inferred DSFA with two other GI inference algorithms. The DSFA generated by our method performs superior which indicates that our method is robust and has a potential for predicting the phosphorylation sites in a kinase specific manner.

  9. Field Measurement-Based System Identification and Dynamic Response Prediction of a Unique MIT Building.

    Science.gov (United States)

    Cha, Young-Jin; Trocha, Peter; Büyüköztürk, Oral

    2016-07-01

    Tall buildings are ubiquitous in major cities and house the homes and workplaces of many individuals. However, relatively few studies have been carried out to study the dynamic characteristics of tall buildings based on field measurements. In this paper, the dynamic behavior of the Green Building, a unique 21-story tall structure located on the campus of the Massachusetts Institute of Technology (MIT, Cambridge, MA, USA), was characterized and modeled as a simplified lumped-mass beam model (SLMM), using data from a network of accelerometers. The accelerometer network was used to record structural responses due to ambient vibrations, blast loading, and the October 16th 2012 earthquake near Hollis Center (ME, USA). Spectral and signal coherence analysis of the collected data was used to identify natural frequencies, modes, foundation rocking behavior, and structural asymmetries. A relation between foundation rocking and structural natural frequencies was also found. Natural frequencies and structural acceleration from the field measurements were compared with those predicted by the SLMM which was updated by inverse solving based on advanced multiobjective optimization methods using the measured structural responses and found to have good agreement.

  10. Predicting internalizing problems in Chinese children: the unique and interactive effects of parenting and child temperament.

    Science.gov (United States)

    Muhtadie, Luma; Zhou, Qing; Eisenberg, Nancy; Wang, Yun

    2013-08-01

    The additive and interactive relations of parenting styles (authoritative and authoritarian parenting) and child temperament (anger/frustration, sadness, and effortful control) to children's internalizing problems were examined in a 3.8-year longitudinal study of 425 Chinese children (aged 6-9 years) from Beijing. At Wave 1, parents self-reported on their parenting styles, and parents and teachers rated child temperament. At Wave 2, parents, teachers, and children rated children's internalizing problems. Structural equation modeling indicated that the main effect of authoritative parenting and the interactions of Authoritarian Parenting × Effortful Control and Authoritative Parenting × Anger/Frustration (parents' reports only) prospectively and uniquely predicted internalizing problems. The above results did not vary by child sex and remained significant after controlling for co-occurring externalizing problems. These findings suggest that (a) children with low effortful control may be particularly susceptible to the adverse effect of authoritarian parenting and (b) the benefit of authoritative parenting may be especially important for children with high anger/frustration.

  11. Field Measurement-Based System Identification and Dynamic Response Prediction of a Unique MIT Building

    Directory of Open Access Journals (Sweden)

    Young-Jin Cha

    2016-07-01

    Full Text Available Tall buildings are ubiquitous in major cities and house the homes and workplaces of many individuals. However, relatively few studies have been carried out to study the dynamic characteristics of tall buildings based on field measurements. In this paper, the dynamic behavior of the Green Building, a unique 21-story tall structure located on the campus of the Massachusetts Institute of Technology (MIT, Cambridge, MA, USA, was characterized and modeled as a simplified lumped-mass beam model (SLMM, using data from a network of accelerometers. The accelerometer network was used to record structural responses due to ambient vibrations, blast loading, and the October 16th 2012 earthquake near Hollis Center (ME, USA. Spectral and signal coherence analysis of the collected data was used to identify natural frequencies, modes, foundation rocking behavior, and structural asymmetries. A relation between foundation rocking and structural natural frequencies was also found. Natural frequencies and structural acceleration from the field measurements were compared with those predicted by the SLMM which was updated by inverse solving based on advanced multiobjective optimization methods using the measured structural responses and found to have good agreement.

  12. Flood Predictions Combining Regional and Single Site Hydrometric Information

    Directory of Open Access Journals (Sweden)

    Campos–Aranda

    2010-07-01

    Full Text Available Initially, the statistic benefit of flood predictions obtained by combining reliable regional and scarce site hydrometric data is pointed out. Then the mathematical equations for combining mean and standard deviation logarithms of regional and site data are exposed, as well as the necessary expressions for desired predictions, based on Student's t distribution. Later two numerical applications are described, the first one based in Carrizal hydrometric station located in Santiago River in Nayarit and the second one which makes use of five water gauging stations in Tempoal River in Veracruz. Finally, a conclusion is formulated pointing out the simplicity of that method and the accuracy of its predictions.

  13. Antibody Treatment of Ebola and Sudan Virus Infection via a Uniquely Exposed Epitope within the Glycoprotein Receptor Binding Site

    Science.gov (United States)

    2016-06-14

    1 Antibody treatment of Ebola and Sudan virus infection via a uniquely exposed epitope within the glycoprotein receptor-binding site Katie A...interaction with the endosomal receptor NPC-1, cross neutralizes Ebola (EBOV), Sudan (SUDV), and Bundibugyo viruses, and protects mice and guinea pigs...Filoviridae include two marburgviruses: Marburg virus (MARV) and Ravn virus (RAVV), and five ebolaviruses: Ebola virus (EBOV), Sudan virus (SUDV

  14. Variable context Markov chains for HIV protease cleavage site prediction.

    Science.gov (United States)

    Oğul, Hasan

    2009-06-01

    Deciphering the knowledge of HIV protease specificity and developing computational tools for detecting its cleavage sites in protein polypeptide chain are very desirable for designing efficient and specific chemical inhibitors to prevent acquired immunodeficiency syndrome. In this study, we developed a generative model based on a generalization of variable order Markov chains (VOMC) for peptide sequences and adapted the model for prediction of their cleavability by certain proteases. The new method, called variable context Markov chains (VCMC), attempts to identify the context equivalence based on the evolutionary similarities between individual amino acids. It was applied for HIV-1 protease cleavage site prediction problem and shown to outperform existing methods in terms of prediction accuracy on a common dataset. In general, the method is a promising tool for prediction of cleavage sites of all proteases and encouraged to be used for any kind of peptide classification problem as well.

  15. Selective prediction of interaction sites in protein structures with THEMATICS

    Directory of Open Access Journals (Sweden)

    Murga Leonel F

    2007-04-01

    Full Text Available Abstract Background Methods are now available for the prediction of interaction sites in protein 3D structures. While many of these methods report high success rates for site prediction, often these predictions are not very selective and have low precision. Precision in site prediction is addressed using Theoretical Microscopic Titration Curves (THEMATICS, a simple computational method for the identification of active sites in enzymes. Recall and precision are measured and compared with other methods for the prediction of catalytic sites. Results Using a test set of 169 enzymes from the original Catalytic Residue Dataset (CatRes it is shown that THEMATICS can deliver precise, localised site predictions. Furthermore, adjustment of the cut-off criteria can improve the recall rates for catalytic residues with only a small sacrifice in precision. Recall rates for CatRes/CSA annotated catalytic residues are 41.1%, 50.4%, and 54.2% for Z score cut-off values of 1.00, 0.99, and 0.98, respectively. The corresponding precision rates are 19.4%, 17.9%, and 16.4%. The success rate for catalytic sites is higher, with correct or partially correct predictions for 77.5%, 85.8%, and 88.2% of the enzymes in the test set, corresponding to the same respective Z score cut-offs, if only the CatRes annotations are used as the reference set. Incorporation of additional literature annotations into the reference set gives total success rates of 89.9%, 92.9%, and 94.1%, again for corresponding cut-off values of 1.00, 0.99, and 0.98. False positive rates for a 75-protein test set are 1.95%, 2.60%, and 3.12% for Z score cut-offs of 1.00, 0.99, and 0.98, respectively. Conclusion With a preferred cut-off value of 0.99, THEMATICS achieves a high success rate of interaction site prediction, about 86% correct or partially correct using CatRes/CSA annotations only and about 93% with an expanded reference set. Success rates for catalytic residue prediction are similar to those of

  16. A systems biology approach to transcription factor binding site prediction.

    Directory of Open Access Journals (Sweden)

    Xiang Zhou

    Full Text Available BACKGROUND: The elucidation of mammalian transcriptional regulatory networks holds great promise for both basic and translational research and remains one the greatest challenges to systems biology. Recent reverse engineering methods deduce regulatory interactions from large-scale mRNA expression profiles and cross-species conserved regulatory regions in DNA. Technical challenges faced by these methods include distinguishing between direct and indirect interactions, associating transcription regulators with predicted transcription factor binding sites (TFBSs, identifying non-linearly conserved binding sites across species, and providing realistic accuracy estimates. METHODOLOGY/PRINCIPAL FINDINGS: We address these challenges by closely integrating proven methods for regulatory network reverse engineering from mRNA expression data, linearly and non-linearly conserved regulatory region discovery, and TFBS evaluation and discovery. Using an extensive test set of high-likelihood interactions, which we collected in order to provide realistic prediction-accuracy estimates, we show that a careful integration of these methods leads to significant improvements in prediction accuracy. To verify our methods, we biochemically validated TFBS predictions made for both transcription factors (TFs and co-factors; we validated binding site predictions made using a known E2F1 DNA-binding motif on E2F1 predicted promoter targets, known E2F1 and JUND motifs on JUND predicted promoter targets, and a de novo discovered motif for BCL6 on BCL6 predicted promoter targets. Finally, to demonstrate accuracy of prediction using an external dataset, we showed that sites matching predicted motifs for ZNF263 are significantly enriched in recent ZNF263 ChIP-seq data. CONCLUSIONS/SIGNIFICANCE: Using an integrative framework, we were able to address technical challenges faced by state of the art network reverse engineering methods, leading to significant improvement in direct

  17. Predicting web site audience demographics for web advertising targeting using multi-web site clickstream data

    OpenAIRE

    Bock, K W; D. VAN DEN POEL; Manigart, S.

    2009-01-01

    Several recent studies have explored the virtues of behavioral targeting and personalization for online advertising. In this paper, we add to this literature by proposing a cost-effective methodology for the prediction of demographic web site visitor profiles that can be used for web advertising targeting purposes. The methodology involves the transformation of web site visitors’ clickstream patterns to a set of features and the training of Random Forest classifiers that generate predictions ...

  18. Novel therapeutic approaches for pulmonary arterial hypertension: Unique molecular targets to site-specific drug delivery.

    Science.gov (United States)

    Vaidya, Bhuvaneshwar; Gupta, Vivek

    2015-08-10

    Pulmonary arterial hypertension (PAH) is a cardiopulmonary disorder characterized by increased blood pressure in the small arterioles supplying blood to lungs for oxygenation. Advances in understanding of molecular and cellular biology techniques have led to the findings that PAH is indeed a cascade of diseases exploiting multi-faceted complex pathophysiology, with cellular proliferation and vascular remodeling being the key pathogenic events along with several cellular pathways involved. While current therapies for PAH do provide for amelioration of disease symptoms and acute survival benefits, their full therapeutic potential is hindered by patient incompliance and off-target side effects. To overcome the issues related with current therapy and to devise a more selective therapy, various novel pathways are being investigated for PAH treatment. In addition, inability to deliver anti-PAH drugs to the disease site i.e., distal pulmonary arterioles has been one of the major challenges in achieving improved patient outcomes and improved therapeutic efficacy. Several novel carriers have been explored to increase the selectivity of currently approved anti-PAH drugs and to act as suitable carriers for the delivery of investigational drugs. In the present review, we have discussed potential of various novel molecular pathways/targets including RhoA/Rho kinase, tyrosine kinase, endothelial progenitor cells, vasoactive intestinal peptide, and miRNA in PAH therapeutics. We have also discussed various techniques for site-specific drug delivery of anti-PAH therapeutics so as to improve the efficacy of approved and investigational drugs. This review will provide gainful insights into current advances in PAH therapeutics with an emphasis on site-specific drug payload delivery.

  19. Genome-wide prediction, display and refinement of binding sites with information theory-based models

    Directory of Open Access Journals (Sweden)

    Leeder J Steven

    2003-09-01

    Full Text Available Abstract Background We present Delila-genome, a software system for identification, visualization and analysis of protein binding sites in complete genome sequences. Binding sites are predicted by scanning genomic sequences with information theory-based (or user-defined weight matrices. Matrices are refined by adding experimentally-defined binding sites to published binding sites. Delila-Genome was used to examine the accuracy of individual information contents of binding sites detected with refined matrices as a measure of the strengths of the corresponding protein-nucleic acid interactions. The software can then be used to predict novel sites by rescanning the genome with the refined matrices. Results Parameters for genome scans are entered using a Java-based GUI interface and backend scripts in Perl. Multi-processor CPU load-sharing minimized the average response time for scans of different chromosomes. Scans of human genome assemblies required 4–6 hours for transcription factor binding sites and 10–19 hours for splice sites, respectively, on 24- and 3-node Mosix and Beowulf clusters. Individual binding sites are displayed either as high-resolution sequence walkers or in low-resolution custom tracks in the UCSC genome browser. For large datasets, we applied a data reduction strategy that limited displays of binding sites exceeding a threshold information content to specific chromosomal regions within or adjacent to genes. An HTML document is produced listing binding sites ranked by binding site strength or chromosomal location hyperlinked to the UCSC custom track, other annotation databases and binding site sequences. Post-genome scan tools parse binding site annotations of selected chromosome intervals and compare the results of genome scans using different weight matrices. Comparisons of multiple genome scans can display binding sites that are unique to each scan and identify sites with significantly altered binding strengths

  20. Expert System for Minefield Site Prediction. Phase 1.

    Science.gov (United States)

    1988-02-01

    2.2111- .25 Jlill 1 MICROCOPY RESOLUTION TLST CHART % %R( % % % % % ko , %% % - Af-A -:A.ZA .A r. ETL-0492 Expert system for minefield site...1. TITLE (Include Security Gassfication) EXPERT SYSTEM FOR MINEFIELD SITE PREDICTION FIRST YEAR REPORT r.. Z. PERSONAL AUTHOR(S) Dillencourt, Michael...identify by block number)FIELD GROUP L SUB-GROUP I Expert System ’ LMinefield,8ite ,rediction - * Quadtree,CTeraiin--nalysis,.t 19, ABSTRACT (Continue on

  1. Fast dynamics perturbation analysis for prediction of protein functional sites

    Directory of Open Access Journals (Sweden)

    Cohn Judith D

    2008-01-01

    Full Text Available Abstract Background We present a fast version of the dynamics perturbation analysis (DPA algorithm to predict functional sites in protein structures. The original DPA algorithm finds regions in proteins where interactions cause a large change in the protein conformational distribution, as measured using the relative entropy Dx. Such regions are associated with functional sites. Results The Fast DPA algorithm, which accelerates DPA calculations, is motivated by an empirical observation that Dx in a normal-modes model is highly correlated with an entropic term that only depends on the eigenvalues of the normal modes. The eigenvalues are accurately estimated using first-order perturbation theory, resulting in a N-fold reduction in the overall computational requirements of the algorithm, where N is the number of residues in the protein. The performance of the original and Fast DPA algorithms was compared using protein structures from a standard small-molecule docking test set. For nominal implementations of each algorithm, top-ranked Fast DPA predictions overlapped the true binding site 94% of the time, compared to 87% of the time for original DPA. In addition, per-protein recall statistics (fraction of binding-site residues that are among predicted residues were slightly better for Fast DPA. On the other hand, per-protein precision statistics (fraction of predicted residues that are among binding-site residues were slightly better using original DPA. Overall, the performance of Fast DPA in predicting ligand-binding-site residues was comparable to that of the original DPA algorithm. Conclusion Compared to the original DPA algorithm, the decreased run time with comparable performance makes Fast DPA well-suited for implementation on a web server and for high-throughput analysis.

  2. A GIS approach for predicting prehistoric site locations.

    Energy Technology Data Exchange (ETDEWEB)

    Kuiper, J. A.; Wescott, K. L.

    1999-08-04

    Use of geographic information system (GIS)-based predictive mapping to locate areas of high potential for prehistoric archaeological sites is becoming increasingly popular among archaeologists. Knowledge of the environmental variables influencing activities of original inhabitants is used to produce GIS layers representing the spatial distribution of those variables. The GIS layers are then analyzed to identify locations where combinations of environmental variables match patterns observed at known prehistoric sites. Presented are the results of a study to locate high-potential areas for prehistoric sites in a largely unsurveyed area of 39,000 acres in the Upper Chesapeake Bay region, including details of the analysis process. The project used environmental data from over 500 known sites in other parts of the region and the results corresponded well with known sites in the study area.

  3. Direct and indirect measures of spider fear predict unique variance in children’s fear-related behaviour

    NARCIS (Netherlands)

    Klein, A.M.; Becker, Eni; Rinck, M.

    2011-01-01

    This study investigated whether direct and indirect measures predict unique variance components of fearful behaviour in children. One hundred eighty-nine children aged between 9 and 12 performed a pictorial version of the emotional Stroop task (EST), filled out the Spider Anxiety and Disgust Screeni

  4. Sequence- and structure-based prediction of eukaryotic proteinphosphorylation sites

    DEFF Research Database (Denmark)

    Blom, Nikolaj; Gammeltoft, Steen; Brunak, Søren

    1999-01-01

    in independent sequences with a sensitivity in the range from69 % to 96 %. As an example, we predict novel phosphorylation sites in the p300/CBP protein that may regulateinteraction with transcription factors and histone acetyltransferase activity. In addition, serine and threonine residues inp300/CBP that can...

  5. Functional and catalytic active sites prediction and docking analysis ...

    African Journals Online (AJOL)

    Bioinformatics

    2015-07-01

    Jul 1, 2015 ... industrially important azo dyes such as the molecular weight, molecular ... et al., 2010). The software possesses structure-based method to predict active sites in proteins based on a Difference of Gaussian (DoG) approach ...

  6. Comprehensive prediction of chromosome dimer resolution sites in bacterial genomes

    Directory of Open Access Journals (Sweden)

    Arakawa Kazuharu

    2011-01-01

    Full Text Available Abstract Background During the replication process of bacteria with circular chromosomes, an odd number of homologous recombination events results in concatenated dimer chromosomes that cannot be partitioned into daughter cells. However, many bacteria harbor a conserved dimer resolution machinery consisting of one or two tyrosine recombinases, XerC and XerD, and their 28-bp target site, dif. Results To study the evolution of the dif/XerCD system and its relationship with replication termination, we report the comprehensive prediction of dif sequences in silico using a phylogenetic prediction approach based on iterated hidden Markov modeling. Using this method, dif sites were identified in 641 organisms among 16 phyla, with a 97.64% identification rate for single-chromosome strains. The dif sequence positions were shown to be strongly correlated with the GC skew shift-point that is induced by replicational mutation/selection pressures, but the difference in the positions of the predicted dif sites and the GC skew shift-points did not correlate with the degree of replicational mutation/selection pressures. Conclusions The sequence of dif sites is widely conserved among many bacterial phyla, and they can be computationally identified using our method. The lack of correlation between dif position and the degree of GC skew suggests that replication termination does not occur strictly at dif sites.

  7. Exploiting protein flexibility to predict the location of allosteric sites

    Directory of Open Access Journals (Sweden)

    Panjkovich Alejandro

    2012-10-01

    Full Text Available Abstract Background Allostery is one of the most powerful and common ways of regulation of protein activity. However, for most allosteric proteins identified to date the mechanistic details of allosteric modulation are not yet well understood. Uncovering common mechanistic patterns underlying allostery would allow not only a better academic understanding of the phenomena, but it would also streamline the design of novel therapeutic solutions. This relatively unexplored therapeutic potential and the putative advantages of allosteric drugs over classical active-site inhibitors fuel the attention allosteric-drug research is receiving at present. A first step to harness the regulatory potential and versatility of allosteric sites, in the context of drug-discovery and design, would be to detect or predict their presence and location. In this article, we describe a simple computational approach, based on the effect allosteric ligands exert on protein flexibility upon binding, to predict the existence and position of allosteric sites on a given protein structure. Results By querying the literature and a recently available database of allosteric sites, we gathered 213 allosteric proteins with structural information that we further filtered into a non-redundant set of 91 proteins. We performed normal-mode analysis and observed significant changes in protein flexibility upon allosteric-ligand binding in 70% of the cases. These results agree with the current view that allosteric mechanisms are in many cases governed by changes in protein dynamics caused by ligand binding. Furthermore, we implemented an approach that achieves 65% positive predictive value in identifying allosteric sites within the set of predicted cavities of a protein (stricter parameters set, 0.22 sensitivity, by combining the current analysis on dynamics with previous results on structural conservation of allosteric sites. We also analyzed four biological examples in detail, revealing

  8. Cognitive Prediction of Reading, Math, and Attention: Shared and Unique Influences

    Science.gov (United States)

    Peterson, Robin L.; Boada, Richard; McGrath, Lauren M.; Willcutt, Erik G.; Olson, Richard K.; Pennington, Bruce F.

    2017-01-01

    The current study tested a multiple-cognitive predictor model of word reading, math ability, and attention in a community-based sample of twins ages 8 to 16 years (N = 636). The objective was to identify cognitive predictors unique to each skill domain as well as cognitive predictors shared among skills that could help explain their overlap and…

  9. Polyadenylation site prediction using PolyA-iEP method.

    Science.gov (United States)

    Kavakiotis, Ioannis; Tzanis, George; Vlahavas, Ioannis

    2014-01-01

    This chapter presents a method called PolyA-iEP that has been developed for the prediction of polyadenylation sites. More precisely, PolyA-iEP is a method that recognizes mRNA 3'ends which contain polyadenylation sites. It is a modular system which consists of two main components. The first exploits the advantages of emerging patterns and the second is a distance-based scoring method. The outputs of the two components are finally combined by a classifier. The final results reach very high scores of sensitivity and specificity.

  10. Computational Prediction of RNA-Binding Proteins and Binding Sites

    Directory of Open Access Journals (Sweden)

    Jingna Si

    2015-11-01

    Full Text Available Proteins and RNA interaction have vital roles in many cellular processes such as protein synthesis, sequence encoding, RNA transfer, and gene regulation at the transcriptional and post-transcriptional levels. Approximately 6%–8% of all proteins are RNA-binding proteins (RBPs. Distinguishing these RBPs or their binding residues is a major aim of structural biology. Previously, a number of experimental methods were developed for the determination of protein–RNA interactions. However, these experimental methods are expensive, time-consuming, and labor-intensive. Alternatively, researchers have developed many computational approaches to predict RBPs and protein–RNA binding sites, by combining various machine learning methods and abundant sequence and/or structural features. There are three kinds of computational approaches, which are prediction from protein sequence, prediction from protein structure, and protein-RNA docking. In this paper, we review all existing studies of predictions of RNA-binding sites and RBPs and complexes, including data sets used in different approaches, sequence and structural features used in several predictors, prediction method classifications, performance comparisons, evaluation methods, and future directions.

  11. Computational Prediction of RNA-Binding Proteins and Binding Sites.

    Science.gov (United States)

    Si, Jingna; Cui, Jing; Cheng, Jin; Wu, Rongling

    2015-01-01

    Proteins and RNA interaction have vital roles in many cellular processes such as protein synthesis, sequence encoding, RNA transfer, and gene regulation at the transcriptional and post-transcriptional levels. Approximately 6%-8% of all proteins are RNA-binding proteins (RBPs). Distinguishing these RBPs or their binding residues is a major aim of structural biology. Previously, a number of experimental methods were developed for the determination of protein-RNA interactions. However, these experimental methods are expensive, time-consuming, and labor-intensive. Alternatively, researchers have developed many computational approaches to predict RBPs and protein-RNA binding sites, by combining various machine learning methods and abundant sequence and/or structural features. There are three kinds of computational approaches, which are prediction from protein sequence, prediction from protein structure, and protein-RNA docking. In this paper, we review all existing studies of predictions of RNA-binding sites and RBPs and complexes, including data sets used in different approaches, sequence and structural features used in several predictors, prediction method classifications, performance comparisons, evaluation methods, and future directions.

  12. HMMpTM: improving transmembrane protein topology prediction using phosphorylation and glycosylation site prediction.

    Science.gov (United States)

    Tsaousis, Georgios N; Bagos, Pantelis G; Hamodrakas, Stavros J

    2014-02-01

    During the last two decades a large number of computational methods have been developed for predicting transmembrane protein topology. Current predictors rely on topogenic signals in the protein sequence, such as the distribution of positively charged residues in extra-membrane loops and the existence of N-terminal signals. However, phosphorylation and glycosylation are post-translational modifications (PTMs) that occur in a compartment-specific manner and therefore the presence of a phosphorylation or glycosylation site in a transmembrane protein provides topological information. We examine the combination of phosphorylation and glycosylation site prediction with transmembrane protein topology prediction. We report the development of a Hidden Markov Model based method, capable of predicting the topology of transmembrane proteins and the existence of kinase specific phosphorylation and N/O-linked glycosylation sites along the protein sequence. Our method integrates a novel feature in transmembrane protein topology prediction, which results in improved performance for topology prediction and reliable prediction of phosphorylation and glycosylation sites. The method is freely available at http://bioinformatics.biol.uoa.gr/HMMpTM.

  13. Predicting sulfotyrosine sites using the random forest algorithm with significantly improved prediction accuracy

    Directory of Open Access Journals (Sweden)

    Yang Zheng

    2009-10-01

    Full Text Available Abstract Background Tyrosine sulfation is one of the most important posttranslational modifications. Due to its relevance to various disease developments, tyrosine sulfation has become the target for drug design. In order to facilitate efficient drug design, accurate prediction of sulfotyrosine sites is desirable. A predictor published seven years ago has been very successful with claimed prediction accuracy of 98%. However, it has a particularly low sensitivity when predicting sulfotyrosine sites in some newly sequenced proteins. Results A new approach has been developed for predicting sulfotyrosine sites using the random forest algorithm after a careful evaluation of seven machine learning algorithms. Peptides are formed by consecutive residues symmetrically flanking tyrosine sites. They are then encoded using an amino acid hydrophobicity scale. This new approach has increased the sensitivity by 22%, the specificity by 3%, and the total prediction accuracy by 10% compared with the previous predictor using the same blind data. Meanwhile, both negative and positive predictive powers have been increased by 9%. In addition, the random forest model has an excellent feature for ranking the residues flanking tyrosine sites, hence providing more information for further investigating the tyrosine sulfation mechanism. A web tool has been implemented at http://ecsb.ex.ac.uk/sulfotyrosine for public use. Conclusion The random forest algorithm is able to deliver a better model compared with the Hidden Markov Model, the support vector machine, artificial neural networks, and others for predicting sulfotyrosine sites. The success shows that the random forest algorithm together with an amino acid hydrophobicity scale encoding can be a good candidate for peptide classification.

  14. Gene and translation initiation site prediction in metagenomic sequences

    Energy Technology Data Exchange (ETDEWEB)

    Hyatt, Philip Douglas [ORNL; LoCascio, Philip F [ORNL; Hauser, Loren John [ORNL; Uberbacher, Edward C [ORNL

    2012-01-01

    Gene prediction in metagenomic sequences remains a difficult problem. Current sequencing technologies do not achieve sufficient coverage to assemble the individual genomes in a typical sample; consequently, sequencing runs produce a large number of short sequences whose exact origin is unknown. Since these sequences are usually smaller than the average length of a gene, algorithms must make predictions based on very little data. We present MetaProdigal, a metagenomic version of the gene prediction program Prodigal, that can identify genes in short, anonymous coding sequences with a high degree of accuracy. The novel value of the method consists of enhanced translation initiation site identification, ability to identify sequences that use alternate genetic codes and confidence values for each gene call. We compare the results of MetaProdigal with other methods and conclude with a discussion of future improvements.

  15. Unique Prediction for High-Energy J/\\psi Photoproduction: Color Transparency and Saturation

    CERN Document Server

    Schildknecht, Dieter

    2016-01-01

    Based on the color-dipole picture, we present a successful parameter-free prediction for the recent high-energy $J/\\psi$ photoproduction data from the Large Hadron Collider. The experimental data provide empirical evidence for the transition from color transparency to saturation.

  16. Unique Contributions of Maternal Reading Proficiency to Predicting Children's Preschool Receptive Vocabulary and Reading Proficiency

    Science.gov (United States)

    Phillips, Linda M.; Norris, Stephen P.; Hayward, Denyse V.; Lovell, Meridith A.

    2017-01-01

    This study investigated whether mothers' measured reading proficiency and their educational level predict, over and above each other, their children's receptive vocabulary and reading proficiency when confounding factors of speaking a minority language, ethnicity, number of children in the family, and marital and employment status are controlled.…

  17. The role of sleep in predicting college academic performance: is it a unique predictor?

    Science.gov (United States)

    Taylor, Daniel J; Vatthauer, Karlyn E; Bramoweth, Adam D; Ruggero, Camilo; Roane, Brandy

    2013-01-01

    Few studies have looked at the predictability of academic performance (i.e., cumulative grade point average [GPA]) using sleep when common nonsleep predictors of academic performance are included. This project studied psychological, demographic, educational, and sleep risk factors of decreased academic performance in college undergraduates. Participants (N = 867) completed a questionnaire packet and sleep diary. It was hypothesized that low total sleep time (TST), increased sleep onset latency, later bedtimes, later wake times, and TST inconsistency would predict decreased academic performance. The most significant predictors of academic performance were high school GPA, standardized test scores (i.e., SAT/ACT), TST, time awake before arising (TWAK), TST inconsistency, and the quadratic terms of perceived stress (PSS) and TST.

  18. Assessment of Mars Exploration Rover Landing Site Predictions

    Science.gov (United States)

    Golombek, M. P.

    2005-05-01

    Comprehensive analyses of remote sensing data during the 3-year effort to select the Mars Exploration Rover landing sites at Gusev crater and Meridiani Planum correctly predicted the safe and trafficable surfaces explored by the two rovers. Gusev crater was predicted to be a relatively low relief surface that was comparably dusty, but less rocky than the Viking landing sites. Available data for Meridiani Planum indicated a very flat plain composed of basaltic sand to granules and hematite that would look completely unlike any of the existing landing sites with a dark, low albedo surface, little dust and very few rocks. Orbital thermal inertia measurements of 315 J m-2 s-0.5 K-1 at Gusev suggested surfaces dominated by duricrust to cemented soil-like materials or cohesionless sand or granules, which is consistent with observed soil characteristics and measured thermal inertias from the surface. THEMIS thermal inertias along the traverse at Gusev vary from 285 at the landing site to 330 around Bonneville rim and show systematic variations that can be related to the observed increase in rock abundance (5-30%). Meridiani has an orbital bulk inertia of ~200, similar to measured surface inertias that correspond to observed surfaces dominated by 0.2 mm sand size particles. Rock abundance derived from orbital thermal differencing techniques suggested that Meridiani Planum would have very low rock abundance, consistent with the rock free plain traversed by Opportunity. Spirit landed in an 8% orbital rock abundance pixel, consistent with the measured 7% of the surface covered by rocks >0.04 m diameter at the landing site, which is representative of the plains away from craters. The orbital albedo of the Spirit traverse varies from 0.19 to 0.30, consistent with surface measurements in and out of dust devil tracks. Opportunity is the first landing in a low albedo portion of Mars as seen from orbit, which is consistent with the dark, dust-free surface and measured albedos. The

  19. Does Trait Emotional Intelligence Predict Unique Variance in Early Career Success Beyond IQ and Personality?

    OpenAIRE

    Haro García, José Manuel de; Castejón Costa, Juan Luis

    2014-01-01

    In order to determine the contribution of emotional intelligence (EI) to career success, in this study, we analyzed the relationship between trait EI (TEI), general mental ability (GMA), the big five personality traits, and career success indicators, in a sample of 130 graduates who were in the early stages of their careers. Results from hierarchical regression analyses indicated that TEI, and especially its dimension “repair,” has incremental validity in predicting one of the career success ...

  20. Does Trait Emotional Intelligence Predict Unique Variance in Early Career Success Beyond IQ and Personality?

    OpenAIRE

    Haro García, José Manuel de; Castejón Costa, Juan Luis (coord.)

    2014-01-01

    In order to determine the contribution of emotional intelligence (EI) to career success, in this study, we analyzed the relationship between trait EI (TEI), general mental ability (GMA), the big five personality traits, and career success indicators, in a sample of 130 graduates who were in the early stages of their careers. Results from hierarchical regression analyses indicated that TEI, and especially its dimension “repair,” has incremental validity in predicting one of the career success ...

  1. MetWAMer: eukaryotic translation initiation site prediction

    Directory of Open Access Journals (Sweden)

    Brendel Volker

    2008-09-01

    Full Text Available Abstract Background Translation initiation site (TIS identification is an important aspect of the gene annotation process, requisite for the accurate delineation of protein sequences from transcript data. We have developed the MetWAMer package for TIS prediction in eukaryotic open reading frames of non-viral origin. MetWAMer can be used as a stand-alone, third-party tool for post-processing gene structure annotations generated by external computational programs and/or pipelines, or directly integrated into gene structure prediction software implementations. Results MetWAMer currently implements five distinct methods for TIS prediction, the most accurate of which is a routine that combines weighted, signal-based translation initiation site scores and the contrast in coding potential of sequences flanking TISs using a perceptron. Also, our program implements clustering capabilities through use of the k-medoids algorithm, thereby enabling cluster-specific TIS parameter utilization. In practice, our static weight array matrix-based indexing method for parameter set lookup can be used with good results in data sets exhibiting moderate levels of 5'-complete coverage. Conclusion We demonstrate that improvements in statistically-based models for TIS prediction can be achieved by taking the class of each potential start-methionine into account pending certain testing conditions, and that our perceptron-based model is suitable for the TIS identification task. MetWAMer represents a well-documented, extensible, and freely available software system that can be readily re-trained for differing target applications and/or extended with existing and novel TIS prediction methods, to support further research efforts in this area.

  2. ESA-UbiSite: accurate prediction of human ubiquitination sites by identifying a set of effective negatives.

    Science.gov (United States)

    Wang, Jyun-Rong; Huang, Wen-Lin; Tsai, Ming-Ju; Hsu, Kai-Ti; Huang, Hui-Ling; Ho, Shinn-Ying

    2017-03-01

    Numerous ubiquitination sites remain undiscovered because of the limitations of mass spectrometry-based methods. Existing prediction methods use randomly selected non-validated sites as non-ubiquitination sites to train ubiquitination site prediction models. We propose an evolutionary screening algorithm (ESA) to select effective negatives among non-validated sites and an ESA-based prediction method, ESA-UbiSite, to identify human ubiquitination sites. The ESA selects non-validated sites least likely to be ubiquitination sites as training negatives. Moreover, the ESA and ESA-UbiSite use a set of well-selected physicochemical properties together with a support vector machine for accurate prediction. Experimental results show that ESA-UbiSite with effective negatives achieved 0.92 test accuracy and a Matthews's correlation coefficient of 0.48, better than existing prediction methods. The ESA increased ESA-UbiSite's test accuracy from 0.75 to 0.92 and can improve other post-translational modification site prediction methods. An ESA-UbiSite-based web server has been established at http://iclab.life.nctu.edu.tw/iclab_webtools/ESAUbiSite/ . syho@mail.nctu.edu.tw. Supplementary data are available at Bioinformatics online.

  3. Predicting Risky Sexual Behavior: the Unique and Interactive Roles of Childhood Conduct Disorder Symptoms and Callous-Unemotional Traits.

    Science.gov (United States)

    Anderson, Sarah L; Zheng, Yao; McMahon, Robert J

    2016-11-04

    Conduct disorder (CD) symptoms and callous-unemotional (CU) traits have been shown to be uniquely associated with risky sexual behavior (RSB) in adolescence and early adulthood, yet their interactive role in predicting RSB remains largely unknown. This study aimed to investigate the predictive value of CD symptoms and CU traits, as well as their interaction, on several RSB outcomes in adolescence and early adulthood. A total of 683 participants (41.7 % female, 47.4 % African American) were followed annually and self-reported age of first sexual intercourse, frequency of condom use, pregnancy, contraction of sexually transmitted infections, and engagement in sexual solicitation from grade 7 to 2-years post-high school. CD symptoms predicted age of first sexual intercourse, condom use, and sexual solicitation. CU traits predicted age of first sexual intercourse and pregnancy. Their interaction predicted a composite score of these RSBs such that CD symptoms positively predicted the composite score among those with high levels of CU traits but not among those with low levels of CU traits. The current findings provide information regarding the importance of both CD symptoms and CU traits in understanding adolescent and early adulthood RSB, as well as the benefits of examining multiple RSB outcomes during this developmental period. These findings have implications for the development and implementation of preventive efforts to target these risky behaviors among adolescents and young adults.

  4. Search performance is better predicted by tileability than presence of a unique basic feature.

    Science.gov (United States)

    Chang, Honghua; Rosenholtz, Ruth

    2016-08-01

    Traditional models of visual search such as feature integration theory (FIT; Treisman & Gelade, 1980), have suggested that a key factor determining task difficulty consists of whether or not the search target contains a "basic feature" not found in the other display items (distractors). Here we discriminate between such traditional models and our recent texture tiling model (TTM) of search (Rosenholtz, Huang, Raj, Balas, & Ilie, 2012b), by designing new experiments that directly pit these models against each other. Doing so is nontrivial, for two reasons. First, the visual representation in TTM is fully specified, and makes clear testable predictions, but its complexity makes getting intuitions difficult. Here we elucidate a rule of thumb for TTM, which enables us to easily design new and interesting search experiments. FIT, on the other hand, is somewhat ill-defined and hard to pin down. To get around this, rather than designing totally new search experiments, we start with five classic experiments that FIT already claims to explain: T among Ls, 2 among 5s, Q among Os, O among Qs, and an orientation/luminance-contrast conjunction search. We find that fairly subtle changes in these search tasks lead to significant changes in performance, in a direction predicted by TTM, providing definitive evidence in favor of the texture tiling model as opposed to traditional views of search.

  5. Spatial characterization and prediction of Neanderthal sites based on environmental information and stochastic modelling

    Science.gov (United States)

    Maerker, Michael; Bolus, Michael

    2014-05-01

    We present a unique spatial dataset of Neanderthal sites in Europe that was used to train a set of stochastic models to reveal the correlations between the site locations and environmental indices. In order to assess the relations between the Neanderthal sites and environmental variables as described above we applied a boosted regression tree approach (TREENET) a statistical mechanics approach (MAXENT) and support vector machines. The stochastic models employ a learning algorithm to identify a model that best fits the relationship between the attribute set (predictor variables (environmental variables) and the classified response variable which is in this case the types of Neanderthal sites. A quantitative evaluation of model performance was done by determining the suitability of the model for the geo-archaeological applications and by helping to identify those aspects of the methodology that need improvements. The models' predictive performances were assessed by constructing the Receiver Operating Characteristics (ROC) curves for each Neanderthal class, both for training and test data. In a ROC curve the Sensitivity is plotted over the False Positive Rate (1-Specificity) for all possible cut-off points. The quality of a ROC curve is quantified by the measure of the parameter area under the ROC curve. The dependent variable or target variable in this study are the locations of Neanderthal sites described by latitude and longitude. The information on the site location was collected from literature and own research. All sites were checked for site accuracy using high resolution maps and google earth. The study illustrates that the models show a distinct ranking in model performance with TREENET outperforming the other approaches. Moreover Pre-Neanderthals, Early Neanderthals and Classic Neanderthals show a specific spatial distribution. However, all models show a wide correspondence in the selection of the most important predictor variables generally showing less

  6. Children's unique experience of depression: Using a developmental approach to predict variation in symptomatology

    Directory of Open Access Journals (Sweden)

    Ginicola Misty M

    2007-08-01

    Full Text Available Abstract Background Current clinical knowledge suggests that children can have different types of depressive symptoms (irritability and aggression, but presents no theoretical basis for these differences. Using a developmental approach, the present study sought to test the relationship between developmental level (mental age and expression of depressive symptoms. The primary hypothesis was that as children's mental age increased, so would the number of internalizing symptoms present. Methods Participants were 252 psychiatric inpatients aged 4 to 16 with a diagnosed depressive disorder. All children were diagnosed by trained clinicians using DSM criteria. Patients were predominantly male (61% with varied ethnic backgrounds (Caucasian 54%; African American 22%; Hispanic 19%; Other 5%. Children were given an IQ test (KBIT or WISC while within the hospital. Mental age was calculated by using the child's IQ score and chronological age. Four trained raters reviewed children's records for depressive symptoms as defined by the DSM-IV TR. Additionally, a ratio score was calculated to indicate the number of internalizing symptoms to total symptoms. Results Mental age positively correlated (r = .51 with an internalizing total symptom ratio score and delineated between several individual symptoms. Mental age also predicted comorbidity with anxiety and conduct disorders. Children of a low mental age were more likely to be comorbid with conduct disorders, whereas children with a higher mental age presented more often with anxiety disorders. Gender was independently related to depressive symptoms, but minority status interacted with mental age. Conclusion The results of this study indicate that a developmental approach is useful in understanding children's depressive symptoms and has implications for both diagnosis and treatment of depression. If children experience depression differently, it follows that treatment options may also differ from that which is

  7. Method of predicting Splice Sites based on signal interactions

    Directory of Open Access Journals (Sweden)

    Deogun Jitender S

    2006-04-01

    Full Text Available Abstract Background Predicting and proper ranking of canonical splice sites (SSs is a challenging problem in bioinformatics and machine learning communities. Any progress in SSs recognition will lead to better understanding of splicing mechanism. We introduce several new approaches of combining a priori knowledge for improved SS detection. First, we design our new Bayesian SS sensor based on oligonucleotide counting. To further enhance prediction quality, we applied our new de novo motif detection tool MHMMotif to intronic ends and exons. We combine elements found with sensor information using Naive Bayesian Network, as implemented in our new tool SpliceScan. Results According to our tests, the Bayesian sensor outperforms the contemporary Maximum Entropy sensor for 5' SS detection. We report a number of putative Exonic (ESE and Intronic (ISE Splicing Enhancers found by MHMMotif tool. T-test statistics on mouse/rat intronic alignments indicates, that detected elements are on average more conserved as compared to other oligos, which supports our assumption of their functional importance. The tool has been shown to outperform the SpliceView, GeneSplicer, NNSplice, Genio and NetUTR tools for the test set of human genes. SpliceScan outperforms all contemporary ab initio gene structural prediction tools on the set of 5' UTR gene fragments. Conclusion Designed methods have many attractive properties, compared to existing approaches. Bayesian sensor, MHMMotif program and SpliceScan tools are freely available on our web site. Reviewers This article was reviewed by Manyuan Long, Arcady Mushegian and Mikhail Gelfand.

  8. Prediction, conservation analysis, and structural characterization of mammalian mucin-type O-glycosylation sites

    DEFF Research Database (Denmark)

    Julenius, Karin; Mølgaard, Anne; Gupta, Ramneek

    2005-01-01

    than a nonglycosylated one. The Protein Data Bank was analyzed for structural information, and 12 glycosylated structures were obtained. All positive sites were found in coil or turn regions. A method for predicting the location for mucin-type glycosylation sites was trained using a neural network...... approach. The best overall network used as input amino acid composition, averaged surface accessibility predictions together with substitution matrix profile encoding of the sequence. To improve prediction on isolated (single) sites, networks were trained on isolated sites only. The final method combines...... predictions from the best overall network and the best isolated site network; this prediction method correctly predicted 76% of the glycosylated residues and 93% of the nonglycosylated residues. NetOGlyc 3.1 can predict sites for completely new proteins without losing its performance. The fact that the sites...

  9. Improving prediction of surgical site infection risk with multilevel modeling.

    Directory of Open Access Journals (Sweden)

    Lauren Saunders

    Full Text Available BACKGROUND: Surgical site infection (SSI surveillance is a key factor in the elaboration of strategies to reduce SSI occurrence and in providing surgeons with appropriate data feedback (risk indicators, clinical prediction rule. AIM: To improve the predictive performance of an individual-based SSI risk model by considering a multilevel hierarchical structure. PATIENTS AND METHODS: Data were collected anonymously by the French SSI active surveillance system in 2011. An SSI diagnosis was made by the surgical teams and infection control practitioners following standardized criteria. A random 20% sample comprising 151 hospitals, 502 wards and 62280 patients was used. Three-level (patient, ward, hospital hierarchical logistic regression models were initially performed. Parameters were estimated using the simulation-based Markov Chain Monte Carlo procedure. RESULTS: A total of 623 SSI were diagnosed (1%. The hospital level was discarded from the analysis as it did not contribute to variability of SSI occurrence (p  = 0.32. Established individual risk factors (patient history, surgical procedure and hospitalization characteristics were identified. A significant heterogeneity in SSI occurrence between wards was found (median odds ratio [MOR] 3.59, 95% credibility interval [CI] 3.03 to 4.33 after adjusting for patient-level variables. The effects of the follow-up duration varied between wards (p<10-9, with an increased heterogeneity when follow-up was <15 days (MOR 6.92, 95% CI 5.31 to 9.07]. The final two-level model significantly improved the discriminative accuracy compared to the single level reference model (p<10-9, with an area under the ROC curve of 0.84. CONCLUSION: This study sheds new light on the respective contribution of patient-, ward- and hospital-levels to SSI occurrence and demonstrates the significant impact of the ward level over and above risk factors present at patient level (i.e., independently from patient case-mix.

  10. Unique contributions of emotion regulation and executive functions in predicting the quality of parent-child interaction behaviors.

    Science.gov (United States)

    Shaffer, Anne; Obradović, Jelena

    2017-03-01

    Parenting is a cognitive, emotional, and behavioral endeavor, yet limited research investigates parents' executive functions and emotion regulation as predictors of how parents interact with their children. The current study is a multimethod investigation of parental self-regulation in relation to the quality of parenting behavior and parent-child interactions in a diverse sample of parents and kindergarten-age children. Using path analyses, we tested how parent executive functions (inhibitory control) and lack of emotion regulation strategies uniquely relate to both sensitive/responsive behaviors and positive/collaborative behaviors during observed interaction tasks. In our analyses, we accounted for parent education, financial stress, and social support as socioeconomic factors that likely relate to parent executive function and emotion regulation skills. In a diverse sample of primary caregivers (N = 102), we found that direct assessment of parent inhibitory control was positively associated with sensitive/responsive behaviors, whereas parent self-reported difficulties in using emotion regulation strategies were associated with lower levels of positive and collaborative dyadic behaviors. Parent education and financial stress predicted inhibitory control, and social support predicted emotion regulation difficulties; parent education was also a significant predictor of sensitive/responsive behaviors. Greater inhibitory control skills and fewer difficulties identifying effective emotion regulation strategies were not significantly related in our final path model. We discuss our findings in the context of current and emerging parenting interventions. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  11. The Aiguille du Midi (Mont Blanc massif): a unique high-Alpine site to study bedrock permafrost

    Science.gov (United States)

    Deline, P.; Coviello, V.; Cremonese, E.; Gruber, S.; Krautblatter, M.; Malet, S. Jaillet (1), E.; Morra di Cella, U.; Noetzli, J.; Pogliotti, P.; Verleysdonk, S.

    2009-04-01

    Permafrost and its change in steep high-Alpine rock walls remain insufficiently understood because of the difficulties of in situ measurements. A large proportion of permafrost studies is mainly based on modelling, with a few existing instrumented sites and a resulting lack of process understanding. Yet, a number of rockfalls that occurred in the last decade in the Alps are likely related to climatically-driven permafrost degradation, as indicated by ice in starting zones, increased air temperature, and modelling studies. Starting off in the framework of the French-Italian PERMAdataROC project and presently under development within the EU co-funded project PermaNET (Permafrost long-term monitoring network: www.permanet-alpinespace.eu), our investigations at the Aiguille du Midi begin in 2005. The summit (3842 m a.s.l) is accessible from Chamonix by a cable car which was built at the end of the 1950s. Half a million tourists visit the site each year. Because of its elevation, geometry, and year-round accessibility to rock slopes of diverse aspects and to galleries, the site was chosen for: - Monitoring of the thermal regime in steep rock walls. Thermistors were installed at depths of 2, 10, 30 and 55 cm, at all aspects and with slope angles in the range 60-90° (determining e.g. the presence and influence of snow). - Measurements of high altitude climatic data (air temperature and humidity, incoming and outgoing solar radiation, wind speed and direction) perpendicular to the rockwall surface, by movable automatic weather stations. Together with the rock temperature measurements, these data (see Morra et al., poster in session CR4.1) can be used for physically-based model validation (see Pogliotti et al., oral presentation in session CR4.1) or statistical models construction of rock temperature distribution and variability in the rock walls. - Making a 3D-high-resolution DEM by long-range (rock walls) and short-range (galleries) terrestrial laser scanning

  12. Snow multivariable data assimilation for hydrological predictions in Alpine sites

    Science.gov (United States)

    Piazzi, Gaia; Thirel, Guillaume; Campo, Lorenzo; Gabellani, Simone; Stevenin, Hervè

    2017-04-01

    Snowpack dynamics (snow accumulation and ablation) strongly impacts on hydrological processes in Alpine areas. During the winter season the presence of snow cover (snow accumulation) reduces the drainage in the basin with a resulting lower watershed time of concentration in case of possible rainfall events. Moreover, the release of the significant water volume stored in winter (snowmelt) considerably contributes to the total discharge during the melting period. Therefore when modeling hydrological processes in snow-dominated catchments the quality of predictions deeply depends on how the model succeeds in catching snowpack dynamics. The integration of a hydrological model with a snow module allows improving predictions of river discharges. Besides the well-known modeling limitations (uncertainty in parameterizations; possible errors affecting both meteorological forcing data and initial conditions; approximations in boundary conditions), there are physical factors that make an exhaustive reconstruction of snow dynamics complicated: snow intermittence in space and time, stratification and slow phenomena like metamorphism processes, uncertainty in snowfall evaluation, wind transportation, etc. Data Assimilation (DA) techniques provide an objective methodology to combine several independent snow-related data sources (model simulations, ground-based measurements and remote sensed observations) in order to obtain the most likely estimate of snowpack state. This study presents SMASH (Snow Multidata Assimilation System for Hydrology), a multi-layer snow dynamic model strengthened by a multivariable DA framework for hydrological purposes. The model is physically based on mass and energy balances and can be used to reproduce the main physical processes occurring within the snowpack: accumulation, density dynamics, melting, sublimation, radiative balance, heat and mass exchanges. The model is driven by observed forcing meteorological data (air temperature, wind velocity

  13. Structural and functional studies on a unique linear neutralizing antigenic site (G5) of the rabies virus glycoprotein.

    NARCIS (Netherlands)

    R.W.J. van der Heijden (Roger); J.P.M. Langedijk; J. Groen (Jan); F.G.C.M. Uytdehaag (Fons); R.H. Meloen; A.D.M.E. Osterhaus (Albert)

    1993-01-01

    textabstractThe core of a unique linear neutralization epitope (G5) on the glycoprotein of rabies virus, recognized by a virus-neutralizing mouse monoclonal antibody (MAb 6-15C4), was determined by Pepscan analysis. The G5 epitope was defined as an octapeptide (LHDFRSDE). The contribution of the

  14. Reduction of Ambiguity in Phosphorylation-site Localization in Large-scale Phosphopeptide Profiling by Data Filter using Unique Mass Class Information

    Energy Technology Data Exchange (ETDEWEB)

    Madar, Inamul Hasan; Back, Seunghoon; Mun, Donggi; Kim, Hokeun; Lee, Sangwon [Korea Univ., Seoul (Korea, Republic of); Jung, Jae Hun; Kim, Kwang Pyo [Kyung Hee Univ., Yongin (Korea, Republic of)

    2014-03-15

    The rapid development of shotgun proteomics is paving the way for extensive proteome profiling, while providing extensive information on various post translational modifications (PTMs) that occur to a proteome of interest. For example, the current phosphoproteomic methods can yield more than 10,000 phosphopeptides identified from a proteome sample. Despite these developments, it remains a challenging issue to pinpoint the true phosphorylation sites, especially when multiple sites are possible for phosphorylation in the peptides. We developed the Phospho-UMC filter, which is a simple method of localizing the site of phosphorylation using unique mass classes (UMCs) information to differentiate phosphopeptides with different phosphorylation sites and increase the confidence in phosphorylation site localization. The method was applied to large scale phosphopeptide profiling data and was demonstrated to be effective in the reducing ambiguity associated with the tandem mass spectrometric data analysis of phosphopeptides.

  15. Prediction of nucleosome positioning based on transcription factor binding sites.

    Directory of Open Access Journals (Sweden)

    Xianfu Yi

    Full Text Available BACKGROUND: The DNA of all eukaryotic organisms is packaged into nucleosomes, the basic repeating units of chromatin. The nucleosome consists of a histone octamer around which a DNA core is wrapped and the linker histone H1, which is associated with linker DNA. By altering the accessibility of DNA sequences, the nucleosome has profound effects on all DNA-dependent processes. Understanding the factors that influence nucleosome positioning is of great importance for the study of genomic control mechanisms. Transcription factors (TFs have been suggested to play a role in nucleosome positioning in vivo. PRINCIPAL FINDINGS: Here, the minimum redundancy maximum relevance (mRMR feature selection algorithm, the nearest neighbor algorithm (NNA, and the incremental feature selection (IFS method were used to identify the most important TFs that either favor or inhibit nucleosome positioning by analyzing the numbers of transcription factor binding sites (TFBSs in 53,021 nucleosomal DNA sequences and 50,299 linker DNA sequences. A total of nine important families of TFs were extracted from 35 families, and the overall prediction accuracy was 87.4% as evaluated by the jackknife cross-validation test. CONCLUSIONS: Our results are consistent with the notion that TFs are more likely to bind linker DNA sequences than the sequences in the nucleosomes. In addition, our results imply that there may be some TFs that are important for nucleosome positioning but that play an insignificant role in discriminating nucleosome-forming DNA sequences from nucleosome-inhibiting DNA sequences. The hypothesis that TFs play a role in nucleosome positioning is, thus, confirmed by the results of this study.

  16. Factors predicting surgical site infection after posterior lumbar surgery

    Science.gov (United States)

    Wang, Tao; Wang, Hui; Yang, Da-Long; Jiang, Li-Qiang; Zhang, Li-Jun; Ding, Wen-Yuan

    2017-01-01

    Abstract This is a retrospective study. The purpose of this study is to explore incidence and risk factors for surgical site infection (SSI) after posterior lumbar surgery. SSI is a common complication after posterior lumbar surgery, bringing mental and physical pain and prolonging hospital stay. However, predisposing factors, as reported less, remain controversial. Patients who underwent posterior lumbar surgery at 3 centers between 2006 and 2016 were included. The possible factors include 3 aspects: demographic variables-age, sex, body mass index (BMI), waist-to-hip radio (WHR), hypertension, diabetes, heart disease, smoking, drinking, steroidal injection, surgical time between June and September, preoperative shower; blood test variables-white blood cell (WBC), neutrophil, red blood cell (RBC), hemoglobin (Hb), total protein (TP), albumin, albumin/globulin (A/G), C-reactive protein (CRP), procalcitonin (PCT), erythrocyte sedimentation rate (ESR) and surgical related variables-operation time, blood loss, operative level, instrumentation, incision length. Factors related with SSI were also performed by multivariate analysis. The prevalence of SSI was 3.00% (267 cases of 8879) had a postoperative wound infection. There were significant difference in WHR (0.92 vs 0.83), WBC (4.31 vs 6.69), TP (58.7 vs 65.2), albumin (36.9 vs 43.2), CRP (2.01 vs 0.57), PCT (0.097 vs 0.067), operation time (217.9 vs 195.7), blood loss (997.1 vs 915.3) and operative level (3.05 vs 2.45) and incision length (24.1 vs 20.0) between SSI group and non-SSI group. >60 years old, female, BMI 30.0, diabetes, male smoking, preoperative steroidal injection, surgical time between June and September, no preoperative shower, instrumentation surgery were risk factors for SSI after posterior lumbar surgery. Many factors, >60 years old, female, BMI, WHR, diabetes, male smoking, preoperative steroidal injection, surgical time between June and September, preoperative shower, WBC, TP, albumin, CRP, PCT

  17. KatB, a cyanobacterial Mn-catalase with unique active site configuration: Implications for enzyme function.

    Science.gov (United States)

    Bihani, Subhash C; Chakravarty, Dhiman; Ballal, Anand

    2016-04-01

    Manganese catalases (Mn-catalases), a class of H2O2 detoxifying proteins, are structurally and mechanistically distinct from the commonly occurring catalases, which contain heme. Active site of Mn-catalases can serve as template for the synthesis of catalase mimetics for therapeutic intervention in oxidative stress related disorders. However, unlike the heme catalases, structural aspects of Mn-catalases remain inadequately explored. The genome of the ancient cyanobacterium Anabaena PCC7120, shows the presence of two Mn-catalases, KatA and KatB. Here, we report the biochemical and structural characterization of KatB. The KatB protein (with a C-terminal his-tag) was over-expressed in Escherichia coli and purified by affinity chromatography. On the addition of Mn(2+) to the E. coli growth medium, a substantial increase in production of the soluble KatB protein was observed. The purified KatB protein was an efficient catalase, which was relatively insensitive to inhibition by azide. Crystal structure of KatB showed a hexameric assembly with four-helix bundle fold, characteristic of the Ferritin-like superfamily. With canonical Glu4His2 coordination geometry and two terminal water ligands, the KatB active site was distinctly different from that of other Mn-catalases. Interestingly, the KatB active site closely resembled the active sites of ruberythrin/bacterioferritin, bi-iron members of the Ferritin-like superfamily. The KatB crystal structure provided fundamental insights into the evolutionary relationship within the Ferritin-like superfamily and further showed that Mn-catalases can be sub-divided into two groups, each with a distinct active site configuration.

  18. Exploring the role of water in molecular recognition: predicting protein ligandability using a combinatorial search of surface hydration sites

    Science.gov (United States)

    Vukovic, Sinisa; Brennan, Paul E.; Huggins, David J.

    2016-09-01

    The interaction between any two biological molecules must compete with their interaction with water molecules. This makes water the most important molecule in medicine, as it controls the interactions of every therapeutic with its target. A small molecule binding to a protein is able to recognize a unique binding site on a protein by displacing bound water molecules from specific hydration sites. Quantifying the interactions of these water molecules allows us to estimate the potential of the protein to bind a small molecule. This is referred to as ligandability. In the study, we describe a method to predict ligandability by performing a search of all possible combinations of hydration sites on protein surfaces. We predict ligandability as the summed binding free energy for each of the constituent hydration sites, computed using inhomogeneous fluid solvation theory. We compared the predicted ligandability with the maximum observed binding affinity for 20 proteins in the human bromodomain family. Based on this comparison, it was determined that effective inhibitors have been developed for the majority of bromodomains, in the range from 10 to 100 nM. However, we predict that more potent inhibitors can be developed for the bromodomains BPTF and BRD7 with relative ease, but that further efforts to develop inhibitors for ATAD2 will be extremely challenging. We have also made predictions for the 14 bromodomains with no reported small molecule K d values by isothermal titration calorimetry. The calculations predict that PBRM1(1) will be a challenging target, while others such as TAF1L(2), PBRM1(4) and TAF1(2), should be highly ligandable. As an outcome of this work, we assembled a database of experimental maximal K d that can serve as a community resource assisting medicinal chemistry efforts focused on BRDs. Effective prediction of ligandability would be a very useful tool in the drug discovery process.

  19. SSFinder: High Throughput CRISPR-Cas Target Sites Prediction Tool

    Directory of Open Access Journals (Sweden)

    Santosh Kumar Upadhyay

    2014-01-01

    Full Text Available Clustered regularly interspaced short palindromic repeats (CRISPR and CRISPR-associated protein (Cas system facilitates targeted genome editing in organisms. Despite high demand of this system, finding a reliable tool for the determination of specific target sites in large genomic data remained challenging. Here, we report SSFinder, a python script to perform high throughput detection of specific target sites in large nucleotide datasets. The SSFinder is a user-friendly tool, compatible with Windows, Mac OS, and Linux operating systems, and freely available online.

  20. Protein-lipid interactions: correlation of a predictive algorithm for lipid-binding sites with three-dimensional structural data

    Directory of Open Access Journals (Sweden)

    Goldmann Wolfgang H

    2006-03-01

    Full Text Available Abstract Background Over the past decade our laboratory has focused on understanding how soluble cytoskeleton-associated proteins interact with membranes and other lipid aggregates. Many protein domains mediating specific cell membrane interactions appear by fluorescence microscopy and other precision techniques to be partially inserted into the lipid bilayer. It is unclear whether these protein-lipid-interactions are dependent on shared protein motifs or unique regional physiochemistry, or are due to more global characteristics of the protein. Results We have developed a novel computational program that predicts a protein's lipid-binding site(s from primary sequence data. Hydrophobic labeling, Fourier transform infrared spectroscopy (FTIR, film balance, T-jump, CD spectroscopy and calorimetry experiments confirm that the interfaces predicted for several key cytoskeletal proteins (alpha-actinin, Arp2, CapZ, talin and vinculin partially insert into lipid aggregates. The validity of these predictions is supported by an analysis of the available three-dimensional structural data. The lipid interfaces predicted by our algorithm generally contain energetically favorable secondary structures (e.g., an amphipathic alpha-helix flanked by a flexible hinge or loop region, are solvent-exposed in the intact protein, and possess favorable local or global electrostatic properties. Conclusion At present, there are few reliable methods to determine the region of a protein that mediates biologically important interactions with lipids or lipid aggregates. Our matrix-based algorithm predicts lipid interaction sites that are consistent with the available biochemical and structural data. To determine whether these sites are indeed correctly identified, and whether use of the algorithm can be safely extended to other classes of proteins, will require further mapping of these sites, including genetic manipulation and/or targeted crystallography.

  1. MONTE CARLO ANALYSIS FOR PREDICTION OF NOISE FROM A CONSTRUCTION SITE

    Directory of Open Access Journals (Sweden)

    Zaiton Haron

    2009-06-01

    Full Text Available The large number of operations involving noisy machinery associated with construction site activities result in considerable variation in the noise levels experienced at receiver locations. This paper suggests an approach to predict noise levels generated from a site by using a Monte Carlo approach. This approach enables the determination of details regarding the statistical uncertainties associated with noise level predictions or temporal distributions. This technique could provide the basis for a generalised prediction technique and a simple noise management tool.

  2. Predicting enzymatic function from global binding site descriptors.

    Science.gov (United States)

    Volkamer, Andrea; Kuhn, Daniel; Rippmann, Friedrich; Rarey, Matthias

    2013-03-01

    Due to the rising number of solved protein structures, computer-based techniques for automatic protein functional annotation and classification into families are of high scientific interest. DoGSiteScorer automatically calculates global descriptors for self-predicted pockets based on the 3D structure of a protein. Protein function predictors on three levels with increasing granularity are built by use of a support vector machine (SVM), based on descriptors of 26632 pockets from enzymes with known structure and enzyme classification. The SVM models represent a generalization of the available descriptor space for each enzyme class, subclass, and substrate-specific sub-subclass. Cross-validation studies show accuracies of 68.2% for predicting the correct main class and accuracies between 62.8% and 80.9% for the six subclasses. Substrate-specific recall rates for a kinase subset are 53.8%. Furthermore, application studies show the ability of the method for predicting the function of unknown proteins and gaining valuable information for the function prediction field. Copyright © 2012 Wiley Periodicals, Inc.

  3. Prediction of protein hydration sites from sequence by modular neural networks

    DEFF Research Database (Denmark)

    Ehrlich, L.; Reczko, M.; Bohr, Henrik;

    1998-01-01

    The hydration properties of a protein are important determinants of its structure and function. Here, modular neural networks are employed to predict ordered hydration sites using protein sequence information. First, secondary structure and solvent accessibility are predicted from sequence with t...... provide insight into the mutual interdependencies between the location of ordered water sites and the structural and chemical characteristics of the protein residues.......The hydration properties of a protein are important determinants of its structure and function. Here, modular neural networks are employed to predict ordered hydration sites using protein sequence information. First, secondary structure and solvent accessibility are predicted from sequence with two...... structure and solvent accessibility and, using actual values of these properties, redidue hydration can be predicted to 77% accuracy with a Metthews coefficient of 0.43. However, predicted property data with an accuracy of 60-70% result in less than half the improvement in predictive performance observed...

  4. Prediction of PK-specific phosphorylation site based on information entropy

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Phosphorylation is a crucial way to control the activity of proteins in many eukaryotic organisms in vivo. Experimental methods to determine phosphorylation sites in substrates are usually restricted by the in vitro condition of enzymes and very intensive in time and labor. Although some in silico methods and web servers have been introduced for automatic detection of phosphorylation sites, sophisticated methods are still in urgent demand to further improve prediction performances. Protein primary se-quences can help predict phosphorylation sites catalyzed by different protein kinase and most com-putational approaches use a short local peptide to make prediction. However, the useful information may be lost if only the conservative residues that are not close to the phosphorylation site are consid-ered in prediction, which would hamper the prediction results. A novel prediction method named IEPP (Information-Entropy based Phosphorylation Prediction) is presented in this paper for automatic de-tection of potential phosphorylation sites. In prediction, the sites around the phosphorylation sites are selected or excluded by their entropy values. The algorithm was compared with other methods such as GSP and PPSP on the ABL, MAPK and PKA PK families. The superior prediction accuracies were ob-tained in various measurements such as sensitivity (Sn) and specificity (Sp). Furthermore, compared with some online prediction web servers on the new discovered phosphorylation sites, IEPP also yielded the best performance. IEPP is another useful computational resource for identification of PK-specific phosphorylation sites and it also has the advantages of simpleness, efficiency and con-venience.

  5. POLYAR, a new computer program for prediction of poly(A sites in human sequences

    Directory of Open Access Journals (Sweden)

    Qamar Raheel

    2010-11-01

    Full Text Available Abstract Background mRNA polyadenylation is an essential step of pre-mRNA processing in eukaryotes. Accurate prediction of the pre-mRNA 3'-end cleavage/polyadenylation sites is important for defining the gene boundaries and understanding gene expression mechanisms. Results 28761 human mapped poly(A sites have been classified into three classes containing different known forms of polyadenylation signal (PAS or none of them (PAS-strong, PAS-weak and PAS-less, respectively and a new computer program POLYAR for the prediction of poly(A sites of each class was developed. In comparison with polya_svm (till date the most accurate computer program for prediction of poly(A sites while searching for PAS-strong poly(A sites in human sequences, POLYAR had a significantly higher prediction sensitivity (80.8% versus 65.7% and specificity (66.4% versus 51.7% However, when a similar sort of search was conducted for PAS-weak and PAS-less poly(A sites, both programs had a very low prediction accuracy, which indicates that our knowledge about factors involved in the determination of the poly(A sites is not sufficient to identify such polyadenylation regions. Conclusions We present a new classification of polyadenylation sites into three classes and a novel computer program POLYAR for prediction of poly(A sites/regions of each of the class. In tests, POLYAR shows high accuracy of prediction of the PAS-strong poly(A sites, though this program's efficiency in searching for PAS-weak and PAS-less poly(A sites is not very high but is comparable to other available programs. These findings suggest that additional characteristics of such poly(A sites remain to be elucidated. POLYAR program with a stand-alone version for downloading is available at http://cub.comsats.edu.pk/polyapredict.htm.

  6. Predicting proteasomal cleavage sites: a comparison of available methods

    DEFF Research Database (Denmark)

    Saxova, P.; Buus, S.; Brunak, Søren

    2003-01-01

    The proteasome plays an essential role in the immune responses of vertebrates. By degrading intercellular proteins from self and non-self, the proteasome produces the majority of the peptides that are presented to cytotoxic T cells (CTL). There is accumulating evidence that the C......-terminal, in particular, of CTL epitopes is cleaved precisely by the proteasome, whereas the N-terminal is produced with an extension, and later trimmed by peptidases in the cytoplasm and in the endoplasmic reticulum. Recently, three publicly available methods have been developed for prediction of the specificity...... of the proteasome. Here, we compare the performance of these methods on a large set of CTL epitopes. The best method, NetChop at www.cbs.dtu.dk/Services/NetChop, can capture similar to70% of the C-termini correctly. This result suggests that the predictions can still be improved, particularly if more quantitative...

  7. A Unique Engraved Shale Pendant from the Site of Star Carr: the oldest Mesolithic art in Britain

    Directory of Open Access Journals (Sweden)

    Nicky Milner

    2016-01-01

    Full Text Available In 2015 an engraved shale pendant was found during excavations at the Early Mesolithic site of Star Carr, UK. Engraved motifs on Mesolithic pendants are extremely rare, with the exception of amber pendants from southern Scandinavia. The artwork on the pendant is the earliest known Mesolithic art in Britain; the 'barbed line' motif is comparable to styles on the Continent, particularly in Denmark. When it was first uncovered the lines were barely visible but using a range of digital imaging techniques it has been possible to examine them in detail and determine the style of engraving as well as the order in which the lines might have been made. In addition, microwear and residue analyses were applied to examine whether the pendant showed signs that it had been strung or worn, and whether the lines had been made more visible through the application of pigments, as has been suggested for some Danish amber pendants. This approach of using multiple scientific and analytical techniques has not been used previously and provides a methodology for the examination of similar artefacts in the future.

  8. Prediction of calcium-binding sites by combining loop-modeling with machine learning

    Directory of Open Access Journals (Sweden)

    Altman Russ B

    2009-12-01

    Full Text Available Abstract Background Protein ligand-binding sites in the apo state exhibit structural flexibility. This flexibility often frustrates methods for structure-based recognition of these sites because it leads to the absence of electron density for these critical regions, particularly when they are in surface loops. Methods for recognizing functional sites in these missing loops would be useful for recovering additional functional information. Results We report a hybrid approach for recognizing calcium-binding sites in disordered regions. Our approach combines loop modeling with a machine learning method (FEATURE for structure-based site recognition. For validation, we compared the performance of our method on known calcium-binding sites for which there are both holo and apo structures. When loops in the apo structures are rebuilt using modeling methods, FEATURE identifies 14 out of 20 crystallographically proven calcium-binding sites. It only recognizes 7 out of 20 calcium-binding sites in the initial apo crystal structures. We applied our method to unstructured loops in proteins from SCOP families known to bind calcium in order to discover potential cryptic calcium binding sites. We built 2745 missing loops and evaluated them for potential calcium binding. We made 102 predictions of calcium-binding sites. Ten predictions are consistent with independent experimental verifications. We found indirect experimental evidence for 14 other predictions. The remaining 78 predictions are novel predictions, some with intriguing potential biological significance. In particular, we see an enrichment of beta-sheet folds with predicted calcium binding sites in the connecting loops on the surface that may be important for calcium-mediated function switches. Conclusion Protein crystal structures are a potentially rich source of functional information. When loops are missing in these structures, we may be losing important information about binding sites and active

  9. Can one predict DNA Transcription Start Sites by studying bubbles?

    CERN Document Server

    Van Erp, T S; Hagmann, J G; Peyrard, M

    2005-01-01

    It has been speculated that bubble formation of several base-pairs due to thermal fluctuations is indicatory for biological active sites. Recent evidence, based on experiments and molecular dynamics (MD) simulations using the Peyrard-Bishop-Dauxois model, seems to point in this direction. However, sufficiently large bubbles appear only seldom which makes an accurate calculation difficult even for minimal models. In this letter, we introduce a new method that is orders of magnitude faster than MD. Using this method we are able to show that the present evidence is unsubstantiated.

  10. Prediction of allosteric sites and mediating interactions through bond-to-bond propensities

    CERN Document Server

    Amor, Benjamin R C; Yaliraki, Sophia N; Barahona, Mauricio

    2016-01-01

    Allosteric regulation is central to many biochemical processes. Allosteric sites provide a target to fine-tune protein activity, yet we lack computational methods to predict them. Here, we present an efficient graph-theoretical approach for identifying allosteric sites and the mediating interactions that connect them to the active site. Using an atomistic graph with edges weighted by covalent and non-covalent bond energies, we obtain a bond-to-bond propensity that quantifies the effect of instantaneous bond fluctuations propagating through the protein. We use this propensity to detect the sites and communication pathways most strongly linked to the active site, assessing their significance through quantile regression and comparison against a reference set of 100 generic proteins. We exemplify our method in detail with three well-studied allosteric proteins: caspase-1, CheY, and h-Ras, correctly predicting the location of the allosteric site and identifying key allosteric interactions. Consistent prediction of...

  11. Kinase-specific prediction of protein phosphorylation sites

    DEFF Research Database (Denmark)

    Miller, Martin Lee; Blom, Nikolaj

    2009-01-01

    -substrate specificity. Here, we briefly describe the available resources for predicting kinase-specific phosphorylation from sequence properties. We address the strengths and weaknesses of these resources, which are based on methods ranging from simple consensus patterns to more advanced machine-learning algorithms....... Furthermore, a protocol for the use of the artificial neural network based predictors, NetPhos and NetPhosK, is provided. Finally, we point to possible developments with the intention of providing the community with improved and additional phosphorylation predictors for large-scale modeling of cellular...... signaling networks....

  12. A predictive model of intein insertion site for use in the engineering of molecular switches.

    Directory of Open Access Journals (Sweden)

    James Apgar

    Full Text Available Inteins are intervening protein domains with self-splicing ability that can be used as molecular switches to control activity of their host protein. Successfully engineering an intein into a host protein requires identifying an insertion site that permits intein insertion and splicing while allowing for proper folding of the mature protein post-splicing. By analyzing sequence and structure based properties of native intein insertion sites we have identified four features that showed significant correlation with the location of the intein insertion sites, and therefore may be useful in predicting insertion sites in other proteins that provide native-like intein function. Three of these properties, the distance to the active site and dimer interface site, the SVM score of the splice site cassette, and the sequence conservation of the site showed statistically significant correlation and strong predictive power, with area under the curve (AUC values of 0.79, 0.76, and 0.73 respectively, while the distance to secondary structure/loop junction showed significance but with less predictive power (AUC of 0.54. In a case study of 20 insertion sites in the XynB xylanase, two features of native insertion sites showed correlation with the splice sites and demonstrated predictive value in selecting non-native splice sites. Structural modeling of intein insertions at two sites highlighted the role that the insertion site location could play on the ability of the intein to modulate activity of the host protein. These findings can be used to enrich the selection of insertion sites capable of supporting intein splicing and hosting an intein switch.

  13. Prediction, conservation analysis, and structural characterization of mammalian mucin-type O-glycosylation sites

    DEFF Research Database (Denmark)

    Julenius, Karin; Mølgaard, Anne; Gupta, Ramneek;

    2004-01-01

    than a nonglycosylated one. The Protein Data Bank was analyzed for structural information, and 12 glycosylated structures were obtained. All positive sites were found in coil or turn regions. A method for predicting the location for mucin-type glycosylation sites was trained using a neural network...... could be predicted from averaged properties together with the fact that glycosylation sites are not precisely conserved indicates that mucin-type glycosylation in most cases is a bulk property and not a very site-specific one. NetOGlyc 3.1 is made available at www.cbs.dtu.dk/services/netoglyc....

  14. Recent Progress in Predicting Posttranslational Modification Sites in Proteins.

    Science.gov (United States)

    Xu, Yan; Chou, Kuo-Chen

    2016-01-01

    The posttranslational modification or PTM is a later but subtle step in protein biosynthesis via which to change the properties of a protein by adding a modified group to its one or more amino acid residues. PTMs are responsible for many significant biological processes, and meanwhile for many major diseases as well, such as cancer. Facing the avalanche of biological sequences generated in the post-genomic age, it is important for both basic research and drug development to timely identify the PTM sites in proteins. This Review is devoted to summarize the recent progresses in this area, with a focus on those predictors, which were developed based on the pseudo amino acid composition or PseAAC approach, and for which a publicly accessible web-server has been established. Meanwhile, the future challenge in this area has also been briefly addressed.

  15. Structural descriptor database: a new tool for sequence-based functional site prediction

    Directory of Open Access Journals (Sweden)

    Vasconcelos Ana

    2008-11-01

    Full Text Available Abstract Background The Structural Descriptor Database (SDDB is a web-based tool that predicts the function of proteins and functional site positions based on the structural properties of related protein families. Structural alignments and functional residues of a known protein set (defined as the training set are used to build special Hidden Markov Models (HMM called HMM descriptors. SDDB uses previously calculated and stored HMM descriptors for predicting active sites, binding residues, and protein function. The database integrates biologically relevant data filtered from several databases such as PDB, PDBSUM, CSA and SCOP. It accepts queries in fasta format and predicts functional residue positions, protein-ligand interactions, and protein function, based on the SCOP database. Results To assess the SDDB performance, we used different data sets. The Trypsion-like Serine protease data set assessed how well SDDB predicts functional sites when curated data is available. The SCOP family data set was used to analyze SDDB performance by using training data extracted from PDBSUM (binding sites and from CSA (active sites. The ATP-binding experiment was used to compare our approach with the most current method. For all evaluations, significant improvements were obtained with SDDB. Conclusion SDDB performed better when trusty training data was available. SDDB worked better in predicting active sites rather than binding sites because the former are more conserved than the latter. Nevertheless, by using our prediction method we obtained results with precision above 70%.

  16. An Overview of the Prediction of Protein DNA-Binding Sites

    Directory of Open Access Journals (Sweden)

    Jingna Si

    2015-03-01

    Full Text Available Interactions between proteins and DNA play an important role in many essential biological processes such as DNA replication, transcription, splicing, and repair. The identification of amino acid residues involved in DNA-binding sites is critical for understanding the mechanism of these biological activities. In the last decade, numerous computational approaches have been developed to predict protein DNA-binding sites based on protein sequence and/or structural information, which play an important role in complementing experimental strategies. At this time, approaches can be divided into three categories: sequence-based DNA-binding site prediction, structure-based DNA-binding site prediction, and homology modeling and threading. In this article, we review existing research on computational methods to predict protein DNA-binding sites, which includes data sets, various residue sequence/structural features, machine learning methods for comparison and selection, evaluation methods, performance comparison of different tools, and future directions in protein DNA-binding site prediction. In particular, we detail the meta-analysis of protein DNA-binding sites. We also propose specific implications that are likely to result in novel prediction methods, increased performance, or practical applications.

  17. Predicting DNA-binding sites of proteins based on sequential and 3D structural information.

    Science.gov (United States)

    Li, Bi-Qing; Feng, Kai-Yan; Ding, Juan; Cai, Yu-Dong

    2014-06-01

    Protein-DNA interactions play important roles in many biological processes. To understand the molecular mechanisms of protein-DNA interaction, it is necessary to identify the DNA-binding sites in DNA-binding proteins. In the last decade, computational approaches have been developed to predict protein-DNA-binding sites based solely on protein sequences. In this study, we developed a novel predictor based on support vector machine algorithm coupled with the maximum relevance minimum redundancy method followed by incremental feature selection. We incorporated not only features of physicochemical/biochemical properties, sequence conservation, residual disorder, secondary structure, solvent accessibility, but also five three-dimensional (3D) structural features calculated from PDB data to predict the protein-DNA interaction sites. Feature analysis showed that 3D structural features indeed contributed to the prediction of DNA-binding site and it was demonstrated that the prediction performance was better with 3D structural features than without them. It was also shown via analysis of features from each site that the features of DNA-binding site itself contribute the most to the prediction. Our prediction method may become a useful tool for identifying the DNA-binding sites and the feature analysis described in this paper may provide useful insights for in-depth investigations into the mechanisms of protein-DNA interaction.

  18. A Large-Scale Assessment of Nucleic Acids Binding Site Prediction Programs

    OpenAIRE

    Miao, Zhichao; Westhof, Eric

    2015-01-01

    Computational prediction of nucleic acid binding sites in proteins are necessary to disentangle functional mechanisms in most biological processes and to explore the binding mechanisms. Several strategies have been proposed, but the state-of-the-art approaches display a great diversity in i) the definition of nucleic acid binding sites; ii) the training and test datasets; iii) the algorithmic methods for the prediction strategies; iv) the performance measures and v) the distribution and avail...

  19. A Large-Scale Assessment of Nucleic Acids Binding Site Prediction Programs.

    OpenAIRE

    Zhichao Miao; Eric Westhof

    2015-01-01

    Computational prediction of nucleic acid binding sites in proteins are necessary to disentangle functional mechanisms in most biological processes and to explore the binding mechanisms. Several strategies have been proposed, but the state-of-the-art approaches display a great diversity in i) the definition of nucleic acid binding sites; ii) the training and test datasets; iii) the algorithmic methods for the prediction strategies; iv) the performance measures and v) the distribution and avail...

  20. PROSPER: an integrated feature-based tool for predicting protease substrate cleavage sites.

    Directory of Open Access Journals (Sweden)

    Jiangning Song

    Full Text Available The ability to catalytically cleave protein substrates after synthesis is fundamental for all forms of life. Accordingly, site-specific proteolysis is one of the most important post-translational modifications. The key to understanding the physiological role of a protease is to identify its natural substrate(s. Knowledge of the substrate specificity of a protease can dramatically improve our ability to predict its target protein substrates, but this information must be utilized in an effective manner in order to efficiently identify protein substrates by in silico approaches. To address this problem, we present PROSPER, an integrated feature-based server for in silico identification of protease substrates and their cleavage sites for twenty-four different proteases. PROSPER utilizes established specificity information for these proteases (derived from the MEROPS database with a machine learning approach to predict protease cleavage sites by using different, but complementary sequence and structure characteristics. Features used by PROSPER include local amino acid sequence profile, predicted secondary structure, solvent accessibility and predicted native disorder. Thus, for proteases with known amino acid specificity, PROSPER provides a convenient, pre-prepared tool for use in identifying protein substrates for the enzymes. Systematic prediction analysis for the twenty-four proteases thus far included in the database revealed that the features we have included in the tool strongly improve performance in terms of cleavage site prediction, as evidenced by their contribution to performance improvement in terms of identifying known cleavage sites in substrates for these enzymes. In comparison with two state-of-the-art prediction tools, PoPS and SitePrediction, PROSPER achieves greater accuracy and coverage. To our knowledge, PROSPER is the first comprehensive server capable of predicting cleavage sites of multiple proteases within a single substrate

  1. Using TESS to predict transcription factor binding sites in DNA sequence.

    Science.gov (United States)

    Schug, Jonathan

    2008-03-01

    This unit describes how to use the Transcription Element Search System (TESS). This Web site predicts transcription factor binding sites (TFBS) in DNA sequence using two different kinds of models of sites, strings and positional weight matrices. The binding of transcription factors to DNA is a major part of the control of gene expression. Transcription factors exhibit sequence-specific binding; they form stronger bonds to some DNA sequences than to others. Identification of a good binding site in the promoter for a gene suggests the possibility that the corresponding factor may play a role in the regulation of that gene. However, the sequences transcription factors recognize are typically short and allow for some amount of mismatch. Because of this, binding sites for a factor can typically be found at random every few hundred to a thousand base pairs. TESS has features to help sort through and evaluate the significance of predicted sites.

  2. Phylogeography of the genus Podococcus (Palmae/Arecaceae) in Central African rain forests: Climate stability predicts unique genetic diversity.

    Science.gov (United States)

    Faye, A; Deblauwe, V; Mariac, C; Richard, D; Sonké, B; Vigouroux, Y; Couvreur, T L P

    2016-12-01

    The tropical rain forests of Central Africa contain high levels of species diversity. Paleovegetation or biodiversity patterns suggested successive contraction/expansion phases on this rain forest cover during the last glacial maximum (LGM). Consequently, the hypothesis of the existence of refugia e.g. habitat stability that harbored populations during adverse climatic periods has been proposed. Understory species are tightly associated to forest cover and consequently are ideal markers of forest dynamics. Here, we used two central African rain forest understory species of the palm genus, Podococcus, to assess the role of past climate variation on their distribution and genetic diversity. Species distribution modeling in the present and at the LGM was used to estimate areas of climatic stability. Genetic diversity and phylogeography were estimated by sequencing near complete plastomes for over 120 individuals. Areas of climatic stability were mainly located in mountainous areas like the Monts de Cristal and Monts Doudou in Gabon, but also lowland coastal forests in southeast Cameroon and northeast Gabon. Genetic diversity analyses shows a clear North-South structure of genetic diversity within one species. This divide was estimated to have originated some 500,000years ago. We show that, in Central Africa, high and unique genetic diversity is strongly correlated with inferred areas of climatic stability since the LGM. Our results further highlight the importance of coastal lowland rain forests in Central Africa as harboring not only high species diversity but also important high levels of unique genetic diversity. In the context of strong human pressure on coastal land use and destruction, such unique diversity hotspots need to be considered in future conservation planning.

  3. NetPhosYeast: prediction of protein phosphorylation sites in yeast

    DEFF Research Database (Denmark)

    Ingrell, C.R.; Miller, Martin Lee; Jensen, O.N.

    2007-01-01

    We here present a neural network-based method for the prediction of protein phosphorylation sites in yeast-an important model organism for basic research. Existing protein phosphorylation site predictors are primarily based on mammalian data and show reduced sensitivity on yeast phosphorylation s...

  4. Prediction of protein hydration sites from sequence by modular neural networks

    DEFF Research Database (Denmark)

    Ehrlich, L.; Reczko, M.; Bohr, Henrik

    1998-01-01

    The hydration properties of a protein are important determinants of its structure and function. Here, modular neural networks are employed to predict ordered hydration sites using protein sequence information. First, secondary structure and solvent accessibility are predicted from sequence with t...

  5. Ensemble approach combining multiple methods improves human transcription start site prediction.

    LENUS (Irish Health Repository)

    Dineen, David G

    2010-01-01

    The computational prediction of transcription start sites is an important unsolved problem. Some recent progress has been made, but many promoters, particularly those not associated with CpG islands, are still difficult to locate using current methods. These methods use different features and training sets, along with a variety of machine learning techniques and result in different prediction sets.

  6. NMR studies demonstrate a unique AAB composition and chain register for a heterotrimeric type IV collagen model peptide containing a natural interruption site.

    Science.gov (United States)

    Xiao, Jianxi; Sun, Xiuxia; Madhan, Balaraman; Brodsky, Barbara; Baum, Jean

    2015-10-02

    All non-fibrillar collagens contain interruptions in the (Gly-X-Y)n repeating sequence, such as the more than 20 interruptions found in chains of basement membrane type IV collagen. Two selectively doubly labeled peptides are designed to model a site in type IV collagen with a GVG interruption in the α1(IV) and a corresponding GISLK sequence within the α2(IV) chain. CD and NMR studies on a 2:1 mixture of these two peptides support the formation of a single-component heterotrimer that maintains the one-residue staggering in the triple-helix, has a unique chain register, and contains hydrogen bonds at the interruption site. Formation of hydrogen bonds at interruption sites may provide a driving force for self-assembly and chain register in type IV and other non-fibrillar collagens. This study illustrates the potential role of interruptions in the structure, dynamics, and folding of natural collagen heterotrimers and forms a basis for understanding their biological role.

  7. CaMELS: In silico prediction of calmodulin binding proteins and their binding sites.

    Science.gov (United States)

    Abbasi, Wajid Arshad; Asif, Amina; Andleeb, Saiqa; Minhas, Fayyaz Ul Amir Afsar

    2017-09-01

    Due to Ca(2+) -dependent binding and the sequence diversity of Calmodulin (CaM) binding proteins, identifying CaM interactions and binding sites in the wet-lab is tedious and costly. Therefore, computational methods for this purpose are crucial to the design of such wet-lab experiments. We present an algorithm suite called CaMELS (CalModulin intEraction Learning System) for predicting proteins that interact with CaM as well as their binding sites using sequence information alone. CaMELS offers state of the art accuracy for both CaM interaction and binding site prediction and can aid biologists in studying CaM binding proteins. For CaM interaction prediction, CaMELS uses protein sequence features coupled with a large-margin classifier. CaMELS models the binding site prediction problem using multiple instance machine learning with a custom optimization algorithm which allows more effective learning over imprecisely annotated CaM-binding sites during training. CaMELS has been extensively benchmarked using a variety of data sets, mutagenic studies, proteome-wide Gene Ontology enrichment analyses and protein structures. Our experiments indicate that CaMELS outperforms simple motif-based search and other existing methods for interaction and binding site prediction. We have also found that the whole sequence of a protein, rather than just its binding site, is important for predicting its interaction with CaM. Using the machine learning model in CaMELS, we have identified important features of protein sequences for CaM interaction prediction as well as characteristic amino acid sub-sequences and their relative position for identifying CaM binding sites. Python code for training and evaluating CaMELS together with a webserver implementation is available at the URL: http://faculty.pieas.edu.pk/fayyaz/software.html#camels. © 2017 Wiley Periodicals, Inc.

  8. 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/.

  9. The unique contribution of attitudes toward non-alcoholic drinks to the prediction of adolescents' and young adults' alcohol consumption

    NARCIS (Netherlands)

    Roek, M.A.E.; Spijkerman, R.; Poelen, E.A.P.; Lemmers, A.C.J.; Engels, R.C.M.E.

    2010-01-01

    Attitudes toward alternative behaviors, such as drinking soda instead of alcohol, might contribute to the prediction of young people's drinking behavior. The current study explored the associations between late adolescents' and young adults' attitudes toward alcoholic and non-alcoholic drinks and

  10. The unique contribution of attitudes toward non-alcoholic drinks to the prediction of adolescents' and young adults' alcohol consumption

    NARCIS (Netherlands)

    Roek, M.A.E.; Spijkerman, R.; Poelen, E.A.P.; Lemmers, A.C.J.; Engels, R.C.M.E.

    2010-01-01

    Attitudes toward alternative behaviors, such as drinking soda instead of alcohol, might contribute to the prediction of young people's drinking behavior. The current study explored the associations between late adolescents' and young adults' attitudes toward alcoholic and non-alcoholic drinks and th

  11. Predicting Long-Term Growth in Students' Mathematics Achievement: The Unique Contributions of Motivation and Cognitive Strategies

    Science.gov (United States)

    Murayama, Kou; Pekrun, Reinhard; Lichtenfeld, Stephanie; vom Hofe, Rudolf

    2013-01-01

    This research examined how motivation (perceived control, intrinsic motivation, and extrinsic motivation), cognitive learning strategies (deep and surface strategies), and intelligence jointly predict long-term growth in students' mathematics achievement over 5 years. Using longitudinal data from six annual waves (Grades 5 through 10;…

  12. Predicting Long-Term Growth in Students' Mathematics Achievement: The Unique Contributions of Motivation and Cognitive Strategies

    Science.gov (United States)

    Murayama, Kou; Pekrun, Reinhard; Lichtenfeld, Stephanie; vom Hofe, Rudolf

    2013-01-01

    This research examined how motivation (perceived control, intrinsic motivation, and extrinsic motivation), cognitive learning strategies (deep and surface strategies), and intelligence jointly predict long-term growth in students' mathematics achievement over 5 years. Using longitudinal data from six annual waves (Grades 5 through 10;…

  13. Using site-specific soil samples as a substitution for improved hydrological and nonpoint source predictions.

    Science.gov (United States)

    Chen, Lei; Wang, Guobo; Zhong, Yucen; Zhao, Xin; Shen, Zhenyao

    2016-08-01

    Soil databases are one of the most important inputs for watershed models, and the quality of soil properties affects how well a model performs. The objectives of this study were to (1) quantify the sensitivity of model outputs to soil properties and to (2) use site-specific soil properties as a substitution for more accurate hydrological and nonpoint source (H/NPS) predictions. Soil samples were collected from a typical mountainous watershed in China, and the impacts of soil sample parameters on H/NPS predictions were quantified using the Soil and Water Assessment Tool (SWAT). The most sensitive parameters related to predicting flow, sediment, and total phosphorus (TP) mainly were the soil hydrological, the channel erosion processes, and the initial soil chemical environment, respectively. When the site-specific soil properties were used, the uncertainties (coefficient of variation) related to predicting the hydrology, sediment and TP decreased by 75∼80 %, 75∼84 %, and 46∼61 %, respectively. Based on changes in the Nash-Sutcliff coefficient, the model performance improved by 4.9 and 19.45 % for the hydrological and sediment model, accordingly. However, site-specific soil properties did not contribute to better TP predictions because of the high spatial variability of the soil P concentrations across the large watershed. Thus, although site-specific soil samples can be used to obtain more accurate H/NPS predictions, more sampling sites are required to apply this method in large watersheds.

  14. Prediction of post-translational modification sites using multiple kernel support vector machine

    Directory of Open Access Journals (Sweden)

    BingHua Wang

    2017-04-01

    Full Text Available Protein post-translational modification (PTM is an important mechanism that is involved in the regulation of protein function. Considering the high-cost and labor-intensive of experimental identification, many computational prediction methods are currently available for the prediction of PTM sites by using protein local sequence information in the context of conserved motif. Here we proposed a novel computational method by using the combination of multiple kernel support vector machines (SVM for predicting PTM sites including phosphorylation, O-linked glycosylation, acetylation, sulfation and nitration. To largely make use of local sequence information and site-modification relationships, we developed a local sequence kernel and Gaussian interaction profile kernel, respectively. Multiple kernels were further combined to train SVM for efficiently leveraging kernel information to boost predictive performance. We compared the proposed method with existing PTM prediction methods. The experimental results revealed that the proposed method performed comparable or better performance than the existing prediction methods, suggesting the feasibility of the developed kernels and the usefulness of the proposed method in PTM sites prediction.

  15. Real-time seismic intensity prediction using frequency-dependent site amplification factors

    Science.gov (United States)

    Ogiso, Masashi; Aoki, Shigeki; Hoshiba, Mitsuyuki

    2016-05-01

    A promising approach for the next generation of earthquake early warning system is based on predicting ground motion directly from observed ground motion, without any information of hypocenter. In this study, we predicted seismic intensity at the target stations from the observed ground motion at adjacent stations, employing two different methods of correction for site amplification factors. The first method was frequency-dependent correction prediction, in which we used a digital causal filter to correct the site amplification for the observed waveform in the time domain. The second method was scalar correction, in which we used average differences in seismic intensity between two stations for the site amplification correction. Results from thousands of station pairs that covered almost all of Japan showed that seismic intensity prediction with frequency-dependent correction prediction was more accurate than prediction with scalar correction. Frequency-dependent correction for site amplification in the time domain may lead to more accurate prediction of ground motion in real time.

  16. Predicting Polymerase Ⅱ Core Promoters by Cooperating Transcription Factor Binding Sites in Eukaryotic Genes

    Institute of Scientific and Technical Information of China (English)

    Xiao-Tu MA; Min-Ping QIAN; Hai-Xu TANG

    2004-01-01

    Several discriminate functions for predicting core promoters that based on the potential cooperation between transcription factor binding sites (TFBSs) are discussed. It is demonstrated that the promoter predicting accuracy is improved when the cooperation among TFBSs is taken into consideration.The core promoter region of a newly discovered gene CKLFSF1 is predicted to locate more than 1.5 kb far away from the 5′ end of the transcript and in the last intron of its upstream gene, which is experimentally confirmed later. The core promoters of 3402 human RefSeq sequences, obtained by extending the mRNAs in human genome sequences, are predicted by our algorithm, and there are about 60% of the predicted core promoters locating within the ± 500 bp region relative to the annotated transcription start site.

  17. Cross-prediction of the groundwater chemistry at the SKB sites in Sweden. Pilot study

    Energy Technology Data Exchange (ETDEWEB)

    Skaarman, C.; Laaksoharju, M. [Intera KB (Sweden)

    1997-08-01

    The possibility to perform a large scale prediction throughout Sweden was tested. The aim of the work was: to collect data and create a groundwater database for current and future use; to see if there is any correlation between data at different sites; to perform a modelling where the groundwater composition at different regions in Sweden is predicted. The outcome of the predictions were compared with the measured data at different sites. The results show that it is possible but more work needs to be done to improve the prediction models. More measurements at depth are needed to enable the use of 3D models. It is also important to include hydrogeological parameters in the groundwater chemical prediction models that are used. 8 refs, 115 figs.

  18. Computational Prediction of CRISPR/Cas9 Target Sites Reveals Potential Off-Target Risks in Human and Mouse.

    Science.gov (United States)

    Wang, Qingbo; Ui-Tei, Kumiko

    2017-01-01

    The clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated (Cas) system is a prominent genome engineering technology. In the CRISPR/Cas system, the RNA-guided endonuclease Cas protein introduces a DNA double-stranded break at the genome position recognized by a guide RNA (gRNA) based on complementary base-pairing of about 20-nucleotides in length. The 8- or 12-mer gRNA sequence in the proximal region is especially important for target recognition, and the genes with sequence complementarity to such regions are often disrupted. To carry out target site-specific genome editing, we released the CRISPRdirect ( http://crispr.dbcls.jp /) website. This website allows us to select target site-specific gRNA sequences by performing exhaustive searches against entire genomic sequences. In this study, target site-specific gRNA sequences were designed for human, mouse, Drosophila melanogaster, and Caenorhabditis elegans. The calculation results revealed that at least five gRNA sequences, each of them having only one perfectly complementary site in the whole genome, could be designed for more than 95% of genes, regardless of the organism. Next, among those gRNAs, we selected gRNAs that did not have any other complementary site to the unique 12-mer proximal sequences to avoid possible off-target effects. This computational prediction revealed that target site-specific gRNAs are selectable for the majority of genes in D. melanogaster and C. elegans. However, for >50% of genes in humans and mice, there are no target sites without possible off-target effects.

  19. Estimation of the Aral Sea state predictability based on the open data sources and the unique field observations

    Science.gov (United States)

    Izhitskiy, Alexander; Ayzel, Georgy; Zavialov, Peter; Kurbaniyazov, Abilgazi

    2016-04-01

    The Aral Sea, formerly one of the four largest lakes in the world, has lost over 90% of its volume during the dramatical dessication mainly caused by the severe alteration of water budget of the basin. Shrinkage of the Aral Sea resulted in profound changes of the lake's ecosystem, that became a subject for a number of publications based on a wide range of methods such as field observations, remote sensing data analysis and numerical modeling. However, by the early 21th century, the number of field studies decreased significantly due to almost complete cessation of navigation and displacement of the Aral's shoreline far away from roads and other infrastructure. Thus, only a small amount of field data (salinity, temperature, etc.) for different regions of the lake is available for the last two decades. On the other hand, a set of the open data sources (sea level variability, atmospheric reanalysis) were developed for the region. The main idea of the presented study is to estimate the possibility of prediction of the Aral Sea state using coupled system of basic geoanalysis tools, numerical modeling of hydrological cycle (both for sea and land-surface interactions with atmosphere) and state-of-art machine learning techniques. Firstly, available in situ data, obtained in the Aral Sea by Shirshov Institute and other researchers, are concerned as the "base points of state" for each year within the studied period. Secondly, consistent patterns in the interannual variability of all other available parameters, taken from the open data sources and numerical modeling predictions, are founded out. As a result, such an approach allows predicting the future state of sea basing on the possible climatic scenario.

  20. MBSTAR: multiple instance learning for predicting specific functional binding sites in microRNA targets

    Science.gov (United States)

    Bandyopadhyay, Sanghamitra; Ghosh, Dip; Mitra, Ramkrishna; Zhao, Zhongming

    2015-01-01

    MicroRNA (miRNA) regulates gene expression by binding to specific sites in the 3'untranslated regions of its target genes. Machine learning based miRNA target prediction algorithms first extract a set of features from potential binding sites (PBSs) in the mRNA and then train a classifier to distinguish targets from non-targets. However, they do not consider whether the PBSs are functional or not, and consequently result in high false positive rates. This substantially affects the follow up functional validation by experiments. We present a novel machine learning based approach, MBSTAR (Multiple instance learning of Binding Sites of miRNA TARgets), for accurate prediction of true or functional miRNA binding sites. Multiple instance learning framework is adopted to handle the lack of information about the actual binding sites in the target mRNAs. Biologically validated 9531 interacting and 973 non-interacting miRNA-mRNA pairs are identified from Tarbase 6.0 and confirmed with PAR-CLIP dataset. It is found that MBSTAR achieves the highest number of binding sites overlapping with PAR-CLIP with maximum F-Score of 0.337. Compared to the other methods, MBSTAR also predicts target mRNAs with highest accuracy. The tool and genome wide predictions are available at http://www.isical.ac.in/~bioinfo_miu/MBStar30.htm.

  1. Fraction magnitude understanding and its unique role in predicting general mathematics achievement at two early stages of fraction instruction.

    Science.gov (United States)

    Liu, Yingyi

    2017-09-08

    Prior studies on fraction magnitude understanding focused mainly on students with relatively sufficient formal instruction on fractions whose fraction magnitude understanding is relatively mature. This study fills a research gap by investigating fraction magnitude understanding in the early stages of fraction instruction. It extends previous findings to children with limited and primary formal fraction instruction. Thirty-five fourth graders with limited fraction instruction and forty fourth graders with primary fraction instruction were recruited from a Chinese primary school. Children's fraction magnitude understanding was assessed with a fraction number line estimation task. Approximate number system (ANS) acuity was assessed with a dot discrimination task. Whole number knowledge was assessed with a whole number line estimation task. General reading and mathematics achievements were collected concurrently and 1 year later. In children with limited fraction instruction, fraction representation was linear and fraction magnitude understanding was concurrently related to both ANS and whole number knowledge. In children with primary fraction instruction, fraction magnitude understanding appeared to (marginally) significantly predict general mathematics achievement 1 year later. Fraction magnitude understanding emerged early during formal instruction of fractions. ANS and whole number knowledge were related to fraction magnitude understanding when children first began to learn about fractions in school. The predictive value of fraction magnitude understanding is likely constrained by its sophistication level. © 2017 The British Psychological Society.

  2. Spatial distribution of predicted transcription factor binding sites in Drosophila ChIP peaks.

    Science.gov (United States)

    Pettie, Kade P; Dresch, Jacqueline M; Drewell, Robert A

    2016-08-01

    In the development of the Drosophila embryo, gene expression is directed by the sequence-specific interactions of a large network of protein transcription factors (TFs) and DNA cis-regulatory binding sites. Once the identity of the typically 8-10bp binding sites for any given TF has been determined by one of several experimental procedures, the sequences can be represented in a position weight matrix (PWM) and used to predict the location of additional TF binding sites elsewhere in the genome. Often, alignments of large (>200bp) genomic fragments that have been experimentally determined to bind the TF of interest in Chromatin Immunoprecipitation (ChIP) studies are trimmed under the assumption that the majority of the binding sites are located near the center of all the aligned fragments. In this study, ChIP/chip datasets are analyzed using the corresponding PWMs for the well-studied TFs; CAUDAL, HUNCHBACK, KNIRPS and KRUPPEL, to determine the distribution of predicted binding sites. All four TFs are critical regulators of gene expression along the anterio-posterior axis in early Drosophila development. For all four TFs, the ChIP peaks contain multiple binding sites that are broadly distributed across the genomic region represented by the peak, regardless of the prediction stringency criteria used. This result suggests that ChIP peak trimming may exclude functional binding sites from subsequent analyses.

  3. Gratitude uniquely predicts lower depression in chronic illness populations: A longitudinal study of inflammatory bowel disease and arthritis.

    Science.gov (United States)

    Sirois, Fuschia M; Wood, Alex M

    2017-02-01

    Although gratitude has been identified as a key clinically relevant trait for improving well-being, it is understudied within medical populations. The current study addressed this gap and extended previous and limited cross-sectional research by examining the longitudinal associations of gratitude to depression in 2 chronic illness samples, arthritis and inflammatory bowel disease (IBD). Two chronic illness samples, arthritis (N = 423) and IBD (N = 427), completed online surveys at Time 1 (T1). One hundred sixty-three people with arthritis and 144 people with IBD completed the 6-month follow-up survey (T2). Depression, gratitude, illness cognitions, perceived stress, social support, and disease-related variables were assessed at T1 and T2. At T2, 57.2% of the arthritis sample and 53.4% of the IBD sample met the cut off scores for significant depression. T1 gratitude was negatively associated with depressive symptoms at T1 and T2 in both samples (rs from -.43 to -.50). Regression analyses revealed that T1 gratitude remained a significant and unique predictor of lower T2 depression after controlling for T1 depression, relevant demographic variables, illness cognitions, changes in illness-relevant variables, and another positive psychological construct, thriving, in both samples. As the first investigation of the longitudinal associations of gratitude to psychological well-being in the context of chronic illness, the current study provides important evidence for the relevance of gratitude for health-related clinical populations. Further intervention-based research is warranted to more fully understand the potential benefits of gratitude for adjustment to chronic illness. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  4. Predicting long-term growth in students' mathematics achievement: the unique contributions of motivation and cognitive strategies.

    Science.gov (United States)

    Murayama, Kou; Pekrun, Reinhard; Lichtenfeld, Stephanie; Vom Hofe, Rudolf

    2013-01-01

    This research examined how motivation (perceived control, intrinsic motivation, and extrinsic motivation), cognitive learning strategies (deep and surface strategies), and intelligence jointly predict long-term growth in students' mathematics achievement over 5 years. Using longitudinal data from six annual waves (Grades 5 through 10; Mage  = 11.7 years at baseline; N = 3,530), latent growth curve modeling was employed to analyze growth in achievement. Results showed that the initial level of achievement was strongly related to intelligence, with motivation and cognitive strategies explaining additional variance. In contrast, intelligence had no relation with the growth of achievement over years, whereas motivation and learning strategies were predictors of growth. These findings highlight the importance of motivation and learning strategies in facilitating adolescents' development of mathematical competencies.

  5. Better estimation of protein-DNA interaction parameters improve prediction of functional sites

    Directory of Open Access Journals (Sweden)

    O'Flanagan Ruadhan A

    2008-12-01

    Full Text Available Abstract Background Characterizing transcription factor binding motifs is a common bioinformatics task. For transcription factors with variable binding sites, we need to get many suboptimal binding sites in our training dataset to get accurate estimates of free energy penalties for deviating from the consensus DNA sequence. One procedure to do that involves a modified SELEX (Systematic Evolution of Ligands by Exponential Enrichment method designed to produce many such sequences. Results We analyzed low stringency SELEX data for E. coli Catabolic Activator Protein (CAP, and we show here that appropriate quantitative analysis improves our ability to predict in vitro affinity. To obtain large number of sequences required for this analysis we used a SELEX SAGE protocol developed by Roulet et al. The sequences obtained from here were subjected to bioinformatic analysis. The resulting bioinformatic model characterizes the sequence specificity of the protein more accurately than those sequence specificities predicted from previous analysis just by using a few known binding sites available in the literature. The consequences of this increase in accuracy for prediction of in vivo binding sites (and especially functional ones in the E. coli genome are also discussed. We measured the dissociation constants of several putative CAP binding sites by EMSA (Electrophoretic Mobility Shift Assay and compared the affinities to the bioinformatics scores provided by methods like the weight matrix method and QPMEME (Quadratic Programming Method of Energy Matrix Estimation trained on known binding sites as well as on the new sites from SELEX SAGE data. We also checked predicted genome sites for conservation in the related species S. typhimurium. We found that bioinformatics scores based on SELEX SAGE data does better in terms of prediction of physical binding energies as well as in detecting functional sites. Conclusion We think that training binding site detection

  6. Microbial Communities and Their Predicted Metabolic Functions in Growth Laminae of a Unique Large Conical Mat from Lake Untersee, East Antarctica

    Directory of Open Access Journals (Sweden)

    Hyunmin Koo

    2017-08-01

    Full Text Available In this study, we report the distribution of microbial taxa and their predicted metabolic functions observed in the top (U1, middle (U2, and inner (U3 decadal growth laminae of a unique large conical microbial mat from perennially ice-covered Lake Untersee of East Antarctica, using NextGen sequencing of the 16S rRNA gene and bioinformatics tools. The results showed that the U1 lamina was dominated by cyanobacteria, specifically Phormidium sp., Leptolyngbya sp., and Pseudanabaena sp. The U2 and U3 laminae had high abundances of Actinobacteria, Verrucomicrobia, Proteobacteria, and Bacteroidetes. Closely related taxa within each abundant bacterial taxon found in each lamina were further differentiated at the highest taxonomic resolution using the oligotyping method. PICRUSt analysis, which determines predicted KEGG functional categories from the gene contents and abundances among microbial communities, revealed a high number of sequences belonging to carbon fixation, energy metabolism, cyanophycin, chlorophyll, and photosynthesis proteins in the U1 lamina. The functional predictions of the microbial communities in U2 and U3 represented signal transduction, membrane transport, zinc transport and amino acid-, carbohydrate-, and arsenic- metabolisms. The Nearest Sequenced Taxon Index (NSTI values processed through PICRUSt were 0.10, 0.13, and 0.11 for U1, U2, and U3 laminae, respectively. These values indicated a close correspondence with the reference microbial genome database, implying high confidence in the predicted metabolic functions of the microbial communities in each lamina. The distribution of microbial taxa observed in each lamina and their predicted metabolic functions provides additional insight into the complex microbial ecosystem at Lake Untersee, and lays the foundation for studies that will enhance our understanding of the mechanisms responsible for the formation of these unique mat structures and their evolutionary significance.

  7. Predicting evolutionary site variability from structure in viral proteins: buriedness, flexibility, and design

    CERN Document Server

    Shahmoradi, Amir; Spielman, Stephanie J; Jackson, Eleisha L; Dawson, Eric T; Meyer, Austin G; Wilke, Claus O

    2014-01-01

    Several recent works have shown that protein structure can predict site-specific evolutionary sequence variation. In particular, sites that are buried and/or have many contacts with other sites in a structure have been shown to evolve more slowly, on average, than surface sites with few contacts. Here, we present a comprehensive study of the extent to which numerous structural properties can predict sequence variation. The structural properties we considered include buriedness (relative solvent accessibility and contact number), structural flexibility (B factors, root-mean-square fluctuations, and variation in dihedral angles), and variability in designed structures. We obtained structural flexibility measures both from molecular dynamics simulations performed on 9 non-homologous viral protein structures and from variation in homologous variants of those proteins, where available. We obtained measures of variability in designed structures from flexible-backbone design in the Rosetta software. We found that mo...

  8. LRR conservation mapping to predict functional sites within protein leucine-rich repeat domains.

    Directory of Open Access Journals (Sweden)

    Laura Helft

    Full Text Available Computational prediction of protein functional sites can be a critical first step for analysis of large or complex proteins. Contemporary methods often require several homologous sequences and/or a known protein structure, but these resources are not available for many proteins. Leucine-rich repeats (LRRs are ligand interaction domains found in numerous proteins across all taxonomic kingdoms, including immune system receptors in plants and animals. We devised Repeat Conservation Mapping (RCM, a computational method that predicts functional sites of LRR domains. RCM utilizes two or more homologous sequences and a generic representation of the LRR structure to identify conserved or diversified patches of amino acids on the predicted surface of the LRR. RCM was validated using solved LRR+ligand structures from multiple taxa, identifying ligand interaction sites. RCM was then used for de novo dissection of two plant microbe-associated molecular pattern (MAMP receptors, EF-TU RECEPTOR (EFR and FLAGELLIN-SENSING 2 (FLS2. In vivo testing of Arabidopsis thaliana EFR and FLS2 receptors mutagenized at sites identified by RCM demonstrated previously unknown functional sites. The RCM predictions for EFR, FLS2 and a third plant LRR protein, PGIP, compared favorably to predictions from ODA (optimal docking area, Consurf, and PAML (positive selection analyses, but RCM also made valid functional site predictions not available from these other bioinformatic approaches. RCM analyses can be conducted with any LRR-containing proteins at www.plantpath.wisc.edu/RCM, and the approach should be modifiable for use with other types of repeat protein domains.

  9. Computational predictions provide insights into the biology of TAL effector target sites.

    Science.gov (United States)

    Grau, Jan; Wolf, Annett; Reschke, Maik; Bonas, Ulla; Posch, Stefan; Boch, Jens

    2013-01-01

    Transcription activator-like (TAL) effectors are injected into host plant cells by Xanthomonas bacteria to function as transcriptional activators for the benefit of the pathogen. The DNA binding domain of TAL effectors is composed of conserved amino acid repeat structures containing repeat-variable diresidues (RVDs) that determine DNA binding specificity. In this paper, we present TALgetter, a new approach for predicting TAL effector target sites based on a statistical model. In contrast to previous approaches, the parameters of TALgetter are estimated from training data computationally. We demonstrate that TALgetter successfully predicts known TAL effector target sites and often yields a greater number of predictions that are consistent with up-regulation in gene expression microarrays than an existing approach, Target Finder of the TALE-NT suite. We study the binding specificities estimated by TALgetter and approve that different RVDs are differently important for transcriptional activation. In subsequent studies, the predictions of TALgetter indicate a previously unreported positional preference of TAL effector target sites relative to the transcription start site. In addition, several TAL effectors are predicted to bind to the TATA-box, which might constitute one general mode of transcriptional activation by TAL effectors. Scrutinizing the predicted target sites of TALgetter, we propose several novel TAL effector virulence targets in rice and sweet orange. TAL-mediated induction of the candidates is supported by gene expression microarrays. Validity of these targets is also supported by functional analogy to known TAL effector targets, by an over-representation of TAL effector targets with similar function, or by a biological function related to pathogen infection. Hence, these predicted TAL effector virulence targets are promising candidates for studying the virulence function of TAL effectors. TALgetter is implemented as part of the open-source Java library

  10. Computational predictions provide insights into the biology of TAL effector target sites.

    Directory of Open Access Journals (Sweden)

    Jan Grau

    Full Text Available Transcription activator-like (TAL effectors are injected into host plant cells by Xanthomonas bacteria to function as transcriptional activators for the benefit of the pathogen. The DNA binding domain of TAL effectors is composed of conserved amino acid repeat structures containing repeat-variable diresidues (RVDs that determine DNA binding specificity. In this paper, we present TALgetter, a new approach for predicting TAL effector target sites based on a statistical model. In contrast to previous approaches, the parameters of TALgetter are estimated from training data computationally. We demonstrate that TALgetter successfully predicts known TAL effector target sites and often yields a greater number of predictions that are consistent with up-regulation in gene expression microarrays than an existing approach, Target Finder of the TALE-NT suite. We study the binding specificities estimated by TALgetter and approve that different RVDs are differently important for transcriptional activation. In subsequent studies, the predictions of TALgetter indicate a previously unreported positional preference of TAL effector target sites relative to the transcription start site. In addition, several TAL effectors are predicted to bind to the TATA-box, which might constitute one general mode of transcriptional activation by TAL effectors. Scrutinizing the predicted target sites of TALgetter, we propose several novel TAL effector virulence targets in rice and sweet orange. TAL-mediated induction of the candidates is supported by gene expression microarrays. Validity of these targets is also supported by functional analogy to known TAL effector targets, by an over-representation of TAL effector targets with similar function, or by a biological function related to pathogen infection. Hence, these predicted TAL effector virulence targets are promising candidates for studying the virulence function of TAL effectors. TALgetter is implemented as part of the open

  11. Prediction of protein binding sites in protein structures using hidden Markov support vector machine

    Directory of Open Access Journals (Sweden)

    Lin Lei

    2009-11-01

    Full Text Available Abstract Background Predicting the binding sites between two interacting proteins provides important clues to the function of a protein. Recent research on protein binding site prediction has been mainly based on widely known machine learning techniques, such as artificial neural networks, support vector machines, conditional random field, etc. However, the prediction performance is still too low to be used in practice. It is necessary to explore new algorithms, theories and features to further improve the performance. Results In this study, we introduce a novel machine learning model hidden Markov support vector machine for protein binding site prediction. The model treats the protein binding site prediction as a sequential labelling task based on the maximum margin criterion. Common features derived from protein sequences and structures, including protein sequence profile and residue accessible surface area, are used to train hidden Markov support vector machine. When tested on six data sets, the method based on hidden Markov support vector machine shows better performance than some state-of-the-art methods, including artificial neural networks, support vector machines and conditional random field. Furthermore, its running time is several orders of magnitude shorter than that of the compared methods. Conclusion The improved prediction performance and computational efficiency of the method based on hidden Markov support vector machine can be attributed to the following three factors. Firstly, the relation between labels of neighbouring residues is useful for protein binding site prediction. Secondly, the kernel trick is very advantageous to this field. Thirdly, the complexity of the training step for hidden Markov support vector machine is linear with the number of training samples by using the cutting-plane algorithm.

  12. [Spatial distribution prediction of surface soil Pb in a battery contaminated site].

    Science.gov (United States)

    Liu, Geng; Niu, Jun-Jie; Zhang, Chao; Zhao, Xin; Guo, Guan-Lin

    2014-12-01

    In order to enhance the reliability of risk estimation and to improve the accuracy of pollution scope determination in a battery contaminated site with the soil characteristic pollutant Pb, four spatial interpolation models, including Combination Prediction Model (OK(LG) + TIN), kriging model (OK(BC)), Inverse Distance Weighting model (IDW), and Spline model were employed to compare their effects on the spatial distribution and pollution assessment of soil Pb. The results showed that Pb concentration varied significantly and the data was severely skewed. The variation coefficient of the site was higher in the local region. OK(LG) + TIN was found to be more accurate than the other three models in predicting the actual pollution situations of the contaminated site. The prediction accuracy of other models was lower, due to the effect of the principle of different models and datum feature. The interpolation results of OK(BC), IDW and Spline could not reflect the detailed characteristics of seriously contaminated areas, and were not suitable for mapping and spatial distribution prediction of soil Pb in this site. This study gives great contributions and provides useful references for defining the remediation boundary and making remediation decision of contaminated sites.

  13. GPS-SNO: computational prediction of protein S-nitrosylation sites with a modified GPS algorithm.

    Directory of Open Access Journals (Sweden)

    Yu Xue

    Full Text Available As one of the most important and ubiquitous post-translational modifications (PTMs of proteins, S-nitrosylation plays important roles in a variety of biological processes, including the regulation of cellular dynamics and plasticity. Identification of S-nitrosylated substrates with their exact sites is crucial for understanding the molecular mechanisms of S-nitrosylation. In contrast with labor-intensive and time-consuming experimental approaches, prediction of S-nitrosylation sites using computational methods could provide convenience and increased speed. In this work, we developed a novel software of GPS-SNO 1.0 for the prediction of S-nitrosylation sites. We greatly improved our previously developed algorithm and released the GPS 3.0 algorithm for GPS-SNO. By comparison, the prediction performance of GPS 3.0 algorithm was better than other methods, with an accuracy of 75.80%, a sensitivity of 53.57% and a specificity of 80.14%. As an application of GPS-SNO 1.0, we predicted putative S-nitrosylation sites for hundreds of potentially S-nitrosylated substrates for which the exact S-nitrosylation sites had not been experimentally determined. In this regard, GPS-SNO 1.0 should prove to be a useful tool for experimentalists. The online service and local packages of GPS-SNO were implemented in JAVA and are freely available at: http://sno.biocuckoo.org/.

  14. Perceived mother and father acceptance-rejection predict four unique aspects of child adjustment across nine countries

    Science.gov (United States)

    Putnick, Diane L.; Bornstein, Marc H.; Lansford, Jennifer E.; Malone, Patrick S.; Pastorelli, Concetta; Skinner, Ann T.; Sorbring, Emma; Tapanya, Sombat; Tirado, Liliana Maria Uribe; Zelli, Arnaldo; Alampay, Liane Peña; Al-Hassan, Suha M.; Bacchini, Dario; Bombi, Anna Silvia; Chang, Lei; Deater-Deckard, Kirby; Di Giunta, Laura; Dodge, Kenneth A.; Oburu, Paul

    2014-01-01

    Background It is generally believed that parental rejection of children leads to child maladaptation. However, the specific effects of perceived parental acceptance-rejection on diverse domains of child adjustment and development have been incompletely documented, and whether these effects hold across diverse populations and for mothers and fathers are still open questions. Methods This study assessed children's perceptions of mother and father acceptance-rejection in 1247 families from China, Colombia, Italy, Jordan, Kenya, the Philippines, Sweden, Thailand, and the United States as antecedent predictors of later internalizing and externalizing behavior problems, school performance, prosocial behavior, and social competence. Results Higher perceived parental rejection predicted increases in internalizing and externalizing behavior problems and decreases in school performance and prosocial behavior across three years controlling for within-wave relations, stability across waves, and parental age, education, and social desirability bias. Patterns of relations were similar across mothers and fathers and, with a few exceptions, all 9 countries. Conclusions Children's perceptions of maternal and paternal acceptance-rejection have small but nearly universal effects on multiple aspects of their adjustment and development regardless of the family's country of origin. PMID:25492267

  15. Prediction of Signal Peptide Cleavage Sites with Subsite-Coupled and Template Matching Fusion Algorithm.

    Science.gov (United States)

    Zhang, Shao-Wu; Zhang, Ting-He; Zhang, Jun-Nan; Huang, Yufei

    2014-03-01

    Fast and effective prediction of signal peptides (SP) and their cleavage sites is of great importance in computational biology. The approaches developed to predict signal peptide can be roughly divided into machine learning based, and sliding windows based. In order to further increase the prediction accuracy and coverage of organism for SP cleavage sites, we propose a novel method for predicting SP cleavage sites called Signal-CTF that utilizes machine learning and sliding windows, and is designed for N-termial secretory proteins in a large variety of organisms including human, animal, plant, virus, bacteria, fungi and archaea. Signal-CTF consists of three distinct elements: (1) a subsite-coupled and regularization function with a scaled window of fixed width that selects a set of candidates of possible secretion-cleavable segment for a query secretory protein; (2) a sum fusion system that integrates the outcomes from aligning the cleavage site template sequence with each of the aforementioned candidates in a scaled window of fixed width to determine the best candidate cleavage sites for the query secretory protein; (3) a voting system that identifies the ultimate signal peptide cleavage site among all possible results derived from using scaled windows of different width. When compared with Signal-3L and SignalP 4.0 predictors, the prediction accuracy of Signal-CTF is 4-12 %, 10-25 % higher than that of Signal-3L for human, animal and eukaryote, and SignalP 4.0 for eukaryota, Gram-positive bacteria and Gram-negative bacteria, respectively. Comparing with PRED-SIGNAL and SignalP 4.0 predictors on the 32 archaea secretory proteins of used in Bagos's paper, the prediction accuracy of Signal-CTF is 12.5 %, 25 % higher than that of PRED-SIGNAL and SignalP 4.0, respectively. The predicting results of several long signal peptides show that the Signal-CTF can better predict cleavage sites for long signal peptides than SignalP, Phobius, Philius, SPOCTOPUS, Signal

  16. Predicting Ligand Binding Sites on Protein Surfaces by 3-Dimensional Probability Density Distributions of Interacting Atoms

    Science.gov (United States)

    Jian, Jhih-Wei; Elumalai, Pavadai; Pitti, Thejkiran; Wu, Chih Yuan; Tsai, Keng-Chang; Chang, Jeng-Yih; Peng, Hung-Pin; Yang, An-Suei

    2016-01-01

    Predicting ligand binding sites (LBSs) on protein structures, which are obtained either from experimental or computational methods, is a useful first step in functional annotation or structure-based drug design for the protein structures. In this work, the structure-based machine learning algorithm ISMBLab-LIG was developed to predict LBSs on protein surfaces with input attributes derived from the three-dimensional probability density maps of interacting atoms, which were reconstructed on the query protein surfaces and were relatively insensitive to local conformational variations of the tentative ligand binding sites. The prediction accuracy of the ISMBLab-LIG predictors is comparable to that of the best LBS predictors benchmarked on several well-established testing datasets. More importantly, the ISMBLab-LIG algorithm has substantial tolerance to the prediction uncertainties of computationally derived protein structure models. As such, the method is particularly useful for predicting LBSs not only on experimental protein structures without known LBS templates in the database but also on computationally predicted model protein structures with structural uncertainties in the tentative ligand binding sites. PMID:27513851

  17. Timing of initial arrival at the breeding site predicts age at first reproduction in a long-lived migratory bird.

    Science.gov (United States)

    Becker, Peter H; Dittmann, Tobias; Ludwigs, Jan-Dieter; Limmer, Bente; Ludwig, Sonja C; Bauch, Christina; Braasch, Alexander; Wendeln, Helmut

    2008-08-26

    In long-lived vertebrates, individuals generally visit potential breeding areas or populations during one or more seasons before reproducing for the first time. During these years of prospecting, they select a future breeding site, colony, or mate and improve various skills and their physical condition to meet the requirements of reproduction. One precondition of successful reproduction is arrival in time on the breeding grounds. Here, we study the intricate links among the date of initial spring arrival, body mass, sex, and the age of first breeding in the common tern Sterna hirundo, a long-lived migratory colonial seabird. The study is based on a unique, individual-based, long-term dataset of sexed birds, marked with transponders, which allow recording their individual arrival, overall attendance, and clutch initiation remotely and automatically year by year over the entire lifetime at the natal colony site. We show that the seasonal date of initial arrival at the breeding grounds predicts the individual age at first reproduction, which mostly occurs years later. Late first-time arrivals remain delayed birds throughout subsequent years. Our findings reveal that timing of arrival at the site of reproduction and timing of reproduction itself are coherent parameters of individual quality, which are linked with the prospects of the breeding career and may have consequences for fitness.

  18. Enzyme-like specificity in zeolites: a unique site position in mordenite for selective carbonylation of methanol and dimethyl ether with CO.

    Science.gov (United States)

    Boronat, Mercedes; Martínez-Sánchez, Cristina; Law, David; Corma, Avelino

    2008-12-03

    The mechanism of methanol carbonylation at different positions of zeolite MOR is investigated by quantum-chemical methods in order to discover which are the active sites that can selectively catalyze the desired reaction. It is shown that when methanol carbonylation competes with hydrocarbon formation, the first reaction occurs preferentially within 8MR channels. However, the unique selectivity for the carbonylation of methanol and dimethyl ether in mordenite is not only due to the size of the 8MR channel: neither process occurs equally at the two T3-O31 and T3-O33 positions. We show that only the T3-O33 positions are selective and that this selectivity is due to the unusual orientation of the methoxy group in relation to the 8MR channel (parallel to the cylinder axis). Only in this situation does the transition state for the attack of CO fit perfectly in the 8MR channel, while the reaction with methanol or DME is sterically impeded. This result explains why T3-O31, while also located in the 8MR channel of mordenite, is not as selective as the T3-O33 position and why ferrierite, although it contains 8MR channels, is less selective than mordenite. The competing effect of water is explained at the molecular level, and the molecular microkinetic reaction model has been established.

  19. Protein-binding site prediction based on three-dimensional protein modeling.

    Science.gov (United States)

    Oh, Mina; Joo, Keehyoung; Lee, Jooyoung

    2009-01-01

    Structural information of a protein can guide one to understand the function of the protein, and ligand binding is one of the major biochemical functions of proteins. We have applied a two-stage template-based ligand binding site prediction method to CASP8 targets and achieved high quality results with accuracy/coverage = 70/80 (LEE). First, templates are used for protein structure modeling and then for binding site prediction by structural clustering of ligand-containing templates to the predicted protein model. Remarkably, the results are only a few percent worse than those one can obtain from native structures, which were available only after the prediction. Prediction was performed without knowing identity of ligands, and consequently, in many cases the ligand molecules used for prediction were different from the actual ligands, and yet we find that the prediction was quite successful. The current approach can be easily combined with experiments to investigate protein activities in a systematic way. Copyright 2009 Wiley-Liss, Inc.

  20. Analysis and prediction of gene splice sites in four Aspergillus genomes

    DEFF Research Database (Denmark)

    Wang, Kai; Ussery, David; Brunak, Søren

    2009-01-01

    , splice site prediction program called NetAspGene, for the genus Aspergillus. Gene sequences from Aspergillus fumigatus, the most common mould pathogen, were used to build and test our model. Compared to many animals and plants, Aspergillus contains smaller introns; thus we have applied a larger window...

  1. Ensemble approach combining multiple methods improves human transcription start site prediction

    LENUS (Irish Health Repository)

    Dineen, David G

    2010-11-30

    Abstract Background The computational prediction of transcription start sites is an important unsolved problem. Some recent progress has been made, but many promoters, particularly those not associated with CpG islands, are still difficult to locate using current methods. These methods use different features and training sets, along with a variety of machine learning techniques and result in different prediction sets. Results We demonstrate the heterogeneity of current prediction sets, and take advantage of this heterogeneity to construct a two-level classifier (\\'Profisi Ensemble\\') using predictions from 7 programs, along with 2 other data sources. Support vector machines using \\'full\\' and \\'reduced\\' data sets are combined in an either\\/or approach. We achieve a 14% increase in performance over the current state-of-the-art, as benchmarked by a third-party tool. Conclusions Supervised learning methods are a useful way to combine predictions from diverse sources.

  2. A machine-learning approach for predicting palmitoylation sites from integrated sequence-based features.

    Science.gov (United States)

    Li, Liqi; Luo, Qifa; Xiao, Weidong; Li, Jinhui; Zhou, Shiwen; Li, Yongsheng; Zheng, Xiaoqi; Yang, Hua

    2017-02-01

    Palmitoylation is the covalent attachment of lipids to amino acid residues in proteins. As an important form of protein posttranslational modification, it increases the hydrophobicity of proteins, which contributes to the protein transportation, organelle localization, and functions, therefore plays an important role in a variety of cell biological processes. Identification of palmitoylation sites is necessary for understanding protein-protein interaction, protein stability, and activity. Since conventional experimental techniques to determine palmitoylation sites in proteins are both labor intensive and costly, a fast and accurate computational approach to predict palmitoylation sites from protein sequences is in urgent need. In this study, a support vector machine (SVM)-based method was proposed through integrating PSI-BLAST profile, physicochemical properties, [Formula: see text]-mer amino acid compositions (AACs), and [Formula: see text]-mer pseudo AACs into the principal feature vector. A recursive feature selection scheme was subsequently implemented to single out the most discriminative features. Finally, an SVM method was implemented to predict palmitoylation sites in proteins based on the optimal features. The proposed method achieved an accuracy of 99.41% and Matthews Correlation Coefficient of 0.9773 for a benchmark dataset. The result indicates the efficiency and accuracy of our method in prediction of palmitoylation sites based on protein sequences.

  3. Predicting protein ligand binding sites by combining evolutionary sequence conservation and 3D structure.

    Directory of Open Access Journals (Sweden)

    John A Capra

    2009-12-01

    Full Text Available Identifying a protein's functional sites is an important step towards characterizing its molecular function. Numerous structure- and sequence-based methods have been developed for this problem. Here we introduce ConCavity, a small molecule binding site prediction algorithm that integrates evolutionary sequence conservation estimates with structure-based methods for identifying protein surface cavities. In large-scale testing on a diverse set of single- and multi-chain protein structures, we show that ConCavity substantially outperforms existing methods for identifying both 3D ligand binding pockets and individual ligand binding residues. As part of our testing, we perform one of the first direct comparisons of conservation-based and structure-based methods. We find that the two approaches provide largely complementary information, which can be combined to improve upon either approach alone. We also demonstrate that ConCavity has state-of-the-art performance in predicting catalytic sites and drug binding pockets. Overall, the algorithms and analysis presented here significantly improve our ability to identify ligand binding sites and further advance our understanding of the relationship between evolutionary sequence conservation and structural and functional attributes of proteins. Data, source code, and prediction visualizations are available on the ConCavity web site (http://compbio.cs.princeton.edu/concavity/.

  4. Predicting protein ligand binding sites by combining evolutionary sequence conservation and 3D structure.

    Science.gov (United States)

    Capra, John A; Laskowski, Roman A; Thornton, Janet M; Singh, Mona; Funkhouser, Thomas A

    2009-12-01

    Identifying a protein's functional sites is an important step towards characterizing its molecular function. Numerous structure- and sequence-based methods have been developed for this problem. Here we introduce ConCavity, a small molecule binding site prediction algorithm that integrates evolutionary sequence conservation estimates with structure-based methods for identifying protein surface cavities. In large-scale testing on a diverse set of single- and multi-chain protein structures, we show that ConCavity substantially outperforms existing methods for identifying both 3D ligand binding pockets and individual ligand binding residues. As part of our testing, we perform one of the first direct comparisons of conservation-based and structure-based methods. We find that the two approaches provide largely complementary information, which can be combined to improve upon either approach alone. We also demonstrate that ConCavity has state-of-the-art performance in predicting catalytic sites and drug binding pockets. Overall, the algorithms and analysis presented here significantly improve our ability to identify ligand binding sites and further advance our understanding of the relationship between evolutionary sequence conservation and structural and functional attributes of proteins. Data, source code, and prediction visualizations are available on the ConCavity web site (http://compbio.cs.princeton.edu/concavity/).

  5. Accurate microRNA target prediction using detailed binding site accessibility and machine learning on proteomics data

    Directory of Open Access Journals (Sweden)

    Martin eReczko

    2012-01-01

    Full Text Available MicroRNAs (miRNAs are a class of small regulatory genes regulating gene expression by targetingmessenger RNA. Though computational methods for miRNA target prediction are the prevailingmeans to analyze their function, they still miss a large fraction of the targeted genes and additionallypredict a large number of false positives. Here we introduce a novel algorithm called DIANAmicroT-ANN which combines multiple novel target site features through an artificial neural network(ANN and is trained using recently published high-throughput data measuring the change of proteinlevels after miRNA overexpression, providing positive and negative targeting examples. The featurescharacterizing each miRNA recognition element include binding structure, conservation level and aspecific profile of structural accessibility. The ANN is trained to integrate the features of eachrecognition element along the 3’ untranslated region into a targeting score, reproducing the relativerepression fold change of the protein. Tested on two different sets the algorithm outperforms otherwidely used algorithms and also predicts a significant number of unique and reliable targets notpredicted by the other methods. For 542 human miRNAs DIANA-microT-ANN predicts 120,000targets not provided by TargetScan 5.0. The algorithm is freely available athttp://microrna.gr/microT-ANN.

  6. Probabilistic Assessment of Above Zone Pressure Predictions at a Geologic Carbon Storage Site

    Science.gov (United States)

    Namhata, Argha; Oladyshkin, Sergey; Dilmore, Robert M.; Zhang, Liwei; Nakles, David V.

    2016-12-01

    Carbon dioxide (CO2) storage into geological formations is regarded as an important mitigation strategy for anthropogenic CO2 emissions to the atmosphere. This study first simulates the leakage of CO2 and brine from a storage reservoir through the caprock. Then, we estimate the resulting pressure changes at the zone overlying the caprock also known as Above Zone Monitoring Interval (AZMI). A data-driven approach of arbitrary Polynomial Chaos (aPC) Expansion is then used to quantify the uncertainty in the above zone pressure prediction based on the uncertainties in different geologic parameters. Finally, a global sensitivity analysis is performed with Sobol indices based on the aPC technique to determine the relative importance of different parameters on pressure prediction. The results indicate that there can be uncertainty in pressure prediction locally around the leakage zones. The degree of such uncertainty in prediction depends on the quality of site specific information available for analysis. The scientific results from this study provide substantial insight that there is a need for site-specific data for efficient predictions of risks associated with storage activities. The presented approach can provide a basis of optimized pressure based monitoring network design at carbon storage sites.

  7. Improving the prediction of protein binding sites by combining heterogeneous data and Voronoi diagrams

    Directory of Open Access Journals (Sweden)

    Fernandez-Fuentes Narcis

    2011-08-01

    Full Text Available Abstract Background Protein binding site prediction by computational means can yield valuable information that complements and guides experimental approaches to determine the structure of protein complexes. Predictions become even more relevant and timely given the current resolution of protein interaction maps, where there is a very large and still expanding gap between the available information on: (i which proteins interact and (ii how proteins interact. Proteins interact through exposed residues that present differential physicochemical properties, and these can be exploited to identify protein interfaces. Results Here we present VORFFIP, a novel method for protein binding site prediction. The method makes use of broad set of heterogeneous data and defined of residue environment, by means of Voronoi Diagrams that are integrated by a two-steps Random Forest ensemble classifier. Four sets of residue features (structural, energy terms, sequence conservation, and crystallographic B-factors used in different combinations together with three definitions of residue environment (Voronoi Diagrams, sequence sliding window, and Euclidian distance have been analyzed in order to maximize the performance of the method. Conclusions The integration of different forms information such as structural features, energy term, evolutionary conservation and crystallographic B-factors, improves the performance of binding site prediction. Including the information of neighbouring residues also improves the prediction of protein interfaces. Among the different approaches that can be used to define the environment of exposed residues, Voronoi Diagrams provide the most accurate description. Finally, VORFFIP compares favourably to other methods reported in the recent literature.

  8. Proteins and Their Interacting Partners: An Introduction to Protein-Ligand Binding Site Prediction Methods.

    Science.gov (United States)

    Roche, Daniel Barry; Brackenridge, Danielle Allison; McGuffin, Liam James

    2015-12-15

    Elucidating the biological and biochemical roles of proteins, and subsequently determining their interacting partners, can be difficult and time consuming using in vitro and/or in vivo methods, and consequently the majority of newly sequenced proteins will have unknown structures and functions. However, in silico methods for predicting protein-ligand binding sites and protein biochemical functions offer an alternative practical solution. The characterisation of protein-ligand binding sites is essential for investigating new functional roles, which can impact the major biological research spheres of health, food, and energy security. In this review we discuss the role in silico methods play in 3D modelling of protein-ligand binding sites, along with their role in predicting biochemical functionality. In addition, we describe in detail some of the key alternative in silico prediction approaches that are available, as well as discussing the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and the Continuous Automated Model EvaluatiOn (CAMEO) projects, and their impact on developments in the field. Furthermore, we discuss the importance of protein function prediction methods for tackling 21st century problems.

  9. Site of metabolism prediction based on ab initio derived atom representations.

    Science.gov (United States)

    Finkelmann, Arndt R; Göller, Andreas H; Schneider, Gisbert

    2017-03-21

    Machine learning models for site of metabolism (SoM) prediction offer the ability to identify metabolic soft spots in low molecular weight drug molecules at low computational cost and enable data-based reactivity prediction. SoM prediction is an atom classification problem. Successful construction of machine learning models requires atom representations that capture the reactivity-determining features of a potential reaction site. We have developed a descriptor scheme that characterizes an atom's steric and electronic environment and its relative location in the molecular structure. The partial charge distributions were obtained from fast quantum mechanical calculations. We successfully trained machine learning classifiers on curated cytochrome p450 metabolism data. The models based on the new atom descriptors showed sustained accuracy for retrospective analyses of metabolism optimization campaigns and lead optimization projects from Bayer Pharmaceuticals. The results obtained demonstrate the practicality of quantum-chemistry-supported machine learning models for hit-to-lead optimization.

  10. Prediction of Protein-Protein Interaction Sites Based on Naive Bayes Classifier

    Directory of Open Access Journals (Sweden)

    Haijiang Geng

    2015-01-01

    Full Text Available Protein functions through interactions with other proteins and biomolecules and these interactions occur on the so-called interface residues of the protein sequences. Identifying interface residues makes us better understand the biological mechanism of protein interaction. Meanwhile, information about the interface residues contributes to the understanding of metabolic, signal transduction networks and indicates directions in drug designing. In recent years, researchers have focused on developing new computational methods for predicting protein interface residues. Here we creatively used a 181-dimension protein sequence feature vector as input to the Naive Bayes Classifier- (NBC- based method to predict interaction sites in protein-protein complexes interaction. The prediction of interaction sites in protein interactions is regarded as an amino acid residue binary classification problem by applying NBC with protein sequence features. Independent test results suggested that Naive Bayes Classifier-based method with the protein sequence features as input vectors performed well.

  11. A Random Forest Model for Predicting Allosteric and Functional Sites on Proteins.

    Science.gov (United States)

    Chen, Ava S-Y; Westwood, Nicholas J; Brear, Paul; Rogers, Graeme W; Mavridis, Lazaros; Mitchell, John B O

    2016-04-01

    We created a computational method to identify allosteric sites using a machine learning method trained and tested on protein structures containing bound ligand molecules. The Random Forest machine learning approach was adopted to build our three-way predictive model. Based on descriptors collated for each ligand and binding site, the classification model allows us to assign protein cavities as allosteric, regular or orthosteric, and hence to identify allosteric sites. 43 structural descriptors per complex were derived and were used to characterize individual protein-ligand binding sites belonging to the three classes, allosteric, regular and orthosteric. We carried out a separate validation on a further unseen set of protein structures containing the ligand 2-(N-cyclohexylamino) ethane sulfonic acid (CHES).

  12. Ten problems and solutions when predicting individual outcome from lesion site after stroke.

    Science.gov (United States)

    Price, Cathy J; Hope, Thomas M; Seghier, Mohamed L

    2017-01-15

    In this paper, we consider solutions to ten of the challenges faced when trying to predict an individual's functional outcome after stroke on the basis of lesion site. A primary goal is to find lesion-outcome associations that are consistently observed in large populations of stroke patients because consistent associations maximise confidence in future individualised predictions. To understand and control multiple sources of inter-patient variability, we need to systematically investigate each contributing factor and how each factor depends on other factors. This requires very large cohorts of patients, who differ from one another in typical and measurable ways, including lesion site, lesion size, functional outcome and time post stroke (weeks to decades). These multivariate investigations are complex, particularly when the contributions of different variables interact with one another. Machine learning algorithms can help to identify the most influential variables and indicate dependencies between different factors. Multivariate lesion analyses are needed to understand how the effect of damage to one brain region depends on damage or preservation in other brain regions. Such data-led investigations can reveal predictive relationships between lesion site and outcome. However, to understand and improve the predictions we need explanatory models of the neural networks and degenerate pathways that support functions of interest. This will entail integrating the results of lesion analyses with those from functional imaging (fMRI, MEG), transcranial magnetic stimulation (TMS) and diffusor tensor imaging (DTI) studies of healthy participants and patients. Copyright © 2016 Elsevier Inc. All rights reserved.

  13. STarMir Tools for Prediction of microRNA binding sites

    Science.gov (United States)

    Kanoria, Shaveta; Rennie, William; Liu, Chaochun; Carmack, C. Steven; Lu, Jun; Ding, Ye

    2017-01-01

    MicroRNAs (miRNAs) are a class of endogenous short non-coding RNAs that regulate gene expression by targeting messenger RNAs (mRNAs), which results in translational repression and/or mRNA degradation. As regulatory molecules, miRNAs are involved in many mammalian biological processes and also in the manifestation of certain human diseases. As miRNAs play central role in the regulation of gene expression, understanding miRNA-binding patterns is essential to gain an insight of miRNA mediated gene regulation and also holds promise for therapeutic applications. Computational prediction of miRNA binding sites on target mRNAs facilitates experimental investigation of miRNA functions. This chapter provides protocols for using the STarMir web server for improved predictions of miRNA binding sites on a target mRNA. As an application module of the Sfold RNA package, the current version of STarMir is an implementation of logistic prediction models developed with high throughput miRNA binding data from crosslinking immuno-precipitation (CLIP) studies. The models incorporated comprehensive thermodynamic, structural and sequence features, and were found to make improved predictions of both seed and seedless sites, in comparison to the established algorithms [1]. Their broad applicability was indicated by their good performance in cross-species validation. STarMir is freely available at http://sfold.wadsworth.org/starmir.html PMID:27665594

  14. Ground Motion Prediction for the Vicinity by Using the Microtremor Site-effect Correction

    Science.gov (United States)

    Lin, C. M.; Wen, K. L.; Kuo, C. H.

    2015-12-01

    This study develops a method analyzing the seismograms of a strong-motion station and the microtremor site effects (H/V ratios) around it to predict the ground motion of its vicinity. The Hsinchu Science Park (HSP) in Taiwan was chosen as our study site. The horizontal S-wave seismograms of the TCU017 strong-motion station, which locates at the center of the HSP, were convoluted by the difference of the microtremor H/V ratio between various sites to synthesize the seismograms of several strong-motion stations around the HSP. The comparisons between synthetic and observed seismograms show that this method of ground motion prediction for the vicinity is feasible for far-field earthquakes. However, the seismic source and attenuation effects make this method ineffectual for near-field earthquakes. Because the microtremor H/V ratios at about 200 sites, which are densely distributed in the HSP, were conducted, the seismic ground motion distributions of some historical earthquakes were synthesized by this study. The synthetic ground motion distributions ignore the seismic source and attenuation effects but still show notable variations in the HSP because of the seismic site effects.

  15. Improving N(6)-methyladenosine site prediction with heuristic selection of nucleotide physical-chemical properties.

    Science.gov (United States)

    Zhang, Ming; Sun, Jia-Wei; Liu, Zi; Ren, Ming-Wu; Shen, Hong-Bin; Yu, Dong-Jun

    2016-09-01

    N(6)-methyladenosine (m(6)A) is one of the most common and abundant post-transcriptional RNA modifications found in viruses and most eukaryotes. m(6)A plays an essential role in many vital biological processes to regulate gene expression. Because of its widespread distribution across the genomes, the identification of m(6)A sites from RNA sequences is of significant importance for better understanding the regulatory mechanism of m(6)A. Although progress has been achieved in m(6)A site prediction, challenges remain. This article aims to further improve the performance of m(6)A site prediction by introducing a new heuristic nucleotide physical-chemical property selection (HPCS) algorithm. The proposed HPCS algorithm can effectively extract an optimized subset of nucleotide physical-chemical properties under the prescribed feature representation for encoding an RNA sequence into a feature vector. We demonstrate the efficacy of the proposed HPCS algorithm under different feature representations, including pseudo dinucleotide composition (PseDNC), auto-covariance (AC), and cross-covariance (CC). Based on the proposed HPCS algorithm, we implemented an m(6)A site predictor, called M6A-HPCS, which is freely available at http://csbio.njust.edu.cn/bioinf/M6A-HPCS. Experimental results over rigorous jackknife tests on benchmark datasets demonstrated that the proposed M6A-HPCS achieves higher success rates and outperforms existing state-of-the-art sequence-based m(6)A site predictors.

  16. SPE-5 Ground-Motion Prediction at Far-Field Geophone and Accelerometer Array Sites and SPE-5 Moment and Corner-Frequency Prediction

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Xiaoning [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Patton, Howard John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Chen, Ting [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-03-25

    This report offers predictions for the SPE-5 ground-motion and accelerometer array sites. These predictions pertain to the waveform and spectral amplitude at certain geophone sites using Denny&Johnson source model and a source model derived from SPE data; waveform, peak velocity and peak acceleration at accelerometer sites using the SPE source model and the finite-difference simulation with LLNL 3D velocity model; and the SPE-5 moment and corner frequency.

  17. SPE-5 Ground-Motion Prediction at Far-Field Geophone and Accelerometer Array Sites and SPE-5 Moment and Corner-Frequency Prediction

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Xiaoning [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Patton, Howard John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Chen, Ting [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-03-25

    This report offers predictions for the SPE-5 ground-motion and accelerometer array sites. These predictions pertain to the waveform and spectral amplitude at certain geophone sites using Denny&Johnson source model and a source model derived from SPE data; waveform, peak velocity and peak acceleration at accelerometer sites using the SPE source model and the finite-difference simulation with LLNL 3D velocity model; and the SPE-5 moment and corner frequency.

  18. Development of a protein-ligand-binding site prediction method based on interaction energy and sequence conservation.

    Science.gov (United States)

    Tsujikawa, Hiroto; Sato, Kenta; Wei, Cao; Saad, Gul; Sumikoshi, Kazuya; Nakamura, Shugo; Terada, Tohru; Shimizu, Kentaro

    2016-09-01

    We present a new method for predicting protein-ligand-binding sites based on protein three-dimensional structure and amino acid conservation. This method involves calculation of the van der Waals interaction energy between a protein and many probes placed on the protein surface and subsequent clustering of the probes with low interaction energies to identify the most energetically favorable locus. In addition, it uses amino acid conservation among homologous proteins. Ligand-binding sites were predicted by combining the interaction energy and the amino acid conservation score. The performance of our prediction method was evaluated using a non-redundant dataset of 348 ligand-bound and ligand-unbound protein structure pairs, constructed by filtering entries in a ligand-binding site structure database, LigASite. Ligand-bound structure prediction (bound prediction) indicated that 74.0 % of predicted ligand-binding sites overlapped with real ligand-binding sites by over 25 % of their volume. Ligand-unbound structure prediction (unbound prediction) indicated that 73.9 % of predicted ligand-binding residues overlapped with real ligand-binding residues. The amino acid conservation score improved the average prediction accuracy by 17.0 and 17.6 points for the bound and unbound predictions, respectively. These results demonstrate the effectiveness of the combined use of the interaction energy and amino acid conservation in the ligand-binding site prediction.

  19. A Python analytical pipeline to identify prohormone precursors and predict prohormone cleavage sites

    Directory of Open Access Journals (Sweden)

    Bruce Southey

    2008-12-01

    Full Text Available Neuropeptides and hormones are signaling molecules that support cell-cell communication in the central nervous system. Experimentally characterizing neuropeptides requires significant efforts because of the complex and variable processing of prohormone precursor proteins into neuropeptides and hormones. We demonstrate the power and flexibility of the Python language to develop components of an bioinformatic analytical pipeline to identify precursors from genomic data and to predict cleavage as these precursors are en route to the final bioactive peptides. We identified 75 precursors in the rhesus genome, predicted cleavage sites using support vector machines and compared the rhesus predictions to putative assignments based on homology to human sequences. The correct classification rate of cleavage using the support vector machines was over 97% for both human and rhesus data sets. The functionality of Python has been important to develop and maintain NeuroPred (http://neuroproteomics.scs.uiuc.edu/neuropred.html, a user-centered web application for the neuroscience community that provides cleavage site prediction from a wide range of models, precision and accuracy statistics, post-translational modifications, and the molecular mass of potential peptides. The combined results illustrate the suitability of the Python language to implement an all-inclusive bioinformatics approach to predict neuropeptides that encompasses a large number of interdependent steps, from scanning genomes for precursor genes to identification of potential bioactive neuropeptides.

  20. A python analytical pipeline to identify prohormone precursors and predict prohormone cleavage sites.

    Science.gov (United States)

    Southey, Bruce R; Sweedler, Jonathan V; Rodriguez-Zas, Sandra L

    2008-01-01

    Neuropeptides and hormones are signaling molecules that support cell-cell communication in the central nervous system. Experimentally characterizing neuropeptides requires significant efforts because of the complex and variable processing of prohormone precursor proteins into neuropeptides and hormones. We demonstrate the power and flexibility of the Python language to develop components of an bioinformatic analytical pipeline to identify precursors from genomic data and to predict cleavage as these precursors are en route to the final bioactive peptides. We identified 75 precursors in the rhesus genome, predicted cleavage sites using support vector machines and compared the rhesus predictions to putative assignments based on homology to human sequences. The correct classification rate of cleavage using the support vector machines was over 97% for both human and rhesus data sets. The functionality of Python has been important to develop and maintain NeuroPred (http://neuroproteomics.scs.uiuc.edu/neuropred.html), a user-centered web application for the neuroscience community that provides cleavage site prediction from a wide range of models, precision and accuracy statistics, post-translational modifications, and the molecular mass of potential peptides. The combined results illustrate the suitability of the Python language to implement an all-inclusive bioinformatics approach to predict neuropeptides that encompasses a large number of interdependent steps, from scanning genomes for precursor genes to identification of potential bioactive neuropeptides.

  1. Conserved residues in RF-NH₂ receptor models identify predicted contact sites in ligand-receptor binding.

    Science.gov (United States)

    Bass, C; Katanski, C; Maynard, B; Zurro, I; Mariane, E; Matta, M; Loi, M; Melis, V; Capponi, V; Muroni, P; Setzu, M; Nichols, R

    2014-03-01

    Peptides in the RF-NH2 family are grouped together based on an amidated dipeptide C terminus and signal through G-protein coupled receptors (GPCRs) to influence diverse physiological functions. By determining the mechanisms underlying RF-NH2 signaling targets can be identified to modulate physiological activity; yet, how RF-NH2 peptides interact with GPCRs is relatively unexplored. We predicted conserved residues played a role in Drosophila melanogaster RF-NH2 ligand-receptor interactions. In this study D. melanogaster rhodopsin-like family A peptide GPCRs alignments identified eight conserved residues unique to RF-NH2 receptors. Three of these residues were in extra-cellular loops of modeled RF-NH2 receptors and four in transmembrane helices oriented into a ligand binding pocket to allow contact with a peptide. The eighth residue was unavailable for interaction; yet its conservation suggested it played another role. A novel hydrophobic region representative of RF-NH2 receptors was also discovered. The presence of rhodopsin-like family A GPCR structural motifs including a toggle switch indicated RF-NH2s signal classically; however, some features of the DMS receptors were distinct from other RF-NH2 GPCRs. Additionally, differences in RF-NH2 receptor structures which bind the same peptide explained ligand specificity. Our novel results predicted conserved residues as RF-NH2 ligand-receptor contact sites and identified unique and classic structural features. These discoveries will aid antagonist design to modulate RF-NH2 signaling. Copyright © 2013. Published by Elsevier Inc.

  2. Predicting interaction sites from the energetics of isolated proteins: a new approach to epitope mapping.

    Science.gov (United States)

    Scarabelli, Guido; Morra, Giulia; Colombo, Giorgio

    2010-05-19

    An increasing number of functional studies of proteins have shown that sequence and structural similarities alone may not be sufficient for reliable prediction of their interaction properties. This is particularly true for proteins recognizing specific antibodies, where the prediction of antibody-binding sites, called epitopes, has proven challenging. The antibody-binding properties of an antigen depend on its structure and related dynamics. Aiming to predict the antibody-binding regions of a protein, we investigate a new approach based on the integrated analysis of the dynamical and energetic properties of antigens, to identify nonoptimized, low-intensity energetic interaction networks in the protein structure isolated in solution. The method is based on the idea that recognition sites may correspond to localized regions with low-intensity energetic couplings with the rest of the protein, which allows them to undergo conformational changes, to be recognized by a binding partner, and to tolerate mutations with minimal energetic expense. Upon analyzing the results on isolated proteins and benchmarking against antibody complexes, it is found that the method successfully identifies binding sites located on the protein surface that are accessible to putative binding partners. The combination of dynamics and energetics can thus discriminate between epitopes and other substructures based only on physical properties. We discuss implications for vaccine design.

  3. Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms

    Science.gov (United States)

    Tramontana, Gianluca; Jung, Martin; Schwalm, Christopher R.; Ichii, Kazuhito; Camps-Valls, Gustau; Ráduly, Botond; Reichstein, Markus; Altaf Arain, M.; Cescatti, Alessandro; Kiely, Gerard; Merbold, Lutz; Serrano-Ortiz, Penelope; Sickert, Sven; Wolf, Sebastian; Papale, Dario

    2016-07-01

    Spatio-temporal fields of land-atmosphere fluxes derived from data-driven models can complement simulations by process-based land surface models. While a number of strategies for empirical models with eddy-covariance flux data have been applied, a systematic intercomparison of these methods has been missing so far. In this study, we performed a cross-validation experiment for predicting carbon dioxide, latent heat, sensible heat and net radiation fluxes across different ecosystem types with 11 machine learning (ML) methods from four different classes (kernel methods, neural networks, tree methods, and regression splines). We applied two complementary setups: (1) 8-day average fluxes based on remotely sensed data and (2) daily mean fluxes based on meteorological data and a mean seasonal cycle of remotely sensed variables. The patterns of predictions from different ML and experimental setups were highly consistent. There were systematic differences in performance among the fluxes, with the following ascending order: net ecosystem exchange (R2 0.6), gross primary production (R2> 0.7), latent heat (R2 > 0.7), sensible heat (R2 > 0.7), and net radiation (R2 > 0.8). The ML methods predicted the across-site variability and the mean seasonal cycle of the observed fluxes very well (R2 > 0.7), while the 8-day deviations from the mean seasonal cycle were not well predicted (R2 Fluxes were better predicted at forested and temperate climate sites than at sites in extreme climates or less represented by training data (e.g., the tropics). The evaluated large ensemble of ML-based models will be the basis of new global flux products.

  4. On splice site prediction using weight array models: a comparison of smoothing techniques

    Science.gov (United States)

    Taher, Leila; Meinicke, Peter; Morgenstern, Burkhard

    2007-11-01

    In most eukaryotic genes, protein-coding exons are separated by non-coding introns which are removed from the primary transcript by a process called "splicing". The positions where introns are cut and exons are spliced together are called "splice sites". Thus, computational prediction of splice sites is crucial for gene finding in eukaryotes. Weight array models are a powerful probabilistic approach to splice site detection. Parameters for these models are usually derived from m-tuple frequencies in trusted training data and subsequently smoothed to avoid zero probabilities. In this study we compare three different ways of parameter estimation for m-tuple frequencies, namely (a) non-smoothed probability estimation, (b) standard pseudo counts and (c) a Gaussian smoothing procedure that we recently developed.

  5. Prediction of allosteric sites and mediating interactions through bond-to-bond propensities

    Science.gov (United States)

    Amor, B. R. C.; Schaub, M. T.; Yaliraki, S. N.; Barahona, M.

    2016-08-01

    Allostery is a fundamental mechanism of biological regulation, in which binding of a molecule at a distant location affects the active site of a protein. Allosteric sites provide targets to fine-tune protein activity, yet we lack computational methodologies to predict them. Here we present an efficient graph-theoretical framework to reveal allosteric interactions (atoms and communication pathways strongly coupled to the active site) without a priori information of their location. Using an atomistic graph with energy-weighted covalent and weak bonds, we define a bond-to-bond propensity quantifying the non-local effect of instantaneous bond fluctuations propagating through the protein. Significant interactions are then identified using quantile regression. We exemplify our method with three biologically important proteins: caspase-1, CheY, and h-Ras, correctly predicting key allosteric interactions, whose significance is additionally confirmed against a reference set of 100 proteins. The almost-linear scaling of our method renders it suitable for high-throughput searches for candidate allosteric sites.

  6. SPEER-SERVER: a web server for prediction of protein specificity determining sites

    Science.gov (United States)

    Chakraborty, Abhijit; Mandloi, Sapan; Lanczycki, Christopher J.; Panchenko, Anna R.; Chakrabarti, Saikat

    2012-01-01

    Sites that show specific conservation patterns within subsets of proteins in a protein family are likely to be involved in the development of functional specificity. These sites, generally termed specificity determining sites (SDS), might play a crucial role in binding to a specific substrate or proteins. Identification of SDS through experimental techniques is a slow, difficult and tedious job. Hence, it is very important to develop efficient computational methods that can more expediently identify SDS. Herein, we present Specificity prediction using amino acids’ Properties, Entropy and Evolution Rate (SPEER)-SERVER, a web server that predicts SDS by analyzing quantitative measures of the conservation patterns of protein sites based on their physico-chemical properties and the heterogeneity of evolutionary changes between and within the protein subfamilies. This web server provides an improved representation of results, adds useful input and output options and integrates a wide range of analysis and data visualization tools when compared with the original standalone version of the SPEER algorithm. Extensive benchmarking finds that SPEER-SERVER exhibits sensitivity and precision performance that, on average, meets or exceeds that of other currently available methods. SPEER-SERVER is available at http://www.hpppi.iicb.res.in/ss/. PMID:22689646

  7. Prediction of biological functions on glycosylation site migrations in human influenza H1N1 viruses.

    Science.gov (United States)

    Sun, Shisheng; Wang, Qinzhe; Zhao, Fei; Chen, Wentian; Li, Zheng

    2012-01-01

    Protein glycosylation alteration is typically employed by various viruses for escaping immune pressures from their hosts. Our previous work had shown that not only the increase of glycosylation sites (glycosites) numbers, but also glycosite migration might be involved in the evolution of human seasonal influenza H1N1 viruses. More importantly, glycosite migration was likely a more effectively alteration way for the host adaption of human influenza H1N1 viruses. In this study, we provided more bioinformatics and statistic evidences for further predicting the significant biological functions of glycosite migration in the host adaptation of human influenza H1N1 viruses, by employing homology modeling and in silico protein glycosylation of representative HA and NA proteins as well as amino acid variability analysis at antigenic sites of HA and NA. The results showed that glycosite migrations in human influenza viruses have at least five possible functions: to more effectively mask the antigenic sites, to more effectively protect the enzymatic cleavage sites of neuraminidase (NA), to stabilize the polymeric structures, to regulate the receptor binding and catalytic activities and to balance the binding activity of hemagglutinin (HA) with the release activity of NA. The information here can provide some constructive suggestions for the function research related to protein glycosylation of influenza viruses, although these predictions still need to be supported by experimental data.

  8. Snoring Sounds Predict Obstruction Sites and Surgical Response in Patients with Obstructive Sleep Apnea Hypopnea Syndrome

    Science.gov (United States)

    Lee, Li-Ang; Lo, Yu-Lun; Yu, Jen-Fang; Lee, Gui-She; Ni, Yung-Lun; Chen, Ning-Hung; Fang, Tuan-Jen; Huang, Chung-Guei; Cheng, Wen-Nuan; Li, Hsueh-Yu

    2016-01-01

    Snoring sounds generated by different vibrators of the upper airway may be useful indicators of obstruction sites in patients with obstructive sleep apnea hypopnea syndrome (OSAHS). This study aimed to investigate associations between snoring sounds, obstruction sites, and surgical responses (≥50% reduction in the apnea-hypopnea index [AHI] and DISE), and relocation pharyngoplasty. All patients received follow-up polysomnography after 6 months. Fifteen (42%) patients with at least two complete obstruction sites defined by DISE were significantly, positively associated with maximal snoring sound intensity (40–300 Hz; odds ratio [OR], 1.25, 95% confidence interval [CI] 1.05–1.49) and body mass index (OR, 1.48, 95% CI 1.02–2.15) after logistic regression analysis. Tonsil obstruction was significantly, inversely correlated with mean snoring sound intensity (301–850 Hz; OR, 0.84, 95% CI 0.74–0.96). Moreover, baseline tonsil obstruction detected by either DISE or mean snoring sound intensity (301–850 Hz), and AHI could significantly predict the surgical response. Our findings suggest that snoring sound detection may be helpful in determining obstruction sites and predict surgical responses. PMID:27471038

  9. Position-specific prediction of methylation sites from sequence conservation based on information theory.

    Science.gov (United States)

    Shi, Yinan; Guo, Yanzhi; Hu, Yayun; Li, Menglong

    2015-07-23

    Protein methylation plays vital roles in many biological processes and has been implicated in various human diseases. To fully understand the mechanisms underlying methylation for use in drug design and work in methylation-related diseases, an initial but crucial step is to identify methylation sites. The use of high-throughput bioinformatics methods has become imperative to predict methylation sites. In this study, we developed a novel method that is based only on sequence conservation to predict protein methylation sites. Conservation difference profiles between methylated and non-methylated peptides were constructed by the information entropy (IE) in a wider neighbor interval around the methylation sites that fully incorporated all of the environmental information. Then, the distinctive neighbor residues were identified by the importance scores of information gain (IG). The most representative model was constructed by support vector machine (SVM) for Arginine and Lysine methylation, respectively. This model yielded a promising result on both the benchmark dataset and independent test set. The model was used to screen the entire human proteome, and many unknown substrates were identified. These results indicate that our method can serve as a useful supplement to elucidate the mechanism of protein methylation and facilitate hypothesis-driven experimental design and validation.

  10. Prediction of posttranslational modification sites from amino acid sequences with kernel methods.

    Science.gov (United States)

    Xu, Yan; Wang, Xiaobo; Wang, Yongcui; Tian, Yingjie; Shao, Xiaojian; Wu, Ling-Yun; Deng, Naiyang

    2014-03-07

    Post-translational modification (PTM) is the chemical modification of a protein after its translation and one of the later steps in protein biosynthesis for many proteins. It plays an important role which modifies the end product of gene expression and contributes to biological processes and diseased conditions. However, the experimental methods for identifying PTM sites are both costly and time-consuming. Hence computational methods are highly desired. In this work, a novel encoding method PSPM (position-specific propensity matrices) is developed. Then a support vector machine (SVM) with the kernel matrix computed by PSPM is applied to predict the PTM sites. The experimental results indicate that the performance of new method is better or comparable with the existing methods. Therefore, the new method is a useful computational resource for the identification of PTM sites. A unified standalone software PTMPred is developed. It can be used to predict all types of PTM sites if the user provides the training datasets. The software can be freely downloaded from http://www.aporc.org/doc/wiki/PTMPred.

  11. Computational prediction of cAMP receptor protein (CRP binding sites in cyanobacterial genomes

    Directory of Open Access Journals (Sweden)

    Su Zhengchang

    2009-01-01

    Full Text Available Abstract Background Cyclic AMP receptor protein (CRP, also known as catabolite gene activator protein (CAP, is an important transcriptional regulator widely distributed in many bacteria. The biological processes under the regulation of CRP are highly diverse among different groups of bacterial species. Elucidation of CRP regulons in cyanobacteria will further our understanding of the physiology and ecology of this important group of microorganisms. Previously, CRP has been experimentally studied in only two cyanobacterial strains: Synechocystis sp. PCC 6803 and Anabaena sp. PCC 7120; therefore, a systematic genome-scale study of the potential CRP target genes and binding sites in cyanobacterial genomes is urgently needed. Results We have predicted and analyzed the CRP binding sites and regulons in 12 sequenced cyanobacterial genomes using a highly effective cis-regulatory binding site scanning algorithm. Our results show that cyanobacterial CRP binding sites are very similar to those in E. coli; however, the regulons are very different from that of E. coli. Furthermore, CRP regulons in different cyanobacterial species/ecotypes are also highly diversified, ranging from photosynthesis, carbon fixation and nitrogen assimilation, to chemotaxis and signal transduction. In addition, our prediction indicates that crp genes in modern cyanobacteria are likely inherited from a common ancestral gene in their last common ancestor, and have adapted various cellular functions in different environments, while some cyanobacteria lost their crp genes as well as CRP binding sites during the course of evolution. Conclusion The CRP regulons in cyanobacteria are highly diversified, probably as a result of divergent evolution to adapt to various ecological niches. Cyanobacterial CRPs may function as lineage-specific regulators participating in various cellular processes, and are important in some lineages. However, they are dispensable in some other lineages. The

  12. High DNA melting temperature predicts transcription start site location in human and mouse.

    LENUS (Irish Health Repository)

    Dineen, David G

    2009-12-01

    The accurate computational prediction of transcription start sites (TSS) in vertebrate genomes is a difficult problem. The physicochemical properties of DNA can be computed in various ways and a many combinations of DNA features have been tested in the past for use as predictors of transcription. We looked in detail at melting temperature, which measures the temperature, at which two strands of DNA separate, considering the cooperative nature of this process. We find that peaks in melting temperature correspond closely to experimentally determined transcription start sites in human and mouse chromosomes. Using melting temperature alone, and with simple thresholding, we can predict TSS with accuracy that is competitive with the most accurate state-of-the-art TSS prediction methods. Accuracy is measured using both experimentally and manually determined TSS. The method works especially well with CpG island containing promoters, but also works when CpG islands are absent. This result is clear evidence of the important role of the physical properties of DNA in the process of transcription. It also points to the importance for TSS prediction methods to include melting temperature as prior information.

  13. NBA-Palm: prediction of palmitoylation site implemented in Naïve Bayes algorithm.

    Science.gov (United States)

    Xue, Yu; Chen, Hu; Jin, Changjiang; Sun, Zhirong; Yao, Xuebiao

    2006-10-17

    Protein palmitoylation, an essential and reversible post-translational modification (PTM), has been implicated in cellular dynamics and plasticity. Although numerous experimental studies have been performed to explore the molecular mechanisms underlying palmitoylation processes, the intrinsic feature of substrate specificity has remained elusive. Thus, computational approaches for palmitoylation prediction are much desirable for further experimental design. In this work, we present NBA-Palm, a novel computational method based on Naïve Bayes algorithm for prediction of palmitoylation site. The training data is curated from scientific literature (PubMed) and includes 245 palmitoylated sites from 105 distinct proteins after redundancy elimination. The proper window length for a potential palmitoylated peptide is optimized as six. To evaluate the prediction performance of NBA-Palm, 3-fold cross-validation, 8-fold cross-validation and Jack-Knife validation have been carried out. Prediction accuracies reach 85.79% for 3-fold cross-validation, 86.72% for 8-fold cross-validation and 86.74% for Jack-Knife validation. Two more algorithms, RBF network and support vector machine (SVM), also have been employed and compared with NBA-Palm. Taken together, our analyses demonstrate that NBA-Palm is a useful computational program that provides insights for further experimentation. The accuracy of NBA-Palm is comparable with our previously described tool CSS-Palm. The NBA-Palm is freely accessible from: http://www.bioinfo.tsinghua.edu.cn/NBA-Palm.

  14. NBA-Palm: prediction of palmitoylation site implemented in Naïve Bayes algorithm

    Directory of Open Access Journals (Sweden)

    Jin Changjiang

    2006-10-01

    Full Text Available Abstract Background Protein palmitoylation, an essential and reversible post-translational modification (PTM, has been implicated in cellular dynamics and plasticity. Although numerous experimental studies have been performed to explore the molecular mechanisms underlying palmitoylation processes, the intrinsic feature of substrate specificity has remained elusive. Thus, computational approaches for palmitoylation prediction are much desirable for further experimental design. Results In this work, we present NBA-Palm, a novel computational method based on Naïve Bayes algorithm for prediction of palmitoylation site. The training data is curated from scientific literature (PubMed and includes 245 palmitoylated sites from 105 distinct proteins after redundancy elimination. The proper window length for a potential palmitoylated peptide is optimized as six. To evaluate the prediction performance of NBA-Palm, 3-fold cross-validation, 8-fold cross-validation and Jack-Knife validation have been carried out. Prediction accuracies reach 85.79% for 3-fold cross-validation, 86.72% for 8-fold cross-validation and 86.74% for Jack-Knife validation. Two more algorithms, RBF network and support vector machine (SVM, also have been employed and compared with NBA-Palm. Conclusion Taken together, our analyses demonstrate that NBA-Palm is a useful computational program that provides insights for further experimentation. The accuracy of NBA-Palm is comparable with our previously described tool CSS-Palm. The NBA-Palm is freely accessible from: http://www.bioinfo.tsinghua.edu.cn/NBA-Palm.

  15. Neural Network Prediction of Translation Initiation Sites in Eukaryotes: Perspectives for EST and Genome analysis

    DEFF Research Database (Denmark)

    Pedersen, Anders Gorm; Nielsen, Henrik

    1997-01-01

    Translation in eukaryotes does not always start at the first AUG in an mRNA, implying that context information also plays a role.This makes prediction of translation initiation sites a non-trivial task, especially when analysing EST and genome data where the entire mature mRNA sequence is not known...... and global sequence information. Furthermore, analysis of false predictions shows that AUGs in frame with the actual start codon are more frequently selected than out-of-frame AUGs, suggesting that our nteworks use reading frame detection. A number of conflicts between neural network predictions and database...... annotations are analysed in detail, leading to identification of possible database errors....

  16. Social Networking Site Use Predicts Changes in Young Adults’ Psychological Adjustment

    Science.gov (United States)

    Szwedo, David E.; Mikami, Amori Yee; Allen, Joseph P.

    2012-01-01

    This study examined youths’ friendships and posted pictures on social networking sites as predictors of changes in their adjustment over time. Observational, self-report, and peer report data were obtained from a community sample of 89 young adults interviewed at age 21 and again at age 22. Findings were consistent with a leveling effect for online friendships, predicting decreases in internalizing symptoms for youth with lower initial levels of social acceptance, but increases in symptoms for youth with higher initial levels over the following year. Across the entire sample, deviant behavior in posted photos predicted increases in young adults’ problematic alcohol use over time. The importance of considering the interplay between online and offline social factors for predicting adjustment is discussed. PMID:23109797

  17. Selection and Assessment of Predictions of the Mars Pathfinder Landing Site

    Science.gov (United States)

    Golombek, M. P.; Moore, H. J.; Haldemann, A. F. C.; Cook, R. A.; Parker, T. J.; Schofield, J. T.

    1998-01-01

    The successful landing of the Mars Pathfinder spacecraft on Mars allows the review of the process of selecting the landing site and assessing predictions made for the site based on Viking and Earth-based data. Selection of the landing site for Mars Pathfinder was a two-phase process. The first phase took place from October 1993 to June 1994 and involved: initial identification of engineering constraints, definition of environmental conditions at the site for spacecraft design, and evaluation of the scientific potential of different landing sites. This phase culminated with the first "Mars Pathfinder Landing Site Workshop", held at the Lunar and Planetary Institute in Houston, Texas on April 18-19, 1994, in which suggested approaches and landing sites were solicited from the entire scientific community. A preliminary site was selected by the project for design purposes in June 1994. The second phase took place from July 1994 to March 1996 and involved: developing criteria for evaluating site safety using images and remote sensing data, testing of the spacecraft and landing subsystems (with design improvements) to establish quantitative engineering constraints on landing site characteristics, evaluating all potential landing sites on Mars, and certification of the site by the project. This phase included a second open workshop, "Mars Pathfinder Landing Site Workshop II: Characteristics of the Ares Vallis Region and Field Trips in the Channeled Scabland, Washington" held in Spokane and Moses Lake September 24-30, 1995 and formal acceptance of the site by NASA Headquarters. Engineering constraints on Pathfinder landing sites were developed from the initial design of the spacecraft and the entry, descent and landing scenario. The site must be within 5 degrees of the subsolar latitude at the time of landing (15N for maximum solar power and flexible communications with Earth. It also must be below 0 km elevation to enable enough time for the parachute to bring the lander

  18. Improvement of AEP Predictions Using Diurnal CFD Modelling with Site-Specific Stability Weightings Provided from Mesoscale Simulation

    Science.gov (United States)

    Hristov, Y.; Oxley, G.; Žagar, M.

    2014-06-01

    The Bolund measurement campaign, performed by Danish Technical University (DTU) Wind Energy Department (also known as RISØ), provided significant insight into wind flow modeling over complex terrain. In the blind comparison study several modelling solutions were submitted with the vast majority being steady-state Computational Fluid Dynamics (CFD) approaches with two equation k-epsilon turbulence closure. This approach yielded the most accurate results, and was identified as the state-of-the-art tool for wind turbine generator (WTG) micro-siting. Based on the findings from Bolund, further comparison between CFD and field measurement data has been deemed essential in order to improve simulation accuracy for turbine load and long-term Annual Energy Production (AEP) estimations. Vestas Wind Systems A/S is a major WTG original equipment manufacturer (OEM) with an installed base of over 60GW in over 70 countries accounting for 19% of the global installed base. The Vestas Performance and Diagnostic Centre (VPDC) provides online live data to more than 47GW of these turbines allowing a comprehensive comparison between modelled and real-world energy production data. In previous studies, multiple sites have been simulated with a steady neutral CFD formulation for the atmospheric surface layer (ASL), and wind resource (RSF) files have been generated as a base for long-term AEP predictions showing significant improvement over predictions performed with the industry standard linear WAsP tool. In this study, further improvements to the wind resource file generation with CFD are examined using an unsteady diurnal cycle approach with a full atmospheric boundary layer (ABL) formulation, with the unique stratifications throughout the cycle weighted according to mesoscale simulated sectorwise stability frequencies.

  19. Prediction of carbamylated lysine sites based on the one-class k-nearest neighbor method.

    Science.gov (United States)

    Huang, Guohua; Zhou, You; Zhang, Yuchao; Li, Bi-Qing; Zhang, Ning; Cai, Yu-Dong

    2013-11-01

    Protein carbamylation is one of the important post-translational modifications, which plays a pivotal role in a number of biological conditions, such as diseases, chronic renal failure and atherosclerosis. Therefore, recognition and identification of protein carbamylated sites are essential for disease treatment and prevention. Yet the mechanism of action of carbamylated lysine sites is still not realized. Thus it remains a largely unsolved challenge to uncover it, whether experimentally or theoretically. To address this problem, we have presented a computational framework for theoretically predicting and analyzing carbamylated lysine sites based on both the one-class k-nearest neighbor method and two-stage feature selection. The one-class k-nearest neighbor method requires no negative samples in training. Experimental results showed that by using 280 optimal features the presented method achieved promising performances of SN=82.50% for the jackknife test on the training set, and SN=66.67%, SP=100.00% and MCC=0.8097 for the independent test on the testing set, respectively. Further analysis of the optimal features provided insights into the mechanism of action of carbamylated lysine sites. It is anticipated that our method could be a potentially useful and essential tool for biologists to theoretically investigate carbamylated lysine sites.

  20. E1DS: catalytic site prediction based on 1D signatures of concurrent conservation.

    Science.gov (United States)

    Chien, Ting-Ying; Chang, Darby Tien-Hao; Chen, Chien-Yu; Weng, Yi-Zhong; Hsu, Chen-Ming

    2008-07-01

    Large-scale automatic annotation of protein sequences remains challenging in postgenomics era. E1DS is designed for annotating enzyme sequences based on a repository of 1D signatures. The employed sequence signatures are derived using a novel pattern mining approach that discovers long motifs consisted of several sequential blocks (conserved segments). Each of the sequential blocks is considerably conserved among the protein members of an EC group. Moreover, a signature includes at least three sequential blocks that are concurrently conserved, i.e. frequently observed together in sequences. In other words, a sequence signature is consisted of residues from multiple regions of the protein sequence, which echoes the observation that an enzyme catalytic site is usually constituted of residues that are largely separated in the sequence. E1DS currently contains 5421 sequence signatures that in total cover 932 4-digital EC numbers. E1DS is evaluated based on a collection of enzymes with catalytic sites annotated in Catalytic Site Atlas. When compared to the famous pattern database PROSITE, predictions based on E1DS signatures are considered more sensitive in identifying catalytic sites and the involved residues. E1DS is available at http://e1ds.ee.ncku.edu.tw/ and a mirror site can be found at http://e1ds.csbb.ntu.edu.tw/.

  1. Combining features in a graphical model to predict protein binding sites.

    Science.gov (United States)

    Wierschin, Torsten; Wang, Keyu; Welter, Marlon; Waack, Stephan; Stanke, Mario

    2015-05-01

    Large efforts have been made in classifying residues as binding sites in proteins using machine learning methods. The prediction task can be translated into the computational challenge of assigning each residue the label binding site or non-binding site. Observational data comes from various possibly highly correlated sources. It includes the structure of the protein but not the structure of the complex. The model class of conditional random fields (CRFs) has previously successfully been used for protein binding site prediction. Here, a new CRF-approach is presented that models the dependencies of residues using a general graphical structure defined as a neighborhood graph and thus our model makes fewer independence assumptions on the labels than sequential labeling approaches. A novel node feature "change in free energy" is introduced into the model, which is then denoted by ΔF-CRF. Parameters are trained with an online large-margin algorithm. Using the standard feature class relative accessible surface area alone, the general graph-structure CRF already achieves higher prediction accuracy than the linear chain CRF of Li et al. ΔF-CRF performs significantly better on a large range of false positive rates than the support-vector-machine-based program PresCont of Zellner et al. on a homodimer set containing 128 chains. ΔF-CRF has a broader scope than PresCont since it is not constrained to protein subgroups and requires no multiple sequence alignment. The improvement is attributed to the advantageous combination of the novel node feature with the standard feature and to the adopted parameter training method.

  2. Splice site prediction in Arabidopsis thaliana pre-mRNA by combining local and global sequence information

    DEFF Research Database (Denmark)

    Hebsgaard, Stefan M.; Korning, Peter G.; Tolstrup, Niels

    1996-01-01

    splice sites normally haunting splice site prediction. An analysis of the errors made by the networks in the first step of the method revealed a previously unknown feature, a frequent T-tract prolongation containing cryptic acceptor sites in the 5'end of exons. The method presented here has been compared...

  3. Short communication: genetic variability in the predicted microRNA target sites of caprine casein genes.

    Science.gov (United States)

    Zidi, A; Amills, M; Tomás, A; Vidal, O; Ramírez, O; Carrizosa, J; Urrutia, B; Serradilla, J M; Clop, A

    2010-04-01

    The main goal of the current work was to identify single nucleotide polymorphisms (SNP) that might create or disrupt microRNA (miRNA) target sites in the caprine casein genes. The 3' untranslated regions of the goat alpha(S1)-, alpha(S2)-, beta-, and kappa-casein genes (CSN1S1, CSN1S2, CSN2, and CSN3, respectively) were resequenced in 25 individuals of the Murciano-Granadina, Cashmere, Canarian, Saanen, and Sahelian breeds. Five SNP were identified through this strategy: c.175C>T at CSN1S1; c.109T>C, c.139G>C, and c.160T>C at CSN1S2; and c.216C>T at CSN2. Analysis with the Patrocles Finder tool predicted that all of these SNP are located within regions complementary to the seed of diverse miRNA sequences. These in silico results suggest that polymorphism at miRNA target sites might have some effect on casein expression. We explored this issue by genotyping the c.175C>T SNP (CSN1S1) in 85 Murciano-Granadina goats with records for milk CSN1S1 concentrations. This substitution destroys a putative target site for miR-101, a miRNA known to be expressed in the bovine mammary gland. Although TT goats had higher levels (6.25 g/L) of CSN1S1 than their CT (6.05 g/L) and CC (6.04 g/L) counterparts, these differences were not significant. Experimental confirmation of the miRNA target sites predicted in the current work and performance of additional association analyses in other goat populations will be an essential step to find out if polymorphic miRNA target sites constitute an important source of variation in casein expression.

  4. Predicting sites of new hemorrhage with amyloid imaging in cerebral amyloid angiopathy

    Science.gov (United States)

    Dierksen, Gregory; Betensky, Rebecca; Gidicsin, Christopher; Halpin, Amy; Becker, Alex; Carmasin, Jeremy; Ayres, Alison; Schwab, Kristin; Viswanathan, Anand; Salat, David; Rosand, Jonathan; Johnson, Keith A.; Greenberg, Steven M.

    2012-01-01

    Objective: We aimed to determine whether amyloid imaging can help predict the location and number of future hemorrhages in cerebral amyloid angiopathy (CAA). Methods: We performed a longitudinal cohort study of 11 patients with CAA without dementia who underwent serial brain MRIs after baseline amyloid imaging with Pittsburgh compound B (PiB). Mean distribution volume ratio (DVR) of PiB was determined at the sites of new micro/macrobleeds identified on follow-up MRI and compared with PiB retention at “simulated” hemorrhages, randomly placed in the same subjects using a probability distribution map of CAA-hemorrhage location. Mean PiB retention at the sites of observed new bleeds was also compared to that in shells concentrically surrounding the bleeds. Finally the association between number of incident bleeds and 3 regional amyloid measures were obtained. Results: Nine of 11 subjects had at least one new microbleed on follow-up MRI (median 4, interquartile range [IQR] 1–9) and 2 had 5 new intracerebral hemorrhages. Mean DVR was greater at the sites of incident bleeds (1.34, 95% confidence interval [CI] 1.23–1.46) than simulated lesions (1.14, 95% CI 1.07–1.22, p < 0.0001) in multivariable models. PiB retention decreased with increasing distance from sites of observed bleeds (p < 0.0001). Mean DVR in a superior frontal/parasagittal region of interest correlated independently with number of future hemorrhages after adjustment for relevant covariates (p = 0.003). Conclusions: Our results provide direct evidence that new CAA-related hemorrhages occur preferentially at sites of increased amyloid deposition and suggest that PiB-PET imaging may be a useful tool in prediction of incident hemorrhages in patients with CAA. PMID:22786597

  5. Rapid and accurate prediction and scoring of water molecules in protein binding sites.

    Directory of Open Access Journals (Sweden)

    Gregory A Ross

    Full Text Available Water plays a critical role in ligand-protein interactions. However, it is still challenging to predict accurately not only where water molecules prefer to bind, but also which of those water molecules might be displaceable. The latter is often seen as a route to optimizing affinity of potential drug candidates. Using a protocol we call WaterDock, we show that the freely available AutoDock Vina tool can be used to predict accurately the binding sites of water molecules. WaterDock was validated using data from X-ray crystallography, neutron diffraction and molecular dynamics simulations and correctly predicted 97% of the water molecules in the test set. In addition, we combined data-mining, heuristic and machine learning techniques to develop probabilistic water molecule classifiers. When applied to WaterDock predictions in the Astex Diverse Set of protein ligand complexes, we could identify whether a water molecule was conserved or displaced to an accuracy of 75%. A second model predicted whether water molecules were displaced by polar groups or by non-polar groups to an accuracy of 80%. These results should prove useful for anyone wishing to undertake rational design of new compounds where the displacement of water molecules is being considered as a route to improved affinity.

  6. A homology-based pipeline for global prediction of post-translational modification sites

    Science.gov (United States)

    Chen, Xiang; Shi, Shao-Ping; Xu, Hao-Dong; Suo, Sheng-Bao; Qiu, Jian-Ding

    2016-05-01

    The pathways of protein post-translational modifications (PTMs) have been shown to play particularly important roles for almost any biological process. Identification of PTM substrates along with information on the exact sites is fundamental for fully understanding or controlling biological processes. Alternative computational strategies would help to annotate PTMs in a high-throughput manner. Traditional algorithms are suited for identifying the common organisms and tissues that have a complete PTM atlas or extensive experimental data. While annotation of rare PTMs in most organisms is a clear challenge. In this work, to this end we have developed a novel homology-based pipeline named PTMProber that allows identification of potential modification sites for most of the proteomes lacking PTMs data. Cross-promotion E-value (CPE) as stringent benchmark has been used in our pipeline to evaluate homology to known modification sites. Independent-validation tests show that PTMProber achieves over 58.8% recall with high precision by CPE benchmark. Comparisons with other machine-learning tools show that PTMProber pipeline performs better on general predictions. In addition, we developed a web-based tool to integrate this pipeline at http://bioinfo.ncu.edu.cn/PTMProber/index.aspx. In addition to pre-constructed prediction models of PTM, the website provides an extensional functionality to allow users to customize models.

  7. The Prediction of Calpain Cleavage Sites with the mRMR and IFS Approaches

    Directory of Open Access Journals (Sweden)

    Wenyi Zhang

    2013-01-01

    Full Text Available Calpains are an important family of the Ca2+-dependent cysteine proteases which catalyze the limited proteolysis of many specific substrates. Calpains play crucial roles in basic physiological and pathological processes, and identification of the calpain cleavage sites may facilitate the understanding of the molecular mechanisms and biological function. But traditional experiment approaches to predict the sites are accurate, and are always labor-intensive and time-consuming. Thus, it is common to see that computational methods receive increasing attention due to their convenience and fast speed in recent years. In this study, we develop a new predictor based on the support vector machine (SVM with the maximum relevance minimum redundancy (mRMR method followed by incremental feature selection (IFS. And we concern the feature of physicochemical/biochemical properties, sequence conservation, residual disorder, secondary structure, and solvent accessibility to represent the calpain cleavage sites. Experimental results show that the performance of our predictor is better than several other state-of- the-art predictors, whose average prediction accuracy is 79.49%, sensitivity is 62.31%, and specificity is 88.12%. Since user-friendly and publicly accessible web servers represent the future direction for developing practically more useful predictors, here we have provided a web-server for the method presented in this paper.

  8. Homology modeling and functional sites prediction of azoreductase enzyme from the cyanobacterium Nostoc sp. PCC7120.

    Science.gov (United States)

    Devi, Philem Priyadarshini; Adhikari, Samrat

    2012-12-01

    Industrial dyes such as azodyes are potential environmental pollutants causing deleterious health hazards complications. These dyes are potentially degraded by azoreductase enzyme which is widely distributed in bacteria and also cyanobacteria. The azoreductase enzymes from cyanobacteria have not been explored in detail. Hence this enzyme from Nostoc sp. PCC 7120 has been addressed in detail in the present study considering to explore the physico-chemical properties, evolutionary relationships, functional sites and structural properties using various bioinformatics tools. Four conserved regions were obtained from the multiple sequence analysis. The multiple sequence alignment showed conserved regions at different stretches from 1-11, 40-57, 82-120 and 161-177 amino acid residues. These regions could be used for designing degenerate primers or probes for PCR-based amplification or hybridization-based detection of azoreductase sequences from different source organisms. Domain analysis and functional site prediction showed the presence of functional sites and domain such as flavodoxin like fold responsible for enzyme activity. 3D model was constructed and the best model was selected and validated. Superimposition of the final structure and the template showed variations in certain regions which might be involved in the accommodation of various dyes. Our results may be helpful for further investigations like docking studies as well as in vivo and in vitro conditions although these predictions still need to be studied.

  9. Impediments to predicting site response: Seismic property estimation and modeling simplifications

    Science.gov (United States)

    Thompson, E.M.; Baise, L.G.; Kayen, R.E.; Guzina, B.B.

    2009-01-01

    We compare estimates of the empirical transfer function (ETF) to the plane SH-wave theoretical transfer function (TTF) within a laterally constant medium for invasive and noninvasive estimates of the seismic shear-wave slownesses at 13 Kiban-Kyoshin network stations throughout Japan. The difference between the ETF and either of the TTFs is substantially larger than the difference between the two TTFs computed from different estimates of the seismic properties. We show that the plane SH-wave TTF through a laterally homogeneous medium at vertical incidence inadequately models observed amplifications at most sites for both slowness estimates, obtained via downhole measurements and the spectral analysis of surface waves. Strategies to improve the predictions can be separated into two broad categories: improving the measurement of soil properties and improving the theory that maps the 1D soil profile onto spectral amplification. Using an example site where the 1D plane SH-wave formulation poorly predicts the ETF, we find a more satisfactory fit to the ETF by modeling the full wavefield and incorporating spatially correlated variability of the seismic properties. We conclude that our ability to model the observed site response transfer function is limited largely by the assumptions of the theoretical formulation rather than the uncertainty of the soil property estimates.

  10. LIGSITEcsc: predicting ligand binding sites using the Connolly surface and degree of conservation

    Directory of Open Access Journals (Sweden)

    Schroeder Michael

    2006-09-01

    Full Text Available Abstract Background Identifying pockets on protein surfaces is of great importance for many structure-based drug design applications and protein-ligand docking algorithms. Over the last ten years, many geometric methods for the prediction of ligand-binding sites have been developed. Results We present LIGSITEcsc, an extension and implementation of the LIGSITE algorithm. LIGSITEcsc is based on the notion of surface-solvent-surface events and the degree of conservation of the involved surface residues. We compare our algorithm to four other approaches, LIGSITE, CAST, PASS, and SURFNET, and evaluate all on a dataset of 48 unbound/bound structures and 210 bound-structures. LIGSITEcsc performs slightly better than the other tools and achieves a success rate of 71% and 75%, respectively. Conclusion The use of the Connolly surface leads to slight improvements, the prediction re-ranking by conservation to significant improvements of the binding site predictions. A web server for LIGSITEcsc and its source code is available at scoppi.biotec.tu-dresden.de/pocket.

  11. A Large-Scale Assessment of Nucleic Acids Binding Site Prediction Programs.

    Directory of Open Access Journals (Sweden)

    Zhichao Miao

    2015-12-01

    Full Text Available Computational prediction of nucleic acid binding sites in proteins are necessary to disentangle functional mechanisms in most biological processes and to explore the binding mechanisms. Several strategies have been proposed, but the state-of-the-art approaches display a great diversity in i the definition of nucleic acid binding sites; ii the training and test datasets; iii the algorithmic methods for the prediction strategies; iv the performance measures and v the distribution and availability of the prediction programs. Here we report a large-scale assessment of 19 web servers and 3 stand-alone programs on 41 datasets including more than 5000 proteins derived from 3D structures of protein-nucleic acid complexes. Well-defined binary assessment criteria (specificity, sensitivity, precision, accuracy… are applied. We found that i the tools have been greatly improved over the years; ii some of the approaches suffer from theoretical defects and there is still room for sorting out the essential mechanisms of binding; iii RNA binding and DNA binding appear to follow similar driving forces and iv dataset bias may exist in some methods.

  12. Prediction of TF target sites based on atomistic models of protein-DNA complexes

    Directory of Open Access Journals (Sweden)

    Collado-Vides Julio

    2008-10-01

    Full Text Available Abstract Background The specific recognition of genomic cis-regulatory elements by transcription factors (TFs plays an essential role in the regulation of coordinated gene expression. Studying the mechanisms determining binding specificity in protein-DNA interactions is thus an important goal. Most current approaches for modeling TF specific recognition rely on the knowledge of large sets of cognate target sites and consider only the information contained in their primary sequence. Results Here we describe a structure-based methodology for predicting sequence motifs starting from the coordinates of a TF-DNA complex. Our algorithm combines information regarding the direct and indirect readout of DNA into an atomistic statistical model, which is used to estimate the interaction potential. We first measure the ability of our method to correctly estimate the binding specificities of eight prokaryotic and eukaryotic TFs that belong to different structural superfamilies. Secondly, the method is applied to two homology models, finding that sampling of interface side-chain rotamers remarkably improves the results. Thirdly, the algorithm is compared with a reference structural method based on contact counts, obtaining comparable predictions for the experimental complexes and more accurate sequence motifs for the homology models. Conclusion Our results demonstrate that atomic-detail structural information can be feasibly used to predict TF binding sites. The computational method presented here is universal and might be applied to other systems involving protein-DNA recognition.

  13. Selection and Assessment of Predictions of the Mars Pathfinder Landing Site

    Science.gov (United States)

    Golombek, M. P.; Moore, H. J.; Haldemann, A. F. C.; Cook, R. A.; Parker, T. J.; Schofield, J. T.

    1998-01-01

    The successful landing of the Mars Pathfinder spacecraft on Mars allows the review of the process of selecting the landing site and assessing predictions made for the site based on Viking and Earth-based data. Selection of the landing site for Mars Pathfinder was a two-phase process. The first phase took place from October 1993 to June 1994 and involved: initial identification of engineering constraints, definition of environmental conditions at the site for spacecraft design, and evaluation of the scientific potential of different landing sites. This phase culminated with the first "Mars Pathfinder Landing Site Workshop", held at the Lunar and Planetary Institute in Houston, Texas on April 18-19, 1994, in which suggested approaches and landing sites were solicited from the entire scientific community. A preliminary site was selected by the project for design purposes in June 1994. The second phase took place from July 1994 to March 1996 and involved: developing criteria for evaluating site safety using images and remote sensing data, testing of the spacecraft and landing subsystems (with design improvements) to establish quantitative engineering constraints on landing site characteristics, evaluating all potential landing sites on Mars, and certification of the site by the project. This phase included a second open workshop, "Mars Pathfinder Landing Site Workshop II: Characteristics of the Ares Vallis Region and Field Trips in the Channeled Scabland, Washington" held in Spokane and Moses Lake September 24-30, 1995 and formal acceptance of the site by NASA Headquarters. Engineering constraints on Pathfinder landing sites were developed from the initial design of the spacecraft and the entry, descent and landing scenario. The site must be within 5 degrees of the subsolar latitude at the time of landing (15N for maximum solar power and flexible communications with Earth. It also must be below 0 km elevation to enable enough time for the parachute to bring the lander

  14. RADIOLYTIC HYDROGEN GENERATION INSAVANNAH RIVER SITE (SRS) HIGH LEVEL WASTETANKS COMPARISON OF SRS AND HANFORDMODELING PREDICTIONS

    Energy Technology Data Exchange (ETDEWEB)

    Crawford, C; Ned Bibler, N

    2009-04-15

    In the high level waste tanks at the Savannah River Site (SRS), hydrogen is produced continuously by interaction of the radiation in the tank with water in the waste. Consequently, the vapor spaces of the tanks are purged to prevent the accumulation of H{sub 2} and possible formation of a flammable mixture in a tank. Personnel at SRS have developed an empirical model to predict the rate of H{sub 2} formation in a tank. The basis of this model is the prediction of the G value for H{sub 2} production. This G value is the number of H{sub 2} molecules produced per 100 eV of radiolytic energy absorbed by the waste. Based on experimental studies it was found that the G value for H{sub 2} production from beta radiation and from gamma radiation were essentially equal. The G value for H{sub 2} production from alpha radiation was somewhat higher. Thus, the model has two equations, one for beta/gamma radiation and one for alpha radiation. Experimental studies have also indicated that both G values are decreased by the presence of nitrate and nitrite ions in the waste. These are the main scavengers for the precursors of H{sub 2} in the waste; thus the equations that were developed predict G values for hydrogen production as a function of the concentrations of these two ions in waste. Knowing the beta/gamma and alpha heat loads in the waste allows one to predict the total generation rate for hydrogen in a tank. With this prediction a ventilation rate can be established for each tank to ensure that a flammable mixture is not formed in the vapor space in a tank. Recently personnel at Hanford have developed a slightly different model for predicting hydrogen G values. Their model includes the same precursor for H{sub 2} as the SRS model but also includes an additional precursor not in the SRS model. Including the second precursor for H{sub 2} leads to different empirical equations for predicting the G values for H{sub 2} as a function of the nitrate and nitrite concentrations in

  15. Archaeology Through Computational Linguistics: Inscription Statistics Predict Excavation Sites of Indus Valley Artifacts.

    Science.gov (United States)

    Recchia, Gabriel L; Louwerse, Max M

    2016-11-01

    Computational techniques comparing co-occurrences of city names in texts allow the relative longitudes and latitudes of cities to be estimated algorithmically. However, these techniques have not been applied to estimate the provenance of artifacts with unknown origins. Here, we estimate the geographic origin of artifacts from the Indus Valley Civilization, applying methods commonly used in cognitive science to the Indus script. We show that these methods can accurately predict the relative locations of archeological sites on the basis of artifacts of known provenance, and we further apply these techniques to determine the most probable excavation sites of four sealings of unknown provenance. These findings suggest that inscription statistics reflect historical interactions among locations in the Indus Valley region, and they illustrate how computational methods can help localize inscribed archeological artifacts of unknown origin. The success of this method offers opportunities for the cognitive sciences in general and for computational anthropology specifically.

  16. Big-Five Personality Prediction Based on User Behaviors at Social Network Sites

    CERN Document Server

    Bai, Shuotian; Cheng, Li

    2012-01-01

    Many customer services are already available at Social Network Sites (SNSs), including user recommendation and media interaction, to name a few. There are strong desires to provide online users more dedicated and personalized services that fit into individual's need, usually strongly depending on the inner personalities of the user. However, little has been done to conduct proper psychological analysis, crucial for explaining the user's outer behaviors from their inner personality. In this paper, we propose an approach that intends to facilitate this line of research by directly predicting the so called Big-Five Personality from user's SNS behaviors. Comparing to the conventional inventory-based psychological analysis, we demonstrate via experimental studies that users' personalities can be predicted with reasonable precision based on their online behaviors. Except for proving some former behavior-personality correlation results, our experiments show that extraversion is positively related to one's status rep...

  17. Prediction, conservation analysis, and structural characterization of mammalian mucin-type O-glycosylation sites

    DEFF Research Database (Denmark)

    Julenius, Karin; Mølgaard, Anne; Gupta, Ramneek

    2005-01-01

    O-GalNAc-glycosylation is one of the main types of glycosylation in mammalian cells. No consensus recognition sequence for the O-glycosyltransferases is known, making prediction methods necessary to bridge the gap between the large number of known protein sequences and the small number of proteins...... experimentally investigated with regard to glycosylation status. From O-GLYCBASE a total of 86 mammalian proteins experimentally investigated for in vivo O-GalNAc sites were extracted. Mammalian protein homolog comparisons showed that a glycosylated serine or threonine is less likely to be precisely conserved...

  18. Evaluation of the DayCent model to predict carbon fluxes in French crop sites

    Science.gov (United States)

    Fujisaki, Kenji; Martin, Manuel P.; Zhang, Yao; Bernoux, Martial; Chapuis-Lardy, Lydie

    2017-04-01

    Croplands in temperate regions are an important component of the carbon balance and can act as a sink or a source of carbon, depending on pedoclimatic conditions and management practices. Therefore the evaluation of carbon fluxes in croplands by modelling approach is relevant in the context of global change. This study was part of the Comete-Global project funded by the multi-Partner call FACCE JPI. Carbon fluxes, net ecosystem exchange (NEE), leaf area index (LAI), biomass, and grain production were simulated at the site level in three French crop experiments from the CarboEurope project. Several crops were studied, like winter wheat, rapeseed, barley, maize, and sunflower. Daily NEE was measured with eddy covariance and could be partitioned between gross primary production (GPP) and total ecosystem respiration (TER). Measurements were compared to DayCent simulations, a process-based model predicting plant production and soil organic matter turnover at daily time step. We compared two versions of the model: the original one with a simplified plant module and a newer version that simulates LAI. Input data for modelling were soil properties, climate, and management practices. Simulations of grain yields and biomass production were acceptable when using optimized crop parameters. Simulation of NEE was also acceptable. GPP predictions were improved with the newer version of the model, eliminating temporal shifts that could be observed with the original model. TER was underestimated by the model. Predicted NEE was more sensitive to soil tillage and nitrogen applications than measured NEE. DayCent was therefore a relevant tool to predict carbon fluxes in French crops at the site level. The introduction of LAI in the model improved its performance.

  19. Predicting Protein-Protein Interaction Sites with a Novel Membership Based Fuzzy SVM Classifier.

    Science.gov (United States)

    Sriwastava, Brijesh K; Basu, Subhadip; Maulik, Ujjwal

    2015-01-01

    Predicting residues that participate in protein-protein interactions (PPI) helps to identify, which amino acids are located at the interface. In this paper, we show that the performance of the classical support vector machine (SVM) algorithm can further be improved with the use of a custom-designed fuzzy membership function, for the partner-specific PPI interface prediction problem. We evaluated the performances of both classical SVM and fuzzy SVM (F-SVM) on the PPI databases of three different model proteomes of Homo sapiens, Escherichia coli and Saccharomyces Cerevisiae and calculated the statistical significance of the developed F-SVM over classical SVM algorithm. We also compared our performance with the available state-of-the-art fuzzy methods in this domain and observed significant performance improvements. To predict interaction sites in protein complexes, local composition of amino acids together with their physico-chemical characteristics are used, where the F-SVM based prediction method exploits the membership function for each pair of sequence fragments. The average F-SVM performance (area under ROC curve) on the test samples in 10-fold cross validation experiment are measured as 77.07, 78.39, and 74.91 percent for the aforementioned organisms respectively. Performances on independent test sets are obtained as 72.09, 73.24 and 82.74 percent respectively. The software is available for free download from http://code.google.com/p/cmater-bioinfo.

  20. The effects of reading comprehension and launch site on frequency-predictability interactions during paragraph reading.

    Science.gov (United States)

    Whitford, Veronica; Titone, Debra

    2014-01-01

    We used eye movement measures of paragraph reading to examine whether word frequency and predictability interact during the earliest stages of lexical processing, with a specific focus on whether these effects are modulated by individual differences in reading comprehension or launch site (i.e., saccade length between the prior and currently fixated word--a proxy for the amount of parafoveal word processing). The joint impact of frequency and predictability on reading will elucidate whether these variables additively or multiplicatively affect the earliest stages of lexical access, which, in turn, has implications for computational models of eye movements during reading. Linear mixed effects models revealed additive effects during both early- and late-stage reading, where predictability effects were comparable for low- and high-frequency words. Moreover, less cautious readers (e.g., readers who engaged in skimming, scanning, mindless reading) demonstrated smaller frequency effects than more cautious readers. Taken together, our findings suggest that during extended reading, frequency and predictability exert additive influences on lexical and postlexical processing, and that individual differences in reading comprehension modulate sensitivity to the effects of word frequency.

  1. Caspase cleavage sites in the human proteome: CaspDB, a database of predicted substrates.

    Directory of Open Access Journals (Sweden)

    Sonu Kumar

    Full Text Available Caspases are enzymes belonging to a conserved family of cysteine-dependent aspartic-specific proteases that are involved in vital cellular processes and play a prominent role in apoptosis and inflammation. Determining all relevant protein substrates of caspases remains a challenging task. Over 1500 caspase substrates have been discovered in the human proteome according to published data and new substrates are discovered on a daily basis. To aid the discovery process we developed a caspase cleavage prediction method using the recently published curated MerCASBA database of experimentally determined caspase substrates and a Random Forest classification method. On both internal and external test sets, the ranking of predicted cleavage positions is superior to all previously developed prediction methods. The in silico predicted caspase cleavage positions in human proteins are available from a relational database: CaspDB. Our database provides information about potential cleavage sites in a verified set of all human proteins collected in Uniprot and their orthologs, allowing for tracing of cleavage motif conservation. It also provides information about the positions of disease-annotated single nucleotide polymorphisms, and posttranslational modifications that may modulate the caspase cleaving efficiency.

  2. Predictability of bone density at posterior mandibular implant sites using cone-beam computed tomography intensity values.

    Science.gov (United States)

    Alkhader, Mustafa; Hudieb, Malik; Khader, Yousef

    2017-01-01

    The aim of this study was to investigate the predictability of bone density at posterior mandibular implant sites using cone-beam computed tomography (CBCT) intensity values. CBCT cross-sectional images for 436 posterior mandibular implant sites were selected for the study. Using Invivo software (Anatomage, San Jose, California, USA), two observers classified the bone density into three categories: low, intermediate, and high, and CBCT intensity values were generated. Based on the consensus of the two observers, 15.6% of sites were of low bone density, 47.9% were of intermediate density, and 36.5% were of high density. Receiver-operating characteristic analysis showed that CBCT intensity values had a high predictive power for predicting high density sites (area under the curve [AUC] =0.94, P density sites (AUC = 0.81, P density sites was 218 (sensitivity = 0.77 and specificity = 0.76) and the best cut-off value for intensity to predict high density sites was 403 (sensitivity = 0.93 and specificity = 0.77). CBCT intensity values are considered useful for predicting bone density at posterior mandibular implant sites.

  3. Prediction of extreme wind velocity at the site of the Runyang Suspension Bridge

    Institute of Scientific and Technical Information of China (English)

    Yang DENG; You-liang DING; Ai-qun LI; Guang-dong ZHOU

    2011-01-01

    This paper presents a distribution free method for predicting the extreme wind velocity from wind monitoring data at the site of the Runyang Suspension Bridge (RSB),China using the maximum entropy theory.The maximum entropy theory is a rational approach for choosing the most unbiased probability distribution from a small sample,which is consistent with available data and contains a minimum of spurious information.In this paper,the theory is used for estimating a joint probability density function considering the combined action of wind speed and direction based on statistical analysis of wind monitoring data at the site of the RSB.The joint probability distribution model is further used to estimate the extreme wind velocity at the deck level of the RSB.The results of the analysis reveal that the probability density function of the maximum entropy method achieves a result that fits well with the monitoring data.Hypothesis testing shows that the distributions of the wind velocity data collected during the past three years do not obey the Gumbel distribution.Finally,our comparison shows that the wind predictions of the maximum entropy method are higher than that of the Gumbel distribution,but much lower than the design wind speed.

  4. No site unseen: predicting the failure to control problematic Internet use among young adults.

    Science.gov (United States)

    Yamada, Tetsuhiro; Moshier, Samantha J; Otto, Michael W

    2016-11-01

    Problematic Internet use has been associated with the neglect of valued activities such as work, exercise, social activities, and relationships. In the present study, we expanded the understanding of problematic Internet use by identifying an important predictor of the inability to curb Internet use despite the desire to do so. Specifically, in a college student sample reporting a mean of 27.8 h of recreational Internet use in the past week, we investigated the role of distress intolerance (DI)-an individual difference variable that refers to the inability of an individual to tolerate emotional discomfort and to engage in goal-directed behavior when distressed-to predict the failure to meet personal restrictions on Internet use. Consistent with hypotheses, DI emerged as a significant predictor of the failure to meet self-control goals in both bivariate and multivariate models, indicating that DI offers unique prediction of self-control failure with problematic Internet use. Given that DI is a modifiable trait, these results encourage consideration of DI-focused early intervention strategies.

  5. Computational Prediction of O-linked Glycosylation Sites that Preferentially Map on Intrinsically Disordered Regions of Extracellular Proteins

    Directory of Open Access Journals (Sweden)

    Satoshi Fukuchi

    2010-12-01

    Full Text Available O-glycosylation of mammalian proteins is one of the important posttranslational modifications. We applied a support vector machine (SVM to predict whether Ser or Thr is glycosylated, in order to elucidate the O-glycosylation mechanism. O-glycosylated sites were often found clustered along the sequence, whereas other sites were located sporadically. Therefore, we developed two types of SVMs for predicting clustered and isolated sites separately. We found that the amino acid composition was effective for predicting the clustered type, whereas the site-specific algorithm was effective for the isolated type. The highest prediction accuracy for the clustered type was 74%, while that for the isolated type was 79%. The existence frequency of amino acids around the O-glycosylation sites was different in the two types: namely, Pro, Val and Ala had high existence probabilities at each specific position relative to a glycosylation site, especially for the isolated type. Independent component analyses for the amino acid sequences around O-glycosylation sites showed the position-specific existences of the identified amino acids as independent components. The O-glycosylation sites were preferentially located within intrinsically disordered regions of extracellular proteins: particularly, more than 90% of the clustered O-GalNAc glycosylation sites were observed in intrinsically disordered regions. This feature could be the key for understanding the non-conservation property of O-glycosylation, and its role in functional diversity and structural stability.

  6. Identification of co-regulated genes through Bayesian clustering of predicted regulatory binding sites.

    Science.gov (United States)

    Qin, Zhaohui S; McCue, Lee Ann; Thompson, William; Mayerhofer, Linda; Lawrence, Charles E; Liu, Jun S

    2003-04-01

    The identification of co-regulated genes and their transcription-factor binding sites (TFBS) are key steps toward understanding transcription regulation. In addition to effective laboratory assays, various computational approaches for the detection of TFBS in promoter regions of coexpressed genes have been developed. The availability of complete genome sequences combined with the likelihood that transcription factors and their cognate sites are often conserved during evolution has led to the development of phylogenetic footprinting. The modus operandi of this technique is to search for conserved motifs upstream of orthologous genes from closely related species. The method can identify hundreds of TFBS without prior knowledge of co-regulation or coexpression. Because many of these predicted sites are likely to be bound by the same transcription factor, motifs with similar patterns can be put into clusters so as to infer the sets of co-regulated genes, that is, the regulons. This strategy utilizes only genome sequence information and is complementary to and confirmative of gene expression data generated by microarray experiments. However, the limited data available to characterize individual binding patterns, the variation in motif alignment, motif width, and base conservation, and the lack of knowledge of the number and sizes of regulons make this inference problem difficult. We have developed a Gibbs sampling-based Bayesian motif clustering (BMC) algorithm to address these challenges. Tests on simulated data sets show that BMC produces many fewer errors than hierarchical and K-means clustering methods. The application of BMC to hundreds of predicted gamma-proteobacterial motifs correctly identified many experimentally reported regulons, inferred the existence of previously unreported members of these regulons, and suggested novel regulons.

  7. Prediction of O-glycosylation Sites Using Random Forest and GA-Tuned PSO Technique.

    Science.gov (United States)

    Hassan, Hebatallah; Badr, Amr; Abdelhalim, M B

    2015-01-01

    O-glycosylation is one of the main types of the mammalian protein glycosylation; it occurs on the particular site of serine (S) or threonine (T). Several O-glycosylation site predictors have been developed. However, a need to get even better prediction tools remains. One challenge in training the classifiers is that the available datasets are highly imbalanced, which makes the classification accuracy for the minority class to become unsatisfactory. In our previous work, we have proposed a new classification approach, which is based on particle swarm optimization (PSO) and random forest (RF); this approach has considered the imbalanced dataset problem. The PSO parameters setting in the training process impacts the classification accuracy. Thus, in this paper, we perform parameters optimization for the PSO algorithm, based on genetic algorithm, in order to increase the classification accuracy. Our proposed genetic algorithm-based approach has shown better performance in terms of area under the receiver operating characteristic curve against existing predictors. In addition, we implemented a glycosylation predictor tool based on that approach, and we demonstrated that this tool could successfully identify candidate glycosylation sites in case study protein.

  8. Feature Selection Combined with Neural Network Structure Optimization for HIV-1 Protease Cleavage Site Prediction

    Directory of Open Access Journals (Sweden)

    Hui Liu

    2015-01-01

    Full Text Available It is crucial to understand the specificity of HIV-1 protease for designing HIV-1 protease inhibitors. In this paper, a new feature selection method combined with neural network structure optimization is proposed to analyze the specificity of HIV-1 protease and find the important positions in an octapeptide that determined its cleavability. Two kinds of newly proposed features based on Amino Acid Index database plus traditional orthogonal encoding features are used in this paper, taking both physiochemical and sequence information into consideration. Results of feature selection prove that p2, p1, p1′, and p2′ are the most important positions. Two feature fusion methods are used in this paper: combination fusion and decision fusion aiming to get comprehensive feature representation and improve prediction performance. Decision fusion of subsets that getting after feature selection obtains excellent prediction performance, which proves feature selection combined with decision fusion is an effective and useful method for the task of HIV-1 protease cleavage site prediction. The results and analysis in this paper can provide useful instruction and help designing HIV-1 protease inhibitor in the future.

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

    KAUST Repository

    Wong, Aloysius Tze

    2015-06-09

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

  10. Predicting and mapping potential Whooping Crane stopover habitat to guide site selection for wind energy projects.

    Science.gov (United States)

    Belaire, J Amy; Kreakie, Betty J; Keitt, Timothy; Minor, Emily

    2014-04-01

    Migratory stopover habitats are often not part of planning for conservation or new development projects. We identified potential stopover habitats within an avian migratory flyway and demonstrated how this information can guide the site-selection process for new development. We used the random forests modeling approach to map the distribution of predicted stopover habitat for the Whooping Crane (Grus americana), an endangered species whose migratory flyway overlaps with an area where wind energy development is expected to become increasingly important. We then used this information to identify areas for potential wind power development in a U.S. state within the flyway (Nebraska) that minimize conflicts between Whooping Crane stopover habitat and the development of clean, renewable energy sources. Up to 54% of our study area was predicted to be unsuitable as Whooping Crane stopover habitat and could be considered relatively low risk for conflicts between Whooping Cranes and wind energy development. We suggest that this type of analysis be incorporated into the habitat conservation planning process in areas where incidental take permits are being considered for Whooping Cranes or other species of concern. Field surveys should always be conducted prior to construction to verify model predictions and understand baseline conditions.

  11. Conserved functional motifs and homology modelling to predict hidden moonlighting functional sites

    Directory of Open Access Journals (Sweden)

    Helen R Irving

    2015-06-01

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

  12. A Model for Predicting Late Prehistoric Architectural Sites at the Pinon Canyon Maneuver Site in Southeastern Colorado

    Science.gov (United States)

    2007-01-01

    Archaic. This suggests that vegetal materials, possibly including maize, and other cultigens probably constituted larger portions of the human diet ...placement of rock art has been demonstrated in Upper Paleolithic sites of Europe, as well as in North America (Waller 1993). Open-air sites near canyons

  13. Prediction of P53 mutants (multiple sites transcriptional activity based on structural (2D&3D properties.

    Directory of Open Access Journals (Sweden)

    R Geetha Ramani

    Full Text Available Prediction of secondary site mutations that reinstate mutated p53 to normalcy has been the focus of intense research in the recent past owing to the fact that p53 mutants have been implicated in more than half of all human cancers and restoration of p53 causes tumor regression. However laboratory investigations are more often laborious and resource intensive but computational techniques could well surmount these drawbacks. In view of this, we formulated a novel approach utilizing computational techniques to predict the transcriptional activity of multiple site (one-site to five-site p53 mutants. The optimal MCC obtained by the proposed approach on prediction of one-site, two-site, three-site, four-site and five-site mutants were 0.775,0.341,0.784,0.916 and 0.655 respectively, the highest reported thus far in literature. We have also demonstrated that 2D and 3D features generate higher prediction accuracy of p53 activity and our findings revealed the optimal results for prediction of p53 status, reported till date. We believe detection of the secondary site mutations that suppress tumor growth may facilitate better understanding of the relationship between p53 structure and function and further knowledge on the molecular mechanisms and biological activity of p53, a targeted source for cancer therapy. We expect that our prediction methods and reported results may provide useful insights on p53 functional mechanisms and generate more avenues for utilizing computational techniques in biological data analysis.

  14. Integrated Model of DNA Sequence Numerical Representation and Artificial Neural Network for Human Donor and Acceptor Sites Prediction

    Directory of Open Access Journals (Sweden)

    Mohammed Abo-Zahhad

    2014-07-01

    Full Text Available Human Genome Project has led to a huge inflow of genomic data. After the completion of human genome sequencing, more and more effort is being put into identification of splicing sites of exons and introns (donor and acceptor sites. These invite bioinformatics to analysis the genome sequences and identify the location of exon and intron boundaries or in other words prediction of splicing sites. Prediction of splice sites in genic regions of DNA sequence is one of the most challenging aspects of gene structure recognition. Over the last two decades, artificial neural networks gradually became one of the essential tools in bioinformatics. In this paper artificial neural networks with different numerical mapping techniques have been employed for building integrated model for splice site prediction in genes. An artificial neural network is trained and then used to find splice sites in human genes. A comparison between different mapping methods using trained neural network in terms of their precision in prediction of donor and acceptor sites will be presented in this paper. Training and measuring performance of neural network are carried out using sequences of the human genome (GRch37/hg19- chr21. Simulation results indicate that using Electron-Ion Interaction Potential numerical mapping method with neural network yields to the best performance in prediction.

  15. Evaluation of different approaches for identifying optimal sites to predict mean hillslope soil moisture content

    Science.gov (United States)

    Liao, Kaihua; Zhou, Zhiwen; Lai, Xiaoming; Zhu, Qing; Feng, Huihui

    2017-04-01

    The identification of representative soil moisture sampling sites is important for the validation of remotely sensed mean soil moisture in a certain area and ground-based soil moisture measurements in catchment or hillslope hydrological studies. Numerous approaches have been developed to identify optimal sites for predicting mean soil moisture. Each method has certain advantages and disadvantages, but they have rarely been evaluated and compared. In our study, surface (0-20 cm) soil moisture data from January 2013 to March 2016 (a total of 43 sampling days) were collected at 77 sampling sites on a mixed land-use (tea and bamboo) hillslope in the hilly area of Taihu Lake Basin, China. A total of 10 methods (temporal stability (TS) analyses based on 2 indices, K-means clustering based on 6 kinds of inputs and 2 random sampling strategies) were evaluated for determining optimal sampling sites for mean soil moisture estimation. They were TS analyses based on the smallest index of temporal stability (ITS, a combination of the mean relative difference and standard deviation of relative difference (SDRD)) and based on the smallest SDRD, K-means clustering based on soil properties and terrain indices (EFs), repeated soil moisture measurements (Theta), EFs plus one-time soil moisture data (EFsTheta), and the principal components derived from EFs (EFs-PCA), Theta (Theta-PCA), and EFsTheta (EFsTheta-PCA), and global and stratified random sampling strategies. Results showed that the TS based on the smallest ITS was better (RMSE = 0.023 m3 m-3) than that based on the smallest SDRD (RMSE = 0.034 m3 m-3). The K-means clustering based on EFsTheta (-PCA) was better (RMSE sampling design stratified by the land use was more efficient than the global random method. Forty and 60 sampling sites are needed for stratified sampling and global sampling respectively to make their performances comparable to the best K-means method (EFsTheta-PCA). Overall, TS required only one site, but its

  16. Predicted effectiveness of in-situ activated carbon amendment for field sediment sites with variable site- and compound-specific characteristics

    Energy Technology Data Exchange (ETDEWEB)

    Choi, Yongju, E-mail: ychoi81@snu.ac.kr [Department of Civil and Environmental Engineering, Seoul National University, Seoul 151-744 (Korea, Republic of); Cho, Yeo-Myoung; Luthy, Richard G. [Department of Civil and Environmental Engineering, Stanford University, Stanford, CA 94305-4020 (United States); Werner, David [School of Civil Engineering and Geosciences, Newcastle University, Newcastle upon Tyne NE1 7RU (United Kingdom)

    2016-01-15

    Highlights: • The model accounts for the heterogeneity of AC distribution in field applications. • AC amendment effectiveness is predicted for ten sediment sites. • An HOC mass transfer model and calibrated parameters provide reliable predictions. • AC amendment is predicted to be effective for most sites. • K{sub ow}, K{sub d}, and equilibrium-based calculations are useful indicators. - Abstract: A growing body of evidence shows that the effectiveness of in-situ activated carbon (AC) amendment to treat hydrophobic organic contaminants (HOCs) in sediments can be reliably predicted using a mass transfer modeling approach. This study analyzes available field data for characterizing AC-sediment distribution after mechanical mixing of AC into sediment. Those distributions are used to develop an HOC mass transfer model that accounts for plausible heterogeneities resulting from mixing of AC into sediment. The model is applied to ten field sites in the U.S. and Europe with 2–3 representative HOCs from each site using site- and HOC-specific model parameters collected from the literature. The model predicts that the AC amendment reduces the pore-water HOC concentrations by more than 95% fifteen years after AC deployment for 18 of the 25 total simulated cases when the AC is applied at doses of 1.5 times sediment total organic carbon content with an upper limit of 5 dry wt%. The predicted effectiveness shows negative correlation with the HOC octanol–water partitioning coefficients and the sediment-water distribution coefficients, and positive correlation with the effectiveness calculated based on equilibrium coefficients of sediment and AC, suggesting the possibility for use of the values for screening-level assessments.

  17. Impulse propagation over a complex site: a comparison of experimental results and numerical predictions.

    Science.gov (United States)

    Dragna, Didier; Blanc-Benon, Philippe; Poisson, Franck

    2014-03-01

    Results from outdoor acoustic measurements performed in a railway site near Reims in France in May 2010 are compared to those obtained from a finite-difference time-domain solver of the linearized Euler equations. During the experiments, the ground profile and the different ground surface impedances were determined. Meteorological measurements were also performed to deduce mean vertical profiles of wind and temperature. An alarm pistol was used as a source of impulse signals and three microphones were located along a propagation path. The various measured parameters are introduced as input data into the numerical solver. In the frequency domain, the numerical results are in good accordance with the measurements up to a frequency of 2 kHz. In the time domain, except a time shift, the predicted waveforms match the measured waveforms with a close agreement.

  18. Prediction of primate splice site using inhomogeneous Markov chain and neural network.

    Science.gov (United States)

    Liu, Libin; Ho, Yee-Kin; Yau, Stephen

    2007-07-01

    The inhomogeneous Markov chain model is used to discriminate acceptor and donor sites in genomic DNA sequences. It outperforms statistical methods such as homogeneous Markov chain model, higher order Markov chain and interpolated Markov chain models, and machine-learning methods such as k-nearest neighbor and support vector machine as well. Besides its high accuracy, another advantage of inhomogeneous Markov chain model is its simplicity in computation. In the three states system (acceptor, donor, and neither), the inhomogeneous Markov chain model is combined with a three-layer feed forward neural network. Using this combined system 3175 primate splice-junction gene sequences have been tested, with a prediction accuracy of greater than 98%.

  19. Gene Expression-Based Survival Prediction in Lung Adenocarcinoma: A Multi-Site, Blinded Validation Study

    Science.gov (United States)

    Shedden, Kerby; Taylor, Jeremy M.G.; Enkemann, Steve A.; Tsao, Ming S.; Yeatman, Timothy J.; Gerald, William L.; Eschrich, Steve; Jurisica, Igor; Venkatraman, Seshan E.; Meyerson, Matthew; Kuick, Rork; Dobbin, Kevin K.; Lively, Tracy; Jacobson, James W.; Beer, David G.; Giordano, Thomas J.; Misek, David E.; Chang, Andrew C.; Zhu, Chang Qi; Strumpf, Dan; Hanash, Samir; Shepherd, Francis A.; Ding, Kuyue; Seymour, Lesley; Naoki, Katsuhiko; Pennell, Nathan; Weir, Barbara; Verhaak, Roel; Ladd-Acosta, Christine; Golub, Todd; Gruidl, Mike; Szoke, Janos; Zakowski, Maureen; Rusch, Valerie; Kris, Mark; Viale, Agnes; Motoi, Noriko; Travis, William; Sharma, Anupama

    2009-01-01

    Although prognostic gene expression signatures for survival in early stage lung cancer have been proposed, for clinical application it is critical to establish their performance across different subject populations and in different laboratories. Here we report a large, training-testing, multi-site blinded validation study to characterize the performance of several prognostic models based on gene expression for 442 lung adenocarcinomas. The hypotheses proposed examined whether microarray measurements of gene expression either alone or combined with basic clinical covariates (stage, age, sex) can be used to predict overall survival in lung cancer subjects. Several models examined produced risk scores that substantially correlated with actual subject outcome. Most methods performed better with clinical data, supporting the combined use of clinical and molecular information when building prognostic models for early stage lung cancer. This study also provides the largest available set of microarray data with extensive pathological and clinical annotation for lung adenocarcinomas. PMID:18641660

  20. ChloroP, a neural network-based method for predicting chloroplast transitpeptides and their cleavage sites

    DEFF Research Database (Denmark)

    Emanuelsson, O.; Nielsen, Henrik; von Heijne, Gunnar

    1999-01-01

    We present a neural network based method (ChloroP) for identifying chloroplast transit peptides and their cleavage sites. Using cross-validation, 88% of the sequences in our homology reduced training set were correctly classified as transit peptides or nontransit peptides. This performance level...... is well above that of the publicly available chloroplast localization predictor PSORT. Cleavage sites are predicted using a scoring matrix derived by an automatic motif-finding algorithm. Approximately 60% of the known cleavage sites in our sequence collection were predicted to within +/-2 residues from...

  1. Cell-type specificity of ChIP-predicted transcription factor binding sites

    Directory of Open Access Journals (Sweden)

    Håndstad Tony

    2012-08-01

    Full Text Available Abstract Background Context-dependent transcription factor (TF binding is one reason for differences in gene expression patterns between different cellular states. Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq identifies genome-wide TF binding sites for one particular context—the cells used in the experiment. But can such ChIP-seq data predict TF binding in other cellular contexts and is it possible to distinguish context-dependent from ubiquitous TF binding? Results We compared ChIP-seq data on TF binding for multiple TFs in two different cell types and found that on average only a third of ChIP-seq peak regions are common to both cell types. Expectedly, common peaks occur more frequently in certain genomic contexts, such as CpG-rich promoters, whereas chromatin differences characterize cell-type specific TF binding. We also find, however, that genotype differences between the cell types can explain differences in binding. Moreover, ChIP-seq signal intensity and peak clustering are the strongest predictors of common peaks. Compared with strong peaks located in regions containing peaks for multiple transcription factors, weak and isolated peaks are less common between the cell types and are less associated with data that indicate regulatory activity. Conclusions Together, the results suggest that experimental noise is prevalent among weak peaks, whereas strong and clustered peaks represent high-confidence binding events that often occur in other cellular contexts. Nevertheless, 30-40% of the strongest and most clustered peaks show context-dependent regulation. We show that by combining signal intensity with additional data—ranging from context independent information such as binding site conservation and position weight matrix scores to context dependent chromatin structure—we can predict whether a ChIP-seq peak is likely to be present in other cellular contexts.

  2. SNP2TFBS – a database of regulatory SNPs affecting predicted transcription factor binding site affinity

    Science.gov (United States)

    Kumar, Sunil; Ambrosini, Giovanna; Bucher, Philipp

    2017-01-01

    SNP2TFBS is a computational resource intended to support researchers investigating the molecular mechanisms underlying regulatory variation in the human genome. The database essentially consists of a collection of text files providing specific annotations for human single nucleotide polymorphisms (SNPs), namely whether they are predicted to abolish, create or change the affinity of one or several transcription factor (TF) binding sites. A SNP's effect on TF binding is estimated based on a position weight matrix (PWM) model for the binding specificity of the corresponding factor. These data files are regenerated at regular intervals by an automatic procedure that takes as input a reference genome, a comprehensive SNP catalogue and a collection of PWMs. SNP2TFBS is also accessible over a web interface, enabling users to view the information provided for an individual SNP, to extract SNPs based on various search criteria, to annotate uploaded sets of SNPs or to display statistics about the frequencies of binding sites affected by selected SNPs. Homepage: http://ccg.vital-it.ch/snp2tfbs/. PMID:27899579

  3. Prediction of evacuation time for emergency planning zone of Uljin nuclear site

    Energy Technology Data Exchange (ETDEWEB)

    Jeon, In Young; Lee, Jai Ki [Hanyang Univ., Seoul (Korea, Republic of)

    2002-09-15

    The time for evacuation of residents in Emergency Planning Zone (EPZ) of Uljin nuclear site in case of a radiological emergency was estimated with traffic analysis. Evacuees were classified into 4 groups by considering population density, local jurisdictions, and whether they are residents or transients. The survey to investigate the behavioral characteristics of the residents was made for 200 households and included a hypothetical scenario explaining the accident situation and questions such as dwelling place, time demand for evacuation preparation, transportation means for evacuation, sheltering place, and evacuation direction. The microscopic traffic simulation model, CORSIM, was used to simulate the behavior of evacuating vehicles on networks. The results showed that the evacuation time required for total vehicles to move out from EPZ took longer in the daytime than at night in spite that the delay times at intersections were longer at night than in the daytime. This was analyzed due to the differences of the trip generation time distribution. To validate whether the CORSIM model can appropriately simulate the congested traffic phenomena assumable in case of emergency, a benchmark study was conducted at an intersection without an actuated traffic signal near Uljin site during the traffic peak-time in the morning. This study indicated that the predicted output by the CORSIM model was in good agreement with the observed data, satisfying the purpose of this study.

  4. GPS-SUMO: a tool for the prediction of sumoylation sites and SUMO-interaction motifs.

    Science.gov (United States)

    Zhao, Qi; Xie, Yubin; Zheng, Yueyuan; Jiang, Shuai; Liu, Wenzhong; Mu, Weiping; Liu, Zexian; Zhao, Yong; Xue, Yu; Ren, Jian

    2014-07-01

    Small ubiquitin-like modifiers (SUMOs) regulate a variety of cellular processes through two distinct mechanisms, including covalent sumoylation and non-covalent SUMO interaction. The complexity of SUMO regulations has greatly hampered the large-scale identification of SUMO substrates or interaction partners on a proteome-wide level. In this work, we developed a new tool called GPS-SUMO for the prediction of both sumoylation sites and SUMO-interaction motifs (SIMs) in proteins. To obtain an accurate performance, a new generation group-based prediction system (GPS) algorithm integrated with Particle Swarm Optimization approach was applied. By critical evaluation and comparison, GPS-SUMO was demonstrated to be substantially superior against other existing tools and methods. With the help of GPS-SUMO, it is now possible to further investigate the relationship between sumoylation and SUMO interaction processes. A web service of GPS-SUMO was implemented in PHP+JavaScript and freely available at http://sumosp.biocuckoo.org.

  5. PreTIS: A Tool to Predict Non-canonical 5’ UTR Translational Initiation Sites in Human and Mouse

    Science.gov (United States)

    Reuter, Kerstin; Helms, Volkhard

    2016-01-01

    Translation of mRNA sequences into proteins typically starts at an AUG triplet. In rare cases, translation may also start at alternative non–AUG codons located in the annotated 5’ UTR which leads to an increased regulatory complexity. Since ribosome profiling detects translational start sites at the nucleotide level, the properties of these start sites can then be used for the statistical evaluation of functional open reading frames. We developed a linear regression approach to predict in–frame and out–of–frame translational start sites within the 5’ UTR from mRNA sequence information together with their translation initiation confidence. Predicted start codons comprise AUG as well as near–cognate codons. The underlying datasets are based on published translational start sites for human HEK293 and mouse embryonic stem cells that were derived by the original authors from ribosome profiling data. The average prediction accuracy of true vs. false start sites for HEK293 cells was 80%. When applied to mouse mRNA sequences, the same model predicted translation initiation sites observed in mouse ES cells with an accuracy of 76%. Moreover, we illustrate the effect of in silico mutations in the flanking sequence context of a start site on the predicted initiation confidence. Our new webservice PreTIS visualizes alternative start sites and their respective ORFs and predicts their ability to initiate translation. Solely, the mRNA sequence is required as input. PreTIS is accessible at http://service.bioinformatik.uni-saarland.de/pretis. PMID:27768687

  6. Preparing to return to the Moon: Lessons from science-driven analogue missions to the Mistastin Lake impact structure, Canada, a unique lunar analogue site

    Science.gov (United States)

    Osinski, G. R.; Barfoot, T.; Chanou, A.; Daly, M. G.; Francis, R.; Hodges, K. V.; Jolliff, B. L.; Mader, M. M.; McCullough, E. M.; Moores, J. E.; Pickersgill, A.; Pontefract, A.; Preston, L.; Shankar, B.; Singleton, A.; Sylvester, P.; Tornabene, L. L.; Young, K. E.

    2013-12-01

    Impact cratering is the dominant geological process on the Moon, Near Earth Asteroids (NEAs) and the moons of Mars - the objectives for the new Solar System Exploration Research Virtual Institute (SSERVI). Led by members of the Canadian Lunar Research Network (CLRN), funded by the Canadian Space Agency, and with participants from the U.S., we carried out a series of analogue missions on Earth in order to prepare and train for future potential robotic and human sample return missions. Critically, these analogue missions were driven by the paradigm that operational and technical objectives are conducted while conducting new science and addressing real overarching scientific objectives. An overarching operational goal was to assess the utility of a robotic field reconnaissance mission as a precursor to a human sortie sample return mission. Here, we focus on the results and lessons learned from a robotic precursor mission and follow on human-robotic mission to the Mistastin Lake impact structure in Labrador, northern Canada (55°53'N; 63°18'W). The Mistastin structure was chosen because it represents an exceptional analogue for lunar craters. This site includes both an anorthositic target, a central uplift, well-preserved impact melt rocks - mostly derived from melting anorthosite - and is (or was) relatively unexplored. This crater formed ~36 million years ago and has a diameter of ~28 km. The scientific goals for these analogue missions were to further our understanding of impact chronology, shock processes, impact ejecta and potential resources within impact craters. By combining these goals in an analogue mission campaign key scientific requirements for a robotic precursor were determined. From the outset, these analogue missions were formulated and executed like an actual space mission. Sites of interest were chosen using remote sensing imagery without a priori knowledge of the site through a rigorous site selection process. The first deployment occurred in

  7. Cytoplasmic retention of Xenopus nuclear factor 7 before the mid blastula transition uses a unique anchoring mechanism involving a retention domain and several phosphorylation sites.

    Science.gov (United States)

    Li, X; Shou, W; Kloc, M; Reddy, B A; Etkin, L D

    1994-01-01

    Xenopus nuclear factor 7 (xnf7) is a maternally expressed protein that belongs to the B-box zinc finger gene family consisting of transcription factors, protooncogenes, and ribonucleoproteins. Its function is regulated by retention in the cytoplasm from oocyte maturation until the mid blastula transition (MBT) when it reenters the nucleus. We defined a 22-amino acid cytoplasmic retention domain (CRD) in xnf7 that functioned cooperatively with two phosphorylation sites within the xnf7 molecule to retain the protein in the cytoplasm until the MBT. Deletion of this region or mutations in the phosphorylation sites resulted in the early entry of xnf7 into the nucleus. A mutation changing one of the phosphorylation sites to a glutamic acid resulted in the prolonged retention of the xnf7 protein in the cytoplasm until stages 9-10, well past the MBT. Additionally, a mutant form of xnf7 possessing a second nuclear localization signal at the COOH terminus was retained in the cytoplasm. This suggests that retention of xnf7 was not due to the masking of its NLS as is the case with NFkB and dorsal but was due to a novel anchoring mechanism in which the CRD interacts with an anchor protein. The CRD sequence is also found in another B-box zinc finger protein that is also retained in the cytoplasm until the MBT in the newt. Therefore, we believe that this may be an important mechanism whereby the function of a number of nuclear proteins is regulated during development.

  8. Epsilon glutathione transferases possess a unique class-conserved subunit interface motif that directly interacts with glutathione in the active site.

    Science.gov (United States)

    Wongsantichon, Jantana; Robinson, Robert C; Ketterman, Albert J

    2015-10-20

    Epsilon class glutathione transferases (GSTs) have been shown to contribute significantly to insecticide resistance. We report a new Epsilon class protein crystal structure from Drosophila melanogaster for the glutathione transferase DmGSTE6. The structure reveals a novel Epsilon clasp motif that is conserved across hundreds of millions of years of evolution of the insect Diptera order. This histidine-serine motif lies in the subunit interface and appears to contribute to quaternary stability as well as directly connecting the two glutathiones in the active sites of this dimeric enzyme. © 2015 Authors.

  9. Prospective Observational Study of Single-Site Multiport Per-umbilical Laparoscopic Endosurgery versus Conventional Multiport Laparoscopic Cholecystectomy: Critical Appraisal of a Unique Umbilical Approach

    Directory of Open Access Journals (Sweden)

    Priyadarshan Anand Jategaonkar

    2014-01-01

    Full Text Available Purpose. This prospective observational study compares an innovative approach of Single-Site Multi-Port Per-umbilical Laparoscopic Endo-surgery (SSMPPLE cholecystectomy with the gold standard—Conventional Multi-port Laparoscopic Cholecystectomy (CMLC—to assess the feasibility and efficacy of the former. Methods. In all, 646 patients were studied. SSMPPLE cholecystectomy utilized three ports inserted through three independent mini-incisions at the umbilicus. Only the day-to-day rigid laparoscopic instruments were used in all cases. The SSMPPLE cholecystectomy group had 320 patients and the CMLC group had 326 patients. The outcomes were statistically compared. Results. SSMPPLE cholecystectomy had average operative time of 43.8 min and blood loss of 9.4 mL. Their duration of hospitalization was 1.3 days (range, 1–5. Six patients (1.9% of this group were converted to CMLC. Eleven patients had controlled gallbladder perforations at dissection. The Visual Analogue Scores for pain on postoperative days 0 and 7, the operative time, and the scar grades were significantly better for SSMPPLE than CMLC. However, umbilical sepsis and seroma outcomes were similar. We had no bile-duct injuries or port-site hernias in this study. Conclusion. SSMPPLE cholecystectomy approach complies with the principles of laparoscopic triangulation; it seems feasible and safe method of minimally invasive cholecystectomy. Overall, it has a potential to emerge as an economically viable alternative to single-port surgery.

  10. Prediction of protein modification sites of pyrrolidone carboxylic acid using mRMR feature selection and analysis.

    Directory of Open Access Journals (Sweden)

    Lu-Lu Zheng

    Full Text Available Pyrrolidone carboxylic acid (PCA is formed during a common post-translational modification (PTM of extracellular and multi-pass membrane proteins. In this study, we developed a new predictor to predict the modification sites of PCA based on maximum relevance minimum redundancy (mRMR and incremental feature selection (IFS. We incorporated 727 features that belonged to 7 kinds of protein properties to predict the modification sites, including sequence conservation, residual disorder, amino acid factor, secondary structure and solvent accessibility, gain/loss of amino acid during evolution, propensity of amino acid to be conserved at protein-protein interface and protein surface, and deviation of side chain carbon atom number. Among these 727 features, 244 features were selected by mRMR and IFS as the optimized features for the prediction, with which the prediction model achieved a maximum of MCC of 0.7812. Feature analysis showed that all feature types contributed to the modification process. Further site-specific feature analysis showed that the features derived from PCA's surrounding sites contributed more to the determination of PCA sites than other sites. The detailed feature analysis in this paper might provide important clues for understanding the mechanism of the PCA formation and guide relevant experimental validations.

  11. Interactome-wide prediction of protein-protein binding sites reveals effects of protein sequence variation in Arabidopsis thaliana.

    Directory of Open Access Journals (Sweden)

    Felipe Leal Valentim

    Full Text Available The specificity of protein-protein interactions is encoded in those parts of the sequence that compose the binding interface. Therefore, understanding how changes in protein sequence influence interaction specificity, and possibly the phenotype, requires knowing the location of binding sites in those sequences. However, large-scale detection of protein interfaces remains a challenge. Here, we present a sequence- and interactome-based approach to mine interaction motifs from the recently published Arabidopsis thaliana interactome. The resultant proteome-wide predictions are available via www.ab.wur.nl/sliderbio and set the stage for further investigations of protein-protein binding sites. To assess our method, we first show that, by using a priori information calculated from protein sequences, such as evolutionary conservation and residue surface accessibility, we improve the performance of interface prediction compared to using only interactome data. Next, we present evidence for the functional importance of the predicted sites, which are under stronger selective pressure than the rest of protein sequence. We also observe a tendency for compensatory mutations in the binding sites of interacting proteins. Subsequently, we interrogated the interactome data to formulate testable hypotheses for the molecular mechanisms underlying effects of protein sequence mutations. Examples include proteins relevant for various developmental processes. Finally, we observed, by analysing pairs of paralogs, a correlation between functional divergence and sequence divergence in interaction sites. This analysis suggests that large-scale prediction of binding sites can cast light on evolutionary processes that shape protein-protein interaction networks.

  12. Geodiversity of Island-type Tidal Flats of Korea: Their Uniqueness and Potential to be Inscribed as a World Heritage Site

    Science.gov (United States)

    Woo, K. S.; Chun, S. S.; Moon, K. O.

    2016-12-01

    Over one thousand rocky islands are distributed along the coast of the Korean Peninsula. Many of these islands form are covered by muddy sediments as tidal flats. These `Island-type Tidal Flats' (ITF) have developed due to the decreasing accommodation space during the slow Late Holocene sea-level rise on the broad epicontinental shelf. Sedimentation and evolution show a variety of quite distinctive tidal flat patterns with intertidal and subtidal drainage systems depending upon the location and orientation of rocky shores. They are constantly influenced by the seasonal reversals of monsoonal winds, and are characterized by distinctive depositional settings such as of archipelago type (Shinan Archipelago), estuary type (Yuboodo Island, Seocheon), open bay type (Gochang) and semi-closed bay type (Boseong and Suncheon). Upper intertidal zone dips gently seaward with numerous intertidal creeks. The sediments progressively coarsen seaward from almost pure mud near shores, through mixed-flats (sandy mud and muddy sand) to sand flats with numerous tidal channels towards sea. The dominant sedimentary facies of upper tidal flats consist of homogeneous mud (highly bioturbated) and thinly interlaminated sand/mud to coarsely interlaminated sand/mud (wavy and lenticular bedding) showing seasonal stratification. Surface topography of lower intertidal flats shows landward migrating sand-bar complexes. The ITF is the only place in the world where tide-controlled sedimentation processes have produced special tidal flats surrounding numerous rocky islands on a broad epicontinental shelf. Macrotidal currents combined with waves and typhoons in this semi-closed oceanographic setting have provided unique geological and oceanographic conditions for their formation. We strongly believe that the ITF has great potential to be inscribed on a World Heritage List for the criteria (vii), (viii), (ix) and (x).

  13. Geodiversity of Island-type tidal flat of Korea: Their uniqueness and potential to be inscribed as a World Heritage site

    Science.gov (United States)

    Woo, Kyung Sik; Chun, Seung Soo; Monn, Kyong O.

    2017-04-01

    Over one thousand rocky islands are distributed along the coast of the Korean Peninsula. Many of these islands form are covered by muddy sediments as tidal flats. These 'Island-type Tidal Flats' (ITF) have developed due to the decreasing accommodation space during the slow Late Holocene sea-level rise on the broad epicontinental shelf. Sedimentation and evolution show a variety of quite distinctive tidal flat patterns with intertidal and subtidal drainage systems depending upon the location and orientation of rocky shores. They are constantly influenced by the seasonal reversals of monsoonal winds, and are characterized by distinctive depositional settings such as of archipelago type (Shinan Archipelago), estuary type (Yuboodo Island, Seocheon), open bay type (Gochang) and semi-closed bay type (Boseong and Suncheon). Upper intertidal zone dips gently seaward with numerous intertidal creeks. The sediments progressively coarsen seaward from almost pure mud near shores, through mixed-flats (sandy mud and muddy sand) to sand flats with numerous tidal channels towards sea. The dominant sedimentary facies of upper tidal flats consist of homogeneous mud (highly bioturbated) and thinly interlaminated sand/mud to coarsely interlaminated sand/mud (wavy and lenticular bedding) showing seasonal stratification. Surface topography of lower intertidal flats shows landward migrating sand-bar complexes. The ITF is the only place in the world where tide-controlled sedimentation processes have produced special tidal flats surrounding numerous rocky islands on a broad epicontinental shelf. Macrotidal currents combined with waves and typhoons in this semi-closed oceanographic setting have provided unique geological and oceanographic conditions for their formation. We strongly believe that the ITF has great potential to be inscribed on a World Heritage List for the criteria (vii), (viii), (ix) and (x).

  14. Protein-Protein Interaction Site Predictions with Three-Dimensional Probability Distributions of Interacting Atoms on Protein Surfaces

    Science.gov (United States)

    Chen, Ching-Tai; Peng, Hung-Pin; Jian, Jhih-Wei; Tsai, Keng-Chang; Chang, Jeng-Yih; Yang, Ei-Wen; Chen, Jun-Bo; Ho, Shinn-Ying; Hsu, Wen-Lian; Yang, An-Suei

    2012-01-01

    Protein-protein interactions are key to many biological processes. Computational methodologies devised to predict protein-protein interaction (PPI) sites on protein surfaces are important tools in providing insights into the biological functions of proteins and in developing therapeutics targeting the protein-protein interaction sites. One of the general features of PPI sites is that the core regions from the two interacting protein surfaces are complementary to each other, similar to the interior of proteins in packing density and in the physicochemical nature of the amino acid composition. In this work, we simulated the physicochemical complementarities by constructing three-dimensional probability density maps of non-covalent interacting atoms on the protein surfaces. The interacting probabilities were derived from the interior of known structures. Machine learning algorithms were applied to learn the characteristic patterns of the probability density maps specific to the PPI sites. The trained predictors for PPI sites were cross-validated with the training cases (consisting of 432 proteins) and were tested on an independent dataset (consisting of 142 proteins). The residue-based Matthews correlation coefficient for the independent test set was 0.423; the accuracy, precision, sensitivity, specificity were 0.753, 0.519, 0.677, and 0.779 respectively. The benchmark results indicate that the optimized machine learning models are among the best predictors in identifying PPI sites on protein surfaces. In particular, the PPI site prediction accuracy increases with increasing size of the PPI site and with increasing hydrophobicity in amino acid composition of the PPI interface; the core interface regions are more likely to be recognized with high prediction confidence. The results indicate that the physicochemical complementarity patterns on protein surfaces are important determinants in PPIs, and a substantial portion of the PPI sites can be predicted correctly with

  15. Sequence-specific flexibility organization of splicing flanking sequence and prediction of splice sites in the human genome.

    Science.gov (United States)

    Zuo, Yongchun; Zhang, Pengfei; Liu, Li; Li, Tao; Peng, Yong; Li, Guangpeng; Li, Qianzhong

    2014-09-01

    More and more reported results of nucleosome positioning and histone modifications showed that DNA structure play a well-established role in splicing. In this study, a set of DNA geometric flexibility parameters originated from molecular dynamics (MD) simulations were introduced to discuss the structure organization around splice sites at the DNA level. The obtained profiles of specific flexibility/stiffness around splice sites indicated that the DNA physical-geometry deformation could be used as an alternative way to describe the splicing junction region. In combination with structural flexibility as discriminatory parameter, we developed a hybrid computational model for predicting potential splicing sites. And the better prediction performance was achieved when the benchmark dataset evaluated. Our results showed that the mechanical deformability character of a splice junction is closely correlated with both the splice site strength and structural information in its flanking sequences.

  16. Predicting transcription factor binding sites using local over-representation and comparative genomics

    Directory of Open Access Journals (Sweden)

    Touzet Hélène

    2006-08-01

    Full Text Available Abstract Background Identifying cis-regulatory elements is crucial to understanding gene expression, which highlights the importance of the computational detection of overrepresented transcription factor binding sites (TFBSs in coexpressed or coregulated genes. However, this is a challenging problem, especially when considering higher eukaryotic organisms. Results We have developed a method, named TFM-Explorer, that searches for locally overrepresented TFBSs in a set of coregulated genes, which are modeled by profiles provided by a database of position weight matrices. The novelty of the method is that it takes advantage of spatial conservation in the sequence and supports multiple species. The efficiency of the underlying algorithm and its robustness to noise allow weak regulatory signals to be detected in large heterogeneous data sets. Conclusion TFM-Explorer provides an efficient way to predict TFBS overrepresentation in related sequences. Promising results were obtained in a variety of examples in human, mouse, and rat genomes. The software is publicly available at http://bioinfo.lifl.fr/TFM-Explorer.

  17. COMPARATIVE MODELLING AND LIGAND BINDING SITE PREDICTION OF A FAMILY 43 GLYCOSIDE HYDROLASE FROM Clostridium thermocellum

    Directory of Open Access Journals (Sweden)

    Shadab Ahmed

    2012-06-01

    Full Text Available The phylogenetic analysis of Clostridium thermocellum family 43 glycoside hydrolase (CtGH43 showed close evolutionary relation with carbohydrate binding family 6 proteins from C. cellulolyticum, C. papyrosolvens, C. cellulyticum, and A. cellulyticum. Comparative modeling of CtGH43 was performed based on crystal structures with PDB IDs 3C7F, 1YIF, 1YRZ, 2EXH and 1WL7. The structure having lowest MODELLER objective function was selected. The three-dimensional structure revealed typical 5-fold beta–propeller architecture. Energy minimization and validation of predicted model with VERIFY 3D indicated acceptability of the proposed atomic structure. The Ramachandran plot analysis by RAMPAGE confirmed that family 43 glycoside hydrolase (CtGH43 contains little or negligible segments of helices. It also showed that out of 301 residues, 267 (89.3% were in most favoured region, 23 (7.7% were in allowed region and 9 (3.0% were in outlier region. IUPred analysis of CtGH43 showed no disordered region. Active site analysis showed presence of two Asp and one Glu, assumed to form a catalytic triad. This study gives us information about three-dimensional structure and reaffirms the fact that it has the similar core 5-fold beta–propeller architecture and so probably has the same inverting mechanism of action with the formation of above mentioned catalytic triad for catalysis of polysaccharides.

  18. Genome wide prediction of HNF4alpha functional binding sites by the use of local and global sequence context.

    Science.gov (United States)

    Kel, Alexander E; Niehof, Monika; Matys, Volker; Zemlin, Rüdiger; Borlak, Jürgen

    2008-01-01

    We report an application of machine learning algorithms that enables prediction of the functional context of transcription factor binding sites in the human genome. We demonstrate that our method allowed de novo identification of hepatic nuclear factor (HNF)4alpha binding sites and significantly improved an overall recognition of faithful HNF4alpha targets. When applied to published findings, an unprecedented high number of false positives were identified. The technique can be applied to any transcription factor.

  19. A new method for splice site prediction based on the sequence patterns of splicing signals and regulatory elements

    Institute of Scientific and Technical Information of China (English)

    SUN ZongXiao; SANG LingJie; JU LiNing; ZHU HuaiQiu

    2008-01-01

    It is of significance for splice site prediction to develop novel algorithms that combine the sequence patterns of regulatory elements such as enhancers and silencers with the patterns of splicing signals. In this paper, a statistical model of splicing signals was built based on the entropy density profile (EDP) method, weight array method (WAM) and κ test; moreover, the model of splicing regulatory elements was developed by an unsupervised self-learning method to detect motifs associated with regulatory elements. With two models incorporated, a multi-level support vector machine (SVM) system was de-vised to perform ab initio prediction for splice sites originating from DNA sequence in eukaryotic ge-home. Results of large scale tests on human genomic splice sites show that the new method achieves a comparative high performance in splice site prediction. The method is demonstrated to be with at least the same level of performance and usually better performance than the existing SpliceScan method based on modeling regulatory elements, and shown to have higher accuracies than the traditional methods with modeling splicing signals such as the GeneSplicer. In particular, the method has evident advantage over splice site prediction for the genes with lower GC content.

  20. Surface ozone in the Southern Hemisphere: 20 years of data from a site with a unique setting in El Tololo, Chile

    Science.gov (United States)

    Anet, Julien G.; Steinbacher, Martin; Gallardo, Laura; Velásquez Álvarez, Patricio A.; Emmenegger, Lukas; Buchmann, Brigitte

    2017-05-01

    The knowledge of surface ozone mole fractions and their global distribution is of utmost importance due to the impact of ozone on human health and ecosystems and the central role of ozone in controlling the oxidation capacity of the troposphere. The availability of long-term ozone records is far better in the Northern than in the Southern Hemisphere, and recent analyses of the seven accessible records in the Southern Hemisphere have shown inconclusive trends. Since late 1995, surface ozone is measured in situ at "El Tololo", a high-altitude (2200 m a.s.l.) and pristine station in Chile (30° S, 71° W). The dataset has been recently fully quality controlled and reprocessed. This study presents the observed ozone trends and annual cycles and identifies key processes driving these patterns. From 1995 to 2010, an overall positive trend of ˜ 0.7 ppb decade-1 is found. Strongest trends per season are observed in March and April. Highest mole fractions are observed in late spring (October) and show a strong correlation with ozone transported from the stratosphere down into the troposphere, as simulated with a model. Over the 20 years of observations, the springtime ozone maximum has shifted to earlier times in the year, which, again, is strongly correlated with a temporal shift in the occurrence of the maximum of simulated stratospheric ozone transport at the site. We conclude that background ozone at El Tololo is mainly driven by stratospheric intrusions rather than photochemical production from anthropogenic and biogenic precursors. The major footprint of the sampled air masses is located over the Pacific Ocean. Therefore, due to the negligible influence of local processes, the ozone record also allows studying the influence of El Niño and La Niña episodes on background ozone levels in South America. In agreement with previous studies, we find that, during La Niña conditions, ozone mole fractions reach higher levels than during El Niño conditions.

  1. Neural network model for the prediction of PM10 daily concentrations in two sites in the Western Mediterranean.

    Science.gov (United States)

    de Gennaro, Gianluigi; Trizio, Livia; Di Gilio, Alessia; Pey, Jorge; Pérez, Noemi; Cusack, Michael; Alastuey, Andrés; Querol, Xavier

    2013-10-01

    An artificial neural network (ANN) was developed and tested to forecast PM10 daily concentration in two contrasted environments in NE Spain, a regional background site (Montseny), and an urban background site (Barcelona-CSIC), which was highly influenced by vehicular emissions. In order to predict 24-h average PM10 concentrations, the artificial neural network previously developed by Caselli et al. (2009) was improved by using hourly PM concentrations and deterministic factors such as a Saharan dust alert. In particular, the model input data for prediction were the hourly PM10 concentrations 1-day in advance, local meteorological data and information about air masses origin. The forecasted performance indexes for both sites were calculated and they showed better results for the regional background site in Montseny (R(2)=0.86, SI=0.75) than for urban site in Barcelona (R(2)=0.73, SI=0.58), influenced by local and sometimes unexpected sources. Moreover, a sensitivity analysis conducted to understand the importance of the different variables included among the input data, showed that local meteorology and air masses origin are key factors in the model forecasts. This result explains the reason for the improvement of ANN's forecasting performance at the Montseny site with respect to the Barcelona site. Moreover, the artificial neural network developed in this work could prove useful to predict PM10 concentrations, especially, at regional background sites such as those on the Mediterranean Basin which are primarily affected by long-range transports. Hence, the artificial neural network presented here could be a powerful tool for obtaining real time information on air quality status and could aid stakeholders in their development of cost-effective control strategies.

  2. A new global database to improve predictions of permeability distribution in crystalline rocks at site scale

    Science.gov (United States)

    Achtziger-Zupančič, P.; Loew, S.; Mariéthoz, G.

    2017-05-01

    A comprehensive worldwide permeability data set has been compiled consisting of 29,000 in situ permeabilities from 221 publications and reports and delineating the permeability distribution in crystalline rocks into depths of 2000 meters below ground surface (mbgs). We analyze the influence of technical factors (measurement method, scale effects, preferential sampling, and hydraulic anisotropy) and geological factors (lithology, current stress regime, current seismotectonic activity, and long-term tectonogeological history) on the permeability distribution with depth, by using regression analysis and k-means clustering. The influence of preferential sampling and hydraulic anisotropy are negligible. A scale dependency is observed based on calculated rock test volumes equaling 0.6 orders of magnitude of permeability change per order of magnitude of rock volume tested. Based on the entire data set, permeability decreases as log(k) = -1.5 × log(z) - 16.3 with permeability k (m2) and positively increasing depth z (km), and depth is the main factor driving the permeability distribution. The permeability variance is about 2 orders of magnitude at all depths, presumably representing permeability variations around brittle fault zones. Permeability and specific yield/storage exhibit similar depth trends. While in the upper 200 mbgs fracture flow varies between confined and unconfined, we observe confined fracture and matrix flow below about 600 mbgs depth. The most important geological factors are current seismotectonic activity (determined by peak ground acceleration) and long-term tectonogeological history (determined by geological province). The impact of lithology is less important. Based on the regression coefficients derived for all the geological key factors, permeability ranges of crystalline rocks at site scale can be predicted. First tests with independent data sets are promising.

  3. MetalDetector v2.0: predicting the geometry of metal binding sites from protein sequence

    OpenAIRE

    Passerini, A; Lippi, M.; P. Frasconi

    2011-01-01

    MetalDetector identifies CYS and HIS involved in transition metal protein binding sites, starting from sequence alone. A major new feature of release 2.0 is the ability to predict which residues are jointly involved in the coordination of the same metal ion. The server is available at http://metaldetector.dsi.unifi.it/v2.0/.

  4. V S30, slope, H 800 and f 0: performance of various site-condition proxies in reducing ground-motion aleatory variability and predicting nonlinear site response

    Science.gov (United States)

    Derras, Boumédiène; Bard, Pierre-Yves; Cotton, Fabrice

    2017-09-01

    The aim of this paper is to investigate the ability of various site-condition proxies (SCPs) to reduce ground-motion aleatory variability and evaluate how SCPs capture nonlinearity site effects. The SCPs used here are time-averaged shear-wave velocity in the top 30 m ( V S30), the topographical slope (slope), the fundamental resonance frequency ( f 0) and the depth beyond which V s exceeds 800 m/s ( H 800). We considered first the performance of each SCP taken alone and then the combined performance of the 6 SCP pairs [ V S30- f 0], [ V S30- H 800], [ f 0-slope], [ H 800-slope], [ V S30-slope] and [ f 0- H 800]. This analysis is performed using a neural network approach including a random effect applied on a KiK-net subset for derivation of ground-motion prediction equations setting the relationship between various ground-motion parameters such as peak ground acceleration, peak ground velocity and pseudo-spectral acceleration PSA ( T), and M w, R JB, focal depth and SCPs. While the choice of SCP is found to have almost no impact on the median ground-motion prediction, it does impact the level of aleatory uncertainty. V S30 is found to perform the best of single proxies at short periods ( T < 0.6 s), while f 0 and H 800 perform better at longer periods; considering SCP pairs leads to significant improvements, with particular emphasis on [ V S30- H 800] and [ f 0-slope] pairs. The results also indicate significant nonlinearity on the site terms for soft sites and that the most relevant loading parameter for characterising nonlinear site response is the "stiff" spectral ordinate at the considered period.[Figure not available: see fulltext.

  5. Dynamic neural networks for real-time water level predictions of sewerage systems-covering gauged and ungauged sites

    Directory of Open Access Journals (Sweden)

    Yen-Ming Chiang

    2010-07-01

    Full Text Available In this research, we propose recurrent neural networks (RNNs to build a relationship between rainfalls and water level patterns of an urban sewerage system based on historical torrential rain/storm events. The RNN allows signals to propagate in both forward and backward directions, which offers the network dynamic memories. Besides, the information at the current time-step with a feedback operation can yield a time-delay unit that provides internal input information at the next time-step to effectively deal with time-varying systems. The RNN is implemented at both gauged and ungauged sites for 5-, 10-, 15-, and 20-min-ahead water level predictions. The results show that the RNN is capable of learning the nonlinear sewerage system and producing satisfactory predictions at the gauged sites. Concerning the ungauged sites, there are no historical data of water level to support prediction. In order to overcome such problem, a set of synthetic data, generated from a storm water management model (SWMM under cautious verification process of applicability based on the data from nearby gauging stations, are introduced as the learning target to the training procedure of the RNN and moreover evaluating the performance of the RNN at the ungauged sites. The results demonstrate that the potential role of the SWMM coupled with nearby rainfall and water level information can be of great use in enhancing the capability of the RNN at the ungauged sites. Hence we can conclude that the RNN is an effective and suitable model for successfully predicting the water levels at both gauged and ungauged sites in urban sewerage systems.

  6. Prediction of suspended-sediment concentrations at selected sites in the Fountain Creek watershed, Colorado, 2008-09

    Science.gov (United States)

    Stogner, Robert W.; Nelson, Jonathan M.; McDonald, Richard R.; Kinzel, Paul J.; Mau, David P.

    2013-01-01

    In 2008, the U.S. Geological Survey (USGS), in cooperation with Pikes Peak Area Council of Governments, Colorado Water Conservation Board, Colorado Springs City Engineering, and the Lower Arkansas Valley Water Conservancy District, began a small-scale pilot study to evaluate the effectiveness of the use of a computational model of streamflow and suspended-sediment transport for predicting suspended-sediment concentrations and loads in the Fountain Creek watershed in Colorado. Increased erosion and sedimentation damage have been identified by the Fountain Creek Watershed Plan as key problems within the watershed. A recommendation in the Fountain Creek Watershed plan for management of the basin is to establish measurable criteria to determine if progress in reducing erosion and sedimentation damage is being made. The major objective of this study was to test a computational method to predict local suspended-sediment loads at two sites with different geomorphic characteristics in order to evaluate the feasibility of using such an approach to predict local suspended-sediment loads throughout the entire watershed. Detailed topographic surveys, particle-size data, and suspended-sediment samples were collected at two gaged sites: Monument Creek above Woodmen Road at Colorado Springs, Colorado (USGS gage 07103970), and Sand Creek above mouth at Colorado Springs, Colorado (USGS gage 07105600). These data were used to construct three-dimensional computational models of relatively short channel reaches at each site. The streamflow component of these models predicted a spatially distributed field of water-surface elevation, water velocity, and bed shear stress for a range of stream discharges. Using the model predictions, along with measured particle sizes, the sediment-transport component of the model predicted the suspended-sediment concentration throughout the reach of interest. These computed concentrations were used with predicted flow patterns and channel morphology to

  7. Factors predicting surgical site infection after posterior lumbar surgery: A multicenter retrospective study.

    Science.gov (United States)

    Wang, Tao; Wang, Hui; Yang, Da-Long; Jiang, Li-Qiang; Zhang, Li-Jun; Ding, Wen-Yuan

    2017-02-01

    This is a retrospective study.The purpose of this study is to explore incidence and risk factors for surgical site infection (SSI) after posterior lumbar surgery.SSI is a common complication after posterior lumbar surgery, bringing mental and physical pain and prolonging hospital stay. However, predisposing factors, as reported less, remain controversial.Patients who underwent posterior lumbar surgery at 3 centers between 2006 and 2016 were included. The possible factors include 3 aspects: demographic variables-age, sex, body mass index (BMI), waist-to-hip radio (WHR), hypertension, diabetes, heart disease, smoking, drinking, steroidal injection, surgical time between June and September, preoperative shower; blood test variables-white blood cell (WBC), neutrophil, red blood cell (RBC), hemoglobin (Hb), total protein (TP), albumin, albumin/globulin (A/G), C-reactive protein (CRP), procalcitonin (PCT), erythrocyte sedimentation rate (ESR) and surgical related variables-operation time, blood loss, operative level, instrumentation, incision length. Factors related with SSI were also performed by multivariate analysis.The prevalence of SSI was 3.00% (267 cases of 8879) had a postoperative wound infection. There were significant difference in WHR (0.92 vs 0.83), WBC (4.31 vs 6.69), TP (58.7 vs 65.2), albumin (36.9 vs 43.2), CRP (2.01 vs 0.57), PCT (0.097 vs 0.067), operation time (217.9 vs 195.7), blood loss (997.1 vs 915.3) and operative level (3.05 vs 2.45) and incision length (24.1 vs 20.0) between SSI group and non-SSI group. >60 years old, female, BMI 30.0, diabetes, male smoking, preoperative steroidal injection, surgical time between June and September, no preoperative shower, instrumentation surgery were risk factors for SSI after posterior lumbar surgery.Many factors, >60 years old, female, BMI, WHR, diabetes, male smoking, preoperative steroidal injection, surgical time between June and September, preoperative shower, WBC, TP, albumin, CRP, PCT, operation time

  8. Using Geoarchaeology to Predict the Presence of Offshore Sites in Southern California (Invited)

    Science.gov (United States)

    Hildebrand, J.; York, A.

    2013-12-01

    During the late Pleistocene and early Holocene, the continental shelves off southern California were exposed and available for occupation by prehistoric peoples. Subsequent sealevel rise and marine transgression of the continental shelf resulted in both submergence and potentially reworking of site materials. A model has been developed and tested for continental shelf site locations, using geoarchaeological methods including seismic reflection imaging, coring, and invertebrate fossil identification. In this model, such factors as topography, rate of sea level rise, sediment thickness and context of deposition are all applied to the assessment of potential for site presence and preservation. The most desirable locations for site preservation are found in offshore valley floors and flanks, whereas adjacent uplands are prone to site erosion. Cultural materials from the La Jollan Complex were recovered from two separate offshore sites by large-scale dredging operations. Transgression at these sites occurred prior to about 8000 B.P.. The relation of these cultural materials to the offshore site location model will be discussed.

  9. Unusual adsorption site behavior in PCN-14 metal-organic framework predicted from Monte Carlo simulation.

    Science.gov (United States)

    Lucena, Sebastião M P; Mileo, Paulo G M; Silvino, Pedro F G; Cavalcante, Célio L

    2011-12-01

    The adsorption equilibrium of methane in PCN-14 was simulated by the Monte Carlo technique in the grand canonical ensemble. A new force field was proposed for the methane/PCN-14 system, and the temperature dependence of the molecular siting was investigated. A detailed study of the statistics of the center of mass and potential energy showed a surprising site behavior with no energy barriers between weak and strong sites, allowing open metal sites to guide methane molecules to other neighboring sites. Moreover, this study showed that a model assuming weakly adsorbing open metal clusters in PCN-14, densely populated only at low temperatures (below 150 K), can explain published experimental data. These results also explain previously observed discrepancies between neutron diffraction experiments and Monte Carlo simulations.

  10. ProBiS-CHARMMing: Web Interface for Prediction and Optimization of Ligands in Protein Binding Sites.

    Science.gov (United States)

    Konc, Janez; Miller, Benjamin T; Štular, Tanja; Lešnik, Samo; Woodcock, H Lee; Brooks, Bernard R; Janežič, Dušanka

    2015-11-23

    Proteins often exist only as apo structures (unligated) in the Protein Data Bank, with their corresponding holo structures (with ligands) unavailable. However, apoproteins may not represent the amino-acid residue arrangement upon ligand binding well, which is especially problematic for molecular docking. We developed the ProBiS-CHARMMing web interface by connecting the ProBiS ( http://probis.cmm.ki.si ) and CHARMMing ( http://www.charmming.org ) web servers into one functional unit that enables prediction of protein-ligand complexes and allows for their geometry optimization and interaction energy calculation. The ProBiS web server predicts ligands (small compounds, proteins, nucleic acids, and single-atom ligands) that may bind to a query protein. This is achieved by comparing its surface structure against a nonredundant database of protein structures and finding those that have binding sites similar to that of the query protein. Existing ligands found in the similar binding sites are then transposed to the query according to predictions from ProBiS. The CHARMMing web server enables, among other things, minimization and potential energy calculation for a wide variety of biomolecular systems, and it is used here to optimize the geometry of the predicted protein-ligand complex structures using the CHARMM force field and to calculate their interaction energies with the corresponding query proteins. We show how ProBiS-CHARMMing can be used to predict ligands and their poses for a particular binding site, and minimize the predicted protein-ligand complexes to obtain representations of holoproteins. The ProBiS-CHARMMing web interface is freely available for academic users at http://probis.nih.gov.

  11. Validation of the Registry to Evaluate Early and Long-Term Pulmonary Arterial Hypertension Disease Management (REVEAL) pulmonary hypertension prediction model in a unique population and utility in the prediction of long-term survival.

    Science.gov (United States)

    Cogswell, Rebecca; Kobashigawa, Erin; McGlothlin, Dana; Shaw, Robin; De Marco, Teresa

    2012-11-01

    The Registry to Evaluate Early and Long-Term Pulmonary Arterial (PAH) Hypertension Disease Management (REVEAL) model was designed to predict 1-year survival in patients with PAH. Multivariate prediction models need to be evaluated in cohorts distinct from the derivation set to determine external validity. In addition, limited data exist on the utility of this model in the prediction of long-term survival. REVEAL model performance was assessed to predict 1-year and 5-year outcomes, defined as survival or composite survival or freedom from lung transplant, in 140 patients with PAH. The validation cohort had a higher proportion of human immunodeficiency virus (7.9% vs 1.9%, p model to predict survival was 0.765 at 1 year and 0.712 at 5 years of follow-up. The C-index of the model to predict composite survival or freedom from lung transplant was 0.805 and 0.724 at 1 and 5 years of follow-up, respectively. Prediction by the model, however, was weakest among patients with intermediate-risk predicted survival. The REVEAL model had adequate discrimination to predict 1-year survival in this small but clinically distinct validation cohort. Although the model also had predictive ability out to 5 years, prediction was limited among patients of intermediate risk, suggesting our prediction methods can still be improved. Copyright © 2012. Published by Elsevier Inc.

  12. A Mechanism-Based Model for the Prediction of the Metabolic Sites of Steroids Mediated by Cytochrome P450 3A4

    Directory of Open Access Journals (Sweden)

    Zi-Ru Dai

    2015-06-01

    Full Text Available Early prediction of xenobiotic metabolism is essential for drug discovery and development. As the most important human drug-metabolizing enzyme, cytochrome P450 3A4 has a large active cavity and metabolizes a broad spectrum of substrates. The poor substrate specificity of CYP3A4 makes it a huge challenge to predict the metabolic site(s on its substrates. This study aimed to develop a mechanism-based prediction model based on two key parameters, including the binding conformation and the reaction activity of ligands, which could reveal the process of real metabolic reaction(s and the site(s of modification. The newly established model was applied to predict the metabolic site(s of steroids; a class of CYP3A4-preferred substrates. 38 steroids and 12 non-steroids were randomly divided into training and test sets. Two major metabolic reactions, including aliphatic hydroxylation and N-dealkylation, were involved in this study. At least one of the top three predicted metabolic sites was validated by the experimental data. The overall accuracy for the training and test were 82.14% and 86.36%, respectively. In summary, a mechanism-based prediction model was established for the first time, which could be used to predict the metabolic site(s of CYP3A4 on steroids with high predictive accuracy.

  13. Predicting functional divergence in protein evolution by site-specific rate shifts

    Science.gov (United States)

    Gaucher, Eric A.; Gu, Xun; Miyamoto, Michael M.; Benner, Steven A.

    2002-01-01

    Most modern tools that analyze protein evolution allow individual sites to mutate at constant rates over the history of the protein family. However, Walter Fitch observed in the 1970s that, if a protein changes its function, the mutability of individual sites might also change. This observation is captured in the "non-homogeneous gamma model", which extracts functional information from gene families by examining the different rates at which individual sites evolve. This model has recently been coupled with structural and molecular biology to identify sites that are likely to be involved in changing function within the gene family. Applying this to multiple gene families highlights the widespread divergence of functional behavior among proteins to generate paralogs and orthologs.

  14. Predicting ambient aerosol thermal-optical reflectance (TOR) measurements from infrared spectra: extending the predictions to different years and different sites

    Science.gov (United States)

    Reggente, Matteo; Dillner, Ann M.; Takahama, Satoshi

    2016-02-01

    Organic carbon (OC) and elemental carbon (EC) are major components of atmospheric particulate matter (PM), which has been associated with increased morbidity and mortality, climate change, and reduced visibility. Typically OC and EC concentrations are measured using thermal-optical methods such as thermal-optical reflectance (TOR) from samples collected on quartz filters. In this work, we estimate TOR OC and EC using Fourier transform infrared (FT-IR) absorbance spectra from polytetrafluoroethylene (PTFE Teflon) filters using partial least square regression (PLSR) calibrated to TOR OC and EC measurements for a wide range of samples. The proposed method can be integrated with analysis of routinely collected PTFE filter samples that, in addition to OC and EC concentrations, can concurrently provide information regarding the functional group composition of the organic aerosol. We have used the FT-IR absorbance spectra and TOR OC and EC concentrations collected in the Interagency Monitoring of PROtected Visual Environments (IMPROVE) network (USA). We used 526 samples collected in 2011 at seven sites to calibrate the models, and more than 2000 samples collected in 2013 at 17 sites to test the models. Samples from six sites are present both in the calibration and test sets. The calibrations produce accurate predictions both for samples collected at the same six sites present in the calibration set (R2 = 0.97 and R2 = 0.95 for OC and EC respectively), and for samples from 9 of the 11 sites not included in the calibration set (R2 = 0.96 and R2 = 0.91 for OC and EC respectively). Samples collected at the other two sites require a different calibration model to achieve accurate predictions. We also propose a method to anticipate the prediction error; we calculate the squared Mahalanobis distance in the feature space (scores determined by PLSR) between new spectra and spectra in the calibration set. The squared Mahalanobis distance provides a crude method for assessing the

  15. WAsP prediction errors due to site orography[Wind Atlas Analysis and Application Program

    Energy Technology Data Exchange (ETDEWEB)

    Bowen, A.J.; Mortensen, N.G.

    2004-12-01

    The influence of rugged terrain on the prediction accuracy of the Wind Atlas Analysis and Application Program (WAsP) is investigated using a case study of field measurements taken in rugged terrain. The parameters that could cause substantial errors in a prediction are identified and discussed. In particular, the effects from extreme orography are investigated. A suitable performance indicator is developed which predicts the sign and approximate magnitude of such errors due to orography. This procedure allows the user to assess the consequences of using WAsP outside its operating envelope and could provide a means of correction for rugged terrain effects. (au)

  16. NetOglyc: prediction of mucin type O-glycosylation sites based on sequence context and surface accessibility

    DEFF Research Database (Denmark)

    Hansen, Jan Erik; Lund, Ole; Tolstrup, Niels

    1998-01-01

    -glycosylation signals in these evolutionary-related glycoproteins were found in their first hypervariable loop, V1. However, the strain variation for HIV-1 gp120 was significant. A computer server, available through WWW or E-mail, has been developed for prediction of mucin type O-glycosylation sites in proteins based...... on the amino acid sequence. The server addresses are http://www.cbs.dtu.dk/services/NetOGlyc/ and netOglyc@cbs.dtu.dk...

  17. A neural network method for identification of prokaryotic and eukaryotic signal peptides and prediction of their cleavage sites

    DEFF Research Database (Denmark)

    Nielsen, Henrik; Engelbrecht, Jacob; Brunak, Søren;

    1997-01-01

    We have developed a new method for the identication of signal peptides and their cleavage sites based on neural networks trained on separate sets of prokaryotic and eukaryotic sequences. The method performs signicantly better than previous prediction schemes, and can easily be applied to genome-w......-wide data sets. Discrimination between cleaved signal peptides and uncleaved N-terminal signal-anchor sequences is also possible, though with lower precision....

  18. pkaPS: prediction of protein kinase A phosphorylation sites with the simplified kinase-substrate binding model

    Directory of Open Access Journals (Sweden)

    Schneider Georg

    2007-01-01

    Full Text Available Abstract Background Protein kinase A (cAMP-dependent kinase, PKA is a serine/threonine kinase, for which ca. 150 substrate proteins are known. Based on a refinement of the recognition motif using the available experimental data, we wished to apply the simplified substrate protein binding model for accurate prediction of PKA phosphorylation sites, an approach that was previously successful for the prediction of lipid posttranslational modifications and of the PTS1 peroxisomal translocation signal. Results Approximately 20 sequence positions flanking the phosphorylated residue on both sides have been found to be restricted in their sequence variability (region -18...+23 with the site at position 0. The conserved physical pattern can be rationalized in terms of a qualitative binding model with the catalytic cleft of the protein kinase A. Positions -6...+4 surrounding the phosphorylation site are influenced by direct interaction with the kinase in a varying degree. This sequence stretch is embedded in an intrinsically disordered region composed preferentially of hydrophilic residues with flexible backbone and small side chain. This knowledge has been incorporated into a simplified analytical model of productive binding of substrate proteins with PKA. Conclusion The scoring function of the pkaPS predictor can confidently discriminate PKA phosphorylation sites from serines/threonines with non-permissive sequence environments (sensitivity of ~96% at a specificity of ~94%. The tool "pkaPS" has been applied on the whole human proteome. Among new predicted PKA targets, there are entirely uncharacterized protein groups as well as apparently well-known families such as those of the ribosomal proteins L21e, L22 and L6. Availability The supplementary data as well as the prediction tool as WWW server are available at http://mendel.imp.univie.ac.at/sat/pkaPS. Reviewers Erik van Nimwegen (Biozentrum, University of Basel, Switzerland, Sandor Pongor (International

  19. Tumor characteristics and metastatic sites may predict bevacizumab efficacy in the first-line treatment of metastatic colorectal cancer

    OpenAIRE

    Varol, Umut; Oktay, Esin; YILDIRIM, Mustafa; SURMELI, ZEKI GOKHAN; Dirican, Ahmet; Meydan, Nezih; KARACA, BURCAK; Karabulut, Bulent; Uslu, Ruchan

    2013-01-01

    Colorectal cancer (CRC) is among the most frequently diagnosed cancers and a major cause of cancer-related mortality worldwide. The aim of the present study was to determine whether there was an improvement in the time to disease progression (TTP) in patients with metastatic colorectal cancer (mCRC) treated with first-line bevacizumab plus chemotherapy, according to tumor characteristics and metastatic sites. Tumor characteristics and tumor burden were considered to be predictive markers of t...

  20. Structure-based comparative analysis and prediction of N-linked glycosylation sites in evolutionarily distant eukaryotes.

    Science.gov (United States)

    Lam, Phuc Vinh Nguyen; Goldman, Radoslav; Karagiannis, Konstantinos; Narsule, Tejas; Simonyan, Vahan; Soika, Valerii; Mazumder, Raja

    2013-04-01

    The asparagine-X-serine/threonine (NXS/T) motif, where X is any amino acid except proline, is the consensus motif for N-linked glycosylation. Significant numbers of high-resolution crystal structures of glycosylated proteins allow us to carry out structural analysis of the N-linked glycosylation sites (NGS). Our analysis shows that there is enough structural information from diverse glycoproteins to allow the development of rules which can be used to predict NGS. A Python-based tool was developed to investigate asparagines implicated in N-glycosylation in five species: Homo sapiens, Mus musculus, Drosophila melanogaster, Arabidopsis thaliana and Saccharomyces cerevisiae. Our analysis shows that 78% of all asparagines of NXS/T motif involved in N-glycosylation are localized in the loop/turn conformation in the human proteome. Similar distribution was revealed for all the other species examined. Comparative analysis of the occurrence of NXS/T motifs not known to be glycosylated and their reverse sequence (S/TXN) shows a similar distribution across the secondary structural elements, indicating that the NXS/T motif in itself is not biologically relevant. Based on our analysis, we have defined rules to determine NGS. Using machine learning methods based on these rules we can predict with 93% accuracy if a particular site will be glycosylated. If structural information is not available the tool uses structural prediction results resulting in 74% accuracy. The tool was used to identify glycosylation sites in 108 human proteins with structures and 2247 proteins without structures that have acquired NXS/T site/s due to non-synonymous variation. The tool, Structure Feature Analysis Tool (SFAT), is freely available to the public at http://hive.biochemistry.gwu.edu/tools/sfat. Copyright © 2013. Production and hosting by Elsevier Ltd.

  1. JET2 Viewer: a database of predicted multiple, possibly overlapping, protein–protein interaction sites for PDB structures

    Science.gov (United States)

    Ripoche, Hugues; Laine, Elodie; Ceres, Nicoletta; Carbone, Alessandra

    2017-01-01

    The database JET2 Viewer, openly accessible at http://www.jet2viewer.upmc.fr/, reports putative protein binding sites for all three-dimensional (3D) structures available in the Protein Data Bank (PDB). This knowledge base was generated by applying the computational method JET2 at large-scale on more than 20 000 chains. JET2 strategy yields very precise predictions of interacting surfaces and unravels their evolutionary process and complexity. JET2 Viewer provides an online intelligent display, including interactive 3D visualization of the binding sites mapped onto PDB structures and suitable files recording JET2 analyses. Predictions were evaluated on more than 15 000 experimentally characterized protein interfaces. This is, to our knowledge, the largest evaluation of a protein binding site prediction method. The overall performance of JET2 on all interfaces are: Sen = 52.52, PPV = 51.24, Spe = 80.05, Acc = 75.89. The data can be used to foster new strategies for protein–protein interactions modulation and interaction surface redesign. PMID:27899675

  2. Performance predictions for mechanical excavators in Yucca Mountain tuffs; Yucca Mountain Site Characterization Project

    Energy Technology Data Exchange (ETDEWEB)

    Ozdemir, L.; Gertsch, L.; Neil, D.; Friant, J. [Colorado School of Mines, Golden, CO (United States). Earth Mechanics Inst.

    1992-09-01

    The performances of several mechanical excavators are predicted for use in the tuffs at Yucca Mountain: Tunnel boring machines, the Mobile Miner, a roadheader, a blind shaft borer, a vertical wheel shaft boring machine, raise drills, and V-Moles. Work summarized is comprised of three parts: Initial prediction using existing rock physical property information; Measurement of additional rock physical properties; and Revision of the initial predictions using the enhanced database. The performance predictions are based on theoretical and empirical relationships between rock properties and the forces-experienced by rock cutters and bits during excavation. Machine backup systems and excavation design aspects, such as curves and grades, are considered in determining excavator utilization factors. Instanteous penetration rate, advance rate, and cutter costs are the fundamental performance indicators.

  3. Exploiting structural and topological information to improve prediction of RNA-protein binding sites

    Directory of Open Access Journals (Sweden)

    Yuan Zheng

    2009-10-01

    Full Text Available Abstract Background RNA-protein interactions are important for a wide range of biological processes. Current computational methods to predict interacting residues in RNA-protein interfaces predominately rely on sequence data. It is, however, known that interface residue propensity is closely correlated with structural properties. In this paper we systematically study information obtained from sequences and structures and compare their contributions in this prediction problem. Particularly, different geometrical and network topological properties of protein structures are evaluated to improve interface residue prediction accuracy. Results We have quantified the impact of structural information on the prediction accuracy in comparison to the purely sequence based approach using two machine learning techniques: Naïve Bayes classifiers and Support Vector Machines. The highest AUC of 0.83 was achieved by a Support Vector Machine, exploiting PSI-BLAST profile, accessible surface area, betweenness-centrality and retention coefficient as input features. Taking into account that our results are based on a larger non-redundant data set, the prediction accuracy is considerably higher than reported in previous, comparable studies. A protein-RNA interface predictor (PRIP and the data set have been made available at http://www.qfab.org/PRIP. Conclusion Graph-theoretic properties of residue contact maps derived from protein structures such as betweenness-centrality can supplement sequence or structure features to improve the prediction accuracy for binding residues in RNA-protein interactions. While Support Vector Machines perform better on this task, Naïve Bayes classifiers also have been found to achieve good prediction accuracies but require much less training time and are an attractive choice for large scale predictions.

  4. Verification of geomechanical integrity and prediction of long-term mineral trapping for the Ketzin CO2 storage pilot site

    Science.gov (United States)

    Kempka, Thomas; De Lucia, Marco; Kühn, Michael

    2014-05-01

    Static and dynamic numerical modelling generally accompany the entire CO2 storage site life cycle. Thereto, it is required to match the employed models with field observations on a regular basis in order to predict future site behaviour. We investigated the coupled processes at the Ketzin CO2 storage pilot site [1] using a model coupling concept focusing on the temporal relevance of processes involved (hydraulic, chemical and mechanical) at given time-scales (site operation, abandonment and long-term stabilization). For that purpose, long-term dynamic multi-phase flow simulations [2], [3] established the basis for all simulations discussed in the following. Hereby, pressure changes resulting in geomechanical effects are largest during site operation, whereas geochemical reactions are governed by slow kinetics resulting in a long-term stabilization. To account for mechanical integrity, which may be mainly affected during site operation, we incorporated a regional-scale coupled hydro-mechanical model. Our simulation results show maximum ground surface displacements of about 4 mm, whereas shear and tensile failure are not observed. Consequently, the CO2 storage operation at the Ketzin pilot site does not compromise reservoir, caprock and fault integrity. Chemical processes responsible for mineral trapping are expected to mainly occur during long-term stabilization at the Ketzin pilot site [4]. Hence, our previous assessment [3] was extended by integrating two long-term mineral trapping scenarios. Thereby, mineral trapping contributes to the trapping mechanisms with 11.7 % after 16,000 years of simulation in our conservative and with 30.9 % in our maximum reactivity scenarios. Dynamic flow simulations indicate that only 0.2 % of the CO2 injected (about 67,270 t CO2 in total) is in gaseous state, but structurally trapped after 16,000 years. Depending on the studied long-term scenario, CO2 dissolution is the dominating trapping mechanism with 68.9 % and 88

  5. Predicting success of oligomerized pool engineering (OPEN for zinc finger target site sequences

    Directory of Open Access Journals (Sweden)

    Goodwin Mathew J

    2010-11-01

    Full Text Available Abstract Background Precise and efficient methods for gene targeting are critical for detailed functional analysis of genomes and regulatory networks and for potentially improving the efficacy and safety of gene therapies. Oligomerized Pool ENgineering (OPEN is a recently developed method for engineering C2H2 zinc finger proteins (ZFPs designed to bind specific DNA sequences with high affinity and specificity in vivo. Because generation of ZFPs using OPEN requires considerable effort, a computational method for identifying the sites in any given gene that are most likely to be successfully targeted by this method is desirable. Results Analysis of the base composition of experimentally validated ZFP target sites identified important constraints on the DNA sequence space that can be effectively targeted using OPEN. Using alternate encodings to represent ZFP target sites, we implemented Naïve Bayes and Support Vector Machine classifiers capable of distinguishing "active" targets, i.e., ZFP binding sites that can be targeted with a high rate of success, from those that are "inactive" or poor targets for ZFPs generated using current OPEN technologies. When evaluated using leave-one-out cross-validation on a dataset of 135 experimentally validated ZFP target sites, the best Naïve Bayes classifier, designated ZiFOpT, achieved overall accuracy of 87% and specificity+ of 90%, with an ROC AUC of 0.89. When challenged with a completely independent test set of 140 newly validated ZFP target sites, ZiFOpT performance was comparable in terms of overall accuracy (88% and specificity+ (92%, but with reduced ROC AUC (0.77. Users can rank potentially active ZFP target sites using a confidence score derived from the posterior probability returned by ZiFOpT. Conclusion ZiFOpT, a machine learning classifier trained to identify DNA sequences amenable for targeting by OPEN-generated zinc finger arrays, can guide users to target sites that are most likely to function

  6. Using Tree-Ring Width Data From 1000 Sites to Predict how American Forests Will Respond to Climate Change

    Science.gov (United States)

    Williams, P.; Still, C. J.; Leavitt, S. W.; Fischer, D. T.

    2007-12-01

    Beginning in the early 1900s, tree-ring scientists began analyzing the relative widths of annual growth rings preserved in the cross-sections of trees. Over the years, many ring-width index chronologies, each representing a specific site and species, have been developed and analyzed to infer details regarding past climate, growth response to environmental fluctuation, fire activity, logging practices by past societies, and more. Of the many ring-width chronologies constructed, 1035 represent sites within the continental United States and have been published online within The International Tree-Ring Data Bank as of September 2007 (ITRDB, http://www.ncdc.noaa.gov/paleo/treering.html). Approximately 85% of these sites are located west of the Mississippi River. Here we present results from a three-step study, using this large reserve of tree-growth data to determine how various tree species in various regions have responded to climate fluctuations in the past and how they can be expected to respond to future change. In the first step, we used linear regression to compare each time series of ring-width index values to a suite of local monthly climate variables that may influence tree growth, such as rainfall, temperature, and drought severity (PDSI). We identified the range of months (of a 24- month period) during which each climate parameter most strongly affects growth by comparing Pearson correlation coefficients. In the second step, we identified all sites where at least one climate parameter, during some rage of months, correlates significantly (95% confidence) with ring-width index values. For each of these sites, we constructed a growth model that uses each significantly correlating climate parameter as a growth predictor. In the third step, we applied the growth model to predict the next 100 years of growth response to a monthly climate forecast created by the Hadley Centre for Climate Prediction and Research. This forecast (HadCM3 IS92a) assumes a business as

  7. Evolution of neural networks for the prediction of hydraulic conductivity as a function of borehole geophysical logs: Shobasama site, Japan.

    Energy Technology Data Exchange (ETDEWEB)

    Reeves, Paul C.; McKenna, Sean Andrew

    2004-06-01

    This report describes the methodology and results of a project to develop a neural network for the prediction of the measured hydraulic conductivity or transmissivity in a series of boreholes at the Tono, Japan study site. Geophysical measurements were used as the input to EL feed-forward neural network. A simple genetic algorithm was used to evolve the architecture and parameters of the neural network in conjunction with an optimal subset of geophysical measurements for the prediction of hydraulic conductivity. The first attempt was focused on the estimation of the class of the hydraulic conductivity, high, medium or low, from the geophysical logs. This estimation was done while using the genetic algorithm to simultaneously determine which geophysical logs were the most important and optimizing the architecture of the neural network. Initial results showed that certain geophysical logs provided more information than others- most notably the 'short-normal', micro-resistivity, porosity and sonic logs provided the most information on hydraulic conductivity. The neural network produced excellent training results with accuracy of 90 percent or greater, but was unable to produce accurate predictions of the hydraulic conductivity class. The second attempt at prediction was done using a new methodology and a modified data set. The new methodology builds on the results of the first attempts at prediction by limiting the choices of geophysical logs to only those that provide significant information. Additionally, this second attempt uses a modified data set and predicts transmissivity instead of hydraulic conductivity. Results of these simulations indicate that the most informative geophysical measurements for the prediction of transmissivity are depth and sonic log. The long normal resistivity and self potential borehole logs are moderately informative. In addition, it was found that porosity and crack counts (clear, open, or hairline) do not inform predictions

  8. A sequence-based dynamic ensemble learning system for protein ligand-binding site prediction

    KAUST Repository

    Chen, Peng

    2015-12-03

    Background: Proteins have the fundamental ability to selectively bind to other molecules and perform specific functions through such interactions, such as protein-ligand binding. Accurate prediction of protein residues that physically bind to ligands is important for drug design and protein docking studies. Most of the successful protein-ligand binding predictions were based on known structures. However, structural information is not largely available in practice due to the huge gap between the number of known protein sequences and that of experimentally solved structures

  9. Sequence-based prediction of protein-binding sites in DNA: comparative study of two SVM models.

    Science.gov (United States)

    Park, Byungkyu; Im, Jinyong; Tuvshinjargal, Narankhuu; Lee, Wook; Han, Kyungsook

    2014-11-01

    As many structures of protein-DNA complexes have been known in the past years, several computational methods have been developed to predict DNA-binding sites in proteins. However, its inverse problem (i.e., predicting protein-binding sites in DNA) has received much less attention. One of the reasons is that the differences between the interaction propensities of nucleotides are much smaller than those between amino acids. Another reason is that DNA exhibits less diverse sequence patterns than protein. Therefore, predicting protein-binding DNA nucleotides is much harder than predicting DNA-binding amino acids. We computed the interaction propensity (IP) of nucleotide triplets with amino acids using an extensive dataset of protein-DNA complexes, and developed two support vector machine (SVM) models that predict protein-binding nucleotides from sequence data alone. One SVM model predicts protein-binding nucleotides using DNA sequence data alone, and the other SVM model predicts protein-binding nucleotides using both DNA and protein sequences. In a 10-fold cross-validation with 1519 DNA sequences, the SVM model that uses DNA sequence data only predicted protein-binding nucleotides with an accuracy of 67.0%, an F-measure of 67.1%, and a Matthews correlation coefficient (MCC) of 0.340. With an independent dataset of 181 DNAs that were not used in training, it achieved an accuracy of 66.2%, an F-measure 66.3% and a MCC of 0.324. Another SVM model that uses both DNA and protein sequences achieved an accuracy of 69.6%, an F-measure of 69.6%, and a MCC of 0.383 in a 10-fold cross-validation with 1519 DNA sequences and 859 protein sequences. With an independent dataset of 181 DNAs and 143 proteins, it showed an accuracy of 67.3%, an F-measure of 66.5% and a MCC of 0.329. Both in cross-validation and independent testing, the second SVM model that used both DNA and protein sequence data showed better performance than the first model that used DNA sequence data. To the best of

  10. Individual tree crown approach for predicting site index in boreal forests using airborne laser scanning and hyperspectral data

    Science.gov (United States)

    Kandare, Kaja; Ørka, Hans Ole; Dalponte, Michele; Næsset, Erik; Gobakken, Terje

    2017-08-01

    Site productivity is essential information for sustainable forest management and site index (SI) is the most common quantitative measure of it. The SI is usually determined for individual tree species based on tree height and the age of the 100 largest trees per hectare according to stem diameter. The present study aimed to demonstrate and validate a methodology for the determination of SI using remotely sensed data, in particular fused airborne laser scanning (ALS) and airborne hyperspectral data in a forest site in Norway. The applied approach was based on individual tree crown (ITC) delineation: tree species, tree height, diameter at breast height (DBH), and age were modelled and predicted at ITC level using 10-fold cross validation. Four dominant ITCs per 400 m2 plot were selected as input to predict SI at plot level for Norway spruce (Picea abies (L.) Karst.) and Scots pine (Pinus sylvestris L.). We applied an experimental setup with different subsets of dominant ITCs with different combinations of attributes (predicted or field-derived) for SI predictions. The results revealed that the selection of the dominant ITCs based on the largest DBH independent of tree species, predicted the SI with similar accuracy as ITCs matched with field-derived dominant trees (RMSE: 27.6% vs 23.3%). The SI accuracies were at the same level when dominant species were determined from the remotely sensed or field data (RMSE: 27.6% vs 27.8%). However, when the predicted tree age was used the SI accuracy decreased compared to field-derived age (RMSE: 27.6% vs 7.6%). In general, SI was overpredicted for both tree species in the mature forest, while there was an underprediction in the young forest. In conclusion, the proposed approach for SI determination based on ITC delineation and a combination of ALS and hyperspectral data is an efficient and stable procedure, which has the potential to predict SI in forest areas at various spatial scales and additionally to improve existing SI

  11. Homology models of dipeptidyl peptidases 8 and 9 with a focus on loop predictions near the active site.

    Science.gov (United States)

    Rummey, Christian; Metz, Günther

    2007-01-01

    Dipeptidyl peptidase 4 (DP4) inhibitors are currently under intensive investigation in late-stage clinical trials as a treatment for type II diabetes. Lack of selectivity toward the related enzymes DP8 and DP9 has recently emerged as a possible source of drug-induced toxicity. Unlike DP4, X-ray structures of DP8 and DP9 are not yet available. As an aid to understanding the structural basis for selectivity, the authors have constructed homology models of DP8 and DP9 based on the X-ray coordinates of DP4. Accurate sequence alignment reveals common structural features indicative for a well-preserved overall fold comprising two domains, namely, a hydrolase domain and a so-called beta-propeller, which together form the active site deeply buried within the protein. The conformation of two loops inside this deep cavity is particularly relevant for the active sites. The authors used a published protocol for loop prediction based on conformational sampling and energy analysis to generate plausible solutions for these two loops. The predictive power of the approach was successfully evaluated for the template protein DP4 and two additional known structures from the same protein family, namely, FAP and DPX. The authors also show that inclusion of the covalent ligand NVP-728 greatly enhances the refinement. Based on the established evaluation protocol, the corresponding loops of DP8 and DP9 were predicted and the resulting active sites were compared with DP4. In particular, the authors conclude that differences in the P2-pocket are relevant for the design of selective DP4 inhibitors. The loss of key interactions in DP8 and DP9 as predicted from their models is consistent with the selectivity profile of the DP4 clinical candidate MK-431.

  12. Evaluation of WEPP for runoff and sediment yield prediction on natural gas well sites

    Science.gov (United States)

    Natural gas exploration and production, with nearly 30,000 new wells drilled each year in the US, requires land disturbing activities that can accelerate soil loss. Erosion modeling has been successfully used for decades to predict soil loss and conservation effects on agricultural fields, rangelan...

  13. Paper Highlight: Biomarker Identified for Predicting Early Prostate Cancer Aggressiveness — Site

    Science.gov (United States)

    A team led by Cory Abate-Shen, Michael Shen, and Andrea Califano at Columbia University found that measuring the expression levels of three genes associated with aging can be used to predict the aggressiveness of seemingly low-risk prostate cancer.

  14. SVM-based prediction of propeptide cleavage sites in spider toxins identifies toxin innovation in an Australian tarantula.

    Directory of Open Access Journals (Sweden)

    Emily S W Wong

    Full Text Available Spider neurotoxins are commonly used as pharmacological tools and are a popular source of novel compounds with therapeutic and agrochemical potential. Since venom peptides are inherently toxic, the host spider must employ strategies to avoid adverse effects prior to venom use. It is partly for this reason that most spider toxins encode a protective proregion that upon enzymatic cleavage is excised from the mature peptide. In order to identify the mature toxin sequence directly from toxin transcripts, without resorting to protein sequencing, the propeptide cleavage site in the toxin precursor must be predicted bioinformatically. We evaluated different machine learning strategies (support vector machines, hidden Markov model and decision tree and developed an algorithm (SpiderP for prediction of propeptide cleavage sites in spider toxins. Our strategy uses a support vector machine (SVM framework that combines both local and global sequence information. Our method is superior or comparable to current tools for prediction of propeptide sequences in spider toxins. Evaluation of the SVM method on an independent test set of known toxin sequences yielded 96% sensitivity and 100% specificity. Furthermore, we sequenced five novel peptides (not used to train the final predictor from the venom of the Australian tarantula Selenotypus plumipes to test the accuracy of the predictor and found 80% sensitivity and 99.6% 8-mer specificity. Finally, we used the predictor together with homology information to predict and characterize seven groups of novel toxins from the deeply sequenced venom gland transcriptome of S. plumipes, which revealed structural complexity and innovations in the evolution of the toxins. The precursor prediction tool (SpiderP is freely available on ArachnoServer (http://www.arachnoserver.org/spiderP.html, a web portal to a comprehensive relational database of spider toxins. All training data, test data, and scripts used are available from

  15. The Predicting Model of E-commerce Site Based on the Ideas of Curve Fitting

    Science.gov (United States)

    Tao, Zhang; Li, Zhang; Dingjun, Chen

    On the basis of the idea of the second multiplication curve fitting, the number and scale of Chinese E-commerce site is analyzed. A preventing increase model is introduced in this paper, and the model parameters are solved by the software of Matlab. The validity of the preventing increase model is confirmed though the numerical experiment. The experimental results show that the precision of preventing increase model is ideal.

  16. Determination of the strain generated in InAs/InP quantum wires: prediction of nucleation sites

    Energy Technology Data Exchange (ETDEWEB)

    Molina, S I [Departamento de Ciencia de los Materiales e I.M. y Q.I., Facultad de Ciencias, Universidad de Cadiz, Campus RIo San Pedro, s/n, 11510 Puerto Real, Cadiz (Spain); Ben, T [Departamento de Ciencia de los Materiales e I.M. y Q.I., Facultad de Ciencias, Universidad de Cadiz, Campus RIo San Pedro, s/n, 11510 Puerto Real, Cadiz (Spain); Sales, D L [Departamento de Ciencia de los Materiales e I.M. y Q.I., Facultad de Ciencias, Universidad de Cadiz, Campus RIo San Pedro, s/n, 11510 Puerto Real, Cadiz (Spain); Pizarro, J [Departamento de Lenguajes y Sistemas Informaticos, CASEM, Universidad de Cadiz, Campus RIo San Pedro, s/n, 11510 Puerto Real, Cadiz (Spain); Galindo, P L [Departamento de Lenguajes y Sistemas Informaticos, CASEM, Universidad de Cadiz, Campus RIo San Pedro, s/n, 11510 Puerto Real, Cadiz (Spain); Varela, M [Condensed Matter Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States); Pennycook, S J [Condensed Matter Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States); Fuster, D [Instituto de Microelectronica de Madrid (CNM, CSIC), Isaac Newton 8, 28760 Tres Cantos, Madrid (Spain); Gonzalez, Y [Instituto de Microelectronica de Madrid (CNM, CSIC), Isaac Newton 8, 28760 Tres Cantos, Madrid (Spain); Gonzalez, L [Instituto de Microelectronica de Madrid (CNM, CSIC), Isaac Newton 8, 28760 Tres Cantos, Madrid (Spain)

    2006-11-28

    The compositional distribution in a self-assembled InAs(P) quantum wire grown by molecular beam epitaxy on an InP(001) substrate has been determined by electron energy loss spectrum imaging. We have determined the strain and stress fields generated in and around this wire capped with a 5 nm InP layer by finite element calculations using as input the compositional map experimentally obtained. Preferential sites for nucleation of wires grown on the surface of this InP capping layer are predicted, based on chemical potential minimization, from the determined strain and stress fields on this surface. The determined preferential sites for wire nucleation agree with their experimentally measured locations. The method used in this paper, which combines electron energy loss spectroscopy, high-resolution Z contrast imaging, and elastic theory finite element calculations, is believed to be a valuable technique of wide applicability for predicting the preferential nucleation sites of epitaxial self-assembled nano-objects.

  17. Single-nucleotide mutation matrix: a new model for predicting the NF-κB DNA binding sites.

    Directory of Open Access Journals (Sweden)

    Wenxin Du

    Full Text Available In this study, we established a single nucleotide mutation matrix (SNMM model based on the relative binding affinities of NF-κB p50 homodimer to a wild-type binding site (GGGACTTTCC and its all single-nucleotide mutants detected with the double-stranded DNA microarray. We evaluated this model by scoring different groups of 10-bp DNA sequences with this model and analyzing the correlations between the scores and the relative binding affinities detected with three wet experiments, including the electrophoresis mobility shift assay (EMSA, the protein-binding microarray (PBM and the systematic evolution of ligands by exponential enrichment-sequencing (SELEX-Seq. The results revealed that the SNMM scores were strongly correlated with the detected binding affinities. We also scored the DNA sequences with other three models, including the principal coordinate (PC model, the position weight matrix scoring algorithm (PWMSA model and the Match model, and analyzed the correlations between the scores and the detected binding affinities. In comparison with these models, the SNMM model achieved reliable results. We finally determined 0.747 as the optimal threshold for predicting the NF-κB DNA-binding sites with the SNMM model. The SNMM model thus provides a new alternative model for scoring the relative binding affinities of NF-κB to the 10-bp DNA sequences and predicting the NF-κB DNA-binding sites.

  18. Single-nucleotide mutation matrix: a new model for predicting the NF-κB DNA binding sites.

    Science.gov (United States)

    Du, Wenxin; Gao, Jing; Wang, Tingting; Wang, Jinke

    2014-01-01

    In this study, we established a single nucleotide mutation matrix (SNMM) model based on the relative binding affinities of NF-κB p50 homodimer to a wild-type binding site (GGGACTTTCC) and its all single-nucleotide mutants detected with the double-stranded DNA microarray. We evaluated this model by scoring different groups of 10-bp DNA sequences with this model and analyzing the correlations between the scores and the relative binding affinities detected with three wet experiments, including the electrophoresis mobility shift assay (EMSA), the protein-binding microarray (PBM) and the systematic evolution of ligands by exponential enrichment-sequencing (SELEX-Seq). The results revealed that the SNMM scores were strongly correlated with the detected binding affinities. We also scored the DNA sequences with other three models, including the principal coordinate (PC) model, the position weight matrix scoring algorithm (PWMSA) model and the Match model, and analyzed the correlations between the scores and the detected binding affinities. In comparison with these models, the SNMM model achieved reliable results. We finally determined 0.747 as the optimal threshold for predicting the NF-κB DNA-binding sites with the SNMM model. The SNMM model thus provides a new alternative model for scoring the relative binding affinities of NF-κB to the 10-bp DNA sequences and predicting the NF-κB DNA-binding sites.

  19. Polymorphisms in MicroRNA Binding Sites Predict Colorectal Cancer Survival

    Science.gov (United States)

    Yang, Ying-Pi; Ting, Wen-Chien; Chen, Lu-Min; Lu, Te-Ling; Bao, Bo-Ying

    2017-01-01

    Background: MicroRNAs (miRNAs) mediate negative regulation of target genes through base pairing, and aberrant miRNA expression has been described in cancers. We hypothesized that single nucleotide polymorphisms (SNPs) within miRNA target sites might influence clinical outcomes in patients with colorectal cancer. Methods: Sixteen common SNPs within miRNA target sites were identified, and the association between these SNPs and overall survival was assessed in colorectal cancer patients using Kaplan-Meier analysis, Cox regression model, and survival tree analysis. Results: Survival tree analysis identified a higher-order genetic interaction profile consisting of the RPS6KB1 rs1051424 and ZNF839 rs11704 that was significantly associated with overall survival. The 5-year survival rates were 74.6%, 62.7%, and 57.1% for the low-, medium-, and high-risk genetic profiles, respectively (P = 0.006). The genetic interaction profile remained significant even after adjusting for potential risk factors. Additional in silico analysis provided evidence that rs1051424 and rs11704 affect RPS6KB1 and ZNF839 expressions, which in turn is significantly correlated with prognosis in colorectal cancer. Conclusion: Our results suggest that the genetic interaction profiles among SNPs within miRNA target sites might be prognostic markers for colorectal cancer survival. PMID:28138309

  20. Predicting the macroseismic intensity from early radiated P wave energy for on-site earthquake early warning in Italy

    Science.gov (United States)

    Brondi, P.; Picozzi, M.; Emolo, A.; Zollo, A.; Mucciarelli, M.

    2015-10-01

    Earthquake Early Warning Systems (EEWS) are potentially effective tools for risk mitigation in active seismic regions. The present study explores the possibility of predicting the macroseismic intensity within EEW timeframes using the squared velocity integral (IV2) measured on the early P wave signals, a proxy for the P wave radiated energy of earthquakes. This study shows that IV2 correlates better than the peak displacement measured on P waves with both the peak ground velocity and the Housner Intensity, with the latter being recognized by engineers as a reliable proxy for damage assessment. Therefore, using the strong motion recordings of the Italian Accelerometric Archive, a novel relationship between the parameter IV2 and the macroseismic intensity (IM) has been derived. The validity of this relationship has been assessed using the strong motion recordings of the Istituto Nazionale di Geofisica e Vulcanologia Strong Motion Data and Osservatorio Sismico delle Strutture databases, as well as, in the case of the MW 6, 29 May 2012 Emilia earthquake (Italy), comparing the predicted intensities with the ones observed after a macroseismic survey. Our results indicate that P wave IV2 can become a key parameter for the design of on-site EEWS, capable of proving real-time predictions of the IM at target sites.

  1. Skin sites to predict deep-body temperature while wearing firefighters' personal protective equipment during periodical changes in air temperature.

    Science.gov (United States)

    Kim, Siyeon; Lee, Joo-Young

    2016-04-01

    The aim of this study was to investigate stable and valid measurement sites of skin temperatures as a non-invasive variable to predict deep-body temperature while wearing firefighters' personal protective equipment (PPE) during air temperature changes. Eight male firefighters participated in an experiment which consisted of 60-min exercise and 10-min recovery while wearing PPE without self-contained breathing apparatus (7.75 kg in total PPE mass). Air temperature was periodically fluctuated from 29.5 to 35.5 °C with an amplitude of 6 °C. Rectal temperature was chosen as a deep-body temperature, and 12 skin temperatures were recorded. The results showed that the forehead and chest were identified as the most valid sites to predict rectal temperature (R(2) = 0.826 and 0.824, respectively) in an environment with periodically fluctuated air temperatures. This study suggests that particular skin temperatures are valid as a non-invasive variable when predicting rectal temperature of an individual wearing PPE in changing ambient temperatures. Practitioner Summary: This study should offer assistance for developing a more reliable indirect indicating system of individual heat strain for firefighters in real time, which can be used practically as a precaution of firefighters' heat-related illness and utilised along with physiological monitoring.

  2. Predictability of PV power grid performance on insular sites without weather stations: use of artificial neural networks

    CERN Document Server

    Voyant, Cyril; Paoli, Christophe; Nivet, Marie Laure; Poggi, Philippe; Haurant, P; 10.4229/24thEUPVSEC2009-5BV.2.35

    2010-01-01

    The official meteorological network is poor on the island of Corsica: only three sites being about 50 km apart are equipped with pyranometers which enable measurements by hourly and daily step. These sites are Ajaccio (41\\degree 55'N and 8\\degree 48'E, seaside), Bastia (42\\degree 33'N, 9\\degree 29'E, seaside) and Corte (42\\degree 30'N, 9\\degree 15'E average altitude of 486 meters). This lack of weather station makes difficult the predictability of PV power grid performance. This work intends to study a methodology which can predict global solar irradiation using data available from another location for daily and hourly horizon. In order to achieve this prediction, we have used Artificial Neural Network which is a popular artificial intelligence technique in the forecasting domain. A simulator has been obtained using data available for the station of Ajaccio that is the only station for which we have a lot of data: 16 years from 1972 to 1987. Then we have tested the efficiency of this simulator in two places w...

  3. Predicting species distributions from checklist data using site-occupancy models

    Science.gov (United States)

    Kery, M.; Gardner, B.; Monnerat, C.

    2010-01-01

    Aim: (1) To increase awareness of the challenges induced by imperfect detection, which is a fundamental issue in species distribution modelling; (2) to emphasize the value of replicate observations for species distribution modelling; and (3) to show how 'cheap' checklist data in faunal/floral databases may be used for the rigorous modelling of distributions by site-occupancy models. Location: Switzerland. Methods: We used checklist data collected by volunteers during 1999 and 2000 to analyse the distribution of the blue hawker, Aeshna cyanea (Odonata, Aeshnidae), a common dragonfly in Switzerland. We used data from repeated visits to 1-ha pixels to derive 'detection histories' and apply site-occupancy models to estimate the 'true' species distribution, i.e. corrected for imperfect detection. We modelled blue hawker distribution as a function of elevation and year and its detection probability of elevation, year and season. Results: The best model contained cubic polynomial elevation effects for distribution and quadratic effects of elevation and season for detectability. We compared the site-occupancy model with a conventional distribution model based on a generalized linear model, which assumes perfect detectability (p = 1). The conventional distribution map looked very different from the distribution map obtained using site-occupancy models that accounted for the imperfect detection. The conventional model underestimated the species distribution by 60%, and the slope parameters of the occurrence-elevation relationship were also underestimated when assuming p = 1. Elevation was not only an important predictor of blue hawker occurrence, but also of the detection probability, with a bell-shaped relationship. Furthermore, detectability increased over the season. The average detection probability was estimated at only 0.19 per survey. Main conclusions: Conventional species distribution models do not model species distributions per se but rather the apparent

  4. Support vector machines for prediction of protein signal sequences and their cleavage sites.

    Science.gov (United States)

    Cai, Yu-Dong; Lin, Shuo-liang; Chou, Kuo-Chen

    2003-01-01

    Given a nascent protein sequence, how can one predict its signal peptide or "Zipcode" sequence? This is an important problem for scientists to use signal peptides as a vehicle to find new drugs or to reprogram cells for gene therapy (see, e.g. K.C. Chou, Current Protein and Peptide Science 2002;3:615-22). In this paper, support vector machines (SVMs), a new machine learning method, is applied to approach this problem. The overall rate of correct prediction for 1939 secretary proteins and 1440 nonsecretary proteins was over 91%. It has not escaped our attention that the new method may also serve as a useful tool for further investigating many unclear details regarding the molecular mechanism of the ZIP code protein-sorting system in cells. Copyright 2002 Elsevier Science Inc.

  5. Prediction of the Human EP1 Receptor Binding Site by Homology Modeling and Molecular Dynamics Simulation.

    Science.gov (United States)

    Zare, Behnoush; Madadkar-Sobhani, Armin; Dastmalchi, Siavoush; Mahmoudian, Masoud

    2011-01-01

    The prostanoid receptor EP1 is a G-protein-coupled receptor (GPCR) known to be involved in a variety of pathological disorders such as pain, fever and inflammation. These receptors are important drug targets, but design of subtype specific agonists and antagonists has been partially hampered by the absence of three-dimensional structures for these receptors. To understand the molecular interactions of the PGE2, an endogen ligand, with the EP1 receptor, a homology model of the human EP1 receptor (hEP1R) with all connecting loops was constructed from the 2.6 Å resolution crystal structure (PDB code: 1L9H) of bovine rhodopsin. The initial model generated by MODELLER was subjected to molecular dynamics simulation to assess quality of the model. Also, a step by step ligand-supported model refinement was performed, including initial docking of PGE2 and iloprost in the putative binding site, followed by several rounds of energy minimizations and molecular dynamics simulations. Docking studies were performed for PGE2 and some other related compounds in the active site of the final hEP1 receptor model. The docking enabled us to identify key molecular interactions supported by the mutagenesis data. Also, the correlation of r(2)=0.81 was observed between the Ki values and the docking scores of 15 prostanoid compounds. The results obtained in this study may provide new insights toward understanding the active site conformation of the hEP1 receptor and can be used for the structure-based design of novel specific ligands.

  6. iNitro-Tyr: prediction of nitrotyrosine sites in proteins with general pseudo amino acid composition.

    Directory of Open Access Journals (Sweden)

    Yan Xu

    Full Text Available Nitrotyrosine is one of the post-translational modifications (PTMs in proteins that occurs when their tyrosine residue is nitrated. Compared with healthy people, a remarkably increased level of nitrotyrosine is detected in those suffering from rheumatoid arthritis, septic shock, and coeliac disease. Given an uncharacterized protein sequence that contains many tyrosine residues, which one of them can be nitrated and which one cannot? This is a challenging problem, not only directly related to in-depth understanding the PTM's mechanism but also to the nitrotyrosine-based drug development. Particularly, with the avalanche of protein sequences generated in the postgenomic age, it is highly desired to develop a high throughput tool in this regard. Here, a new predictor called "iNitro-Tyr" was developed by incorporating the position-specific dipeptide propensity into the general pseudo amino acid composition for discriminating the nitrotyrosine sites from non-nitrotyrosine sites in proteins. It was demonstrated via the rigorous jackknife tests that the new predictor not only can yield higher success rate but also is much more stable and less noisy. A web-server for iNitro-Tyr is accessible to the public at http://app.aporc.org/iNitro-Tyr/. For the convenience of most experimental scientists, we have further provided a protocol of step-by-step guide, by which users can easily get their desired results without the need to follow the complicated mathematics that were presented in this paper just for the integrity of its development process. It has not escaped our notice that the approach presented here can be also used to deal with the other PTM sites in proteins.

  7. Cloning and characterization of a novel nuclease from shrimp hepatopancreas, and prediction of its active site.

    Science.gov (United States)

    Wang, W Y; Liaw, S H; Liao, T H

    2000-03-15

    Approximately 95% of the amino acid sequence of a shrimp (Penaeus japonicus) nuclease was derived from protease-digested peptides. A 1461-base cDNA for the nuclease was amplified and sequenced with degenerate primers based on the amino acid sequence and then specific primers by 3' and 5' RACE (rapid amplification of cDNA ends). It contains an open reading frame encoding a putative 21-residue signal peptide and a 381-residue mature protein. The N-terminus of the enzyme is pyroglutamate, deduced from composition and matrix-assisted laser desorption ionization-time-of-flight MS analyses, and confirmed by a glutamine residue in the cDNA sequence. The enzyme has 11 Cys residues, forming five intramolecular disulphides. The eleventh Cys residue was linked to a thiol compound with an estimated molecular mass of between 500 and 700 Da. A sequence similarity search revealed no homologous proteins but residues 205-255 shared a conserved active-site motif within a distinct group of nucleases. His(211) in this conserved motif was shown to be very important in catalysis by site-specific modification with (14)C-labelled iodoacetate. The shrimp nuclease, previously designated DNase I, does indeed possess a low level of hydrolytic activity towards RNA in the presence of Mg(2+) and Ca(2+). The conservation of functionally important residues during distant evolution might imply that the catalytic mechanisms are similar in these nucleases, which should be classified in one subfamily. Finally, an active-site structure for shrimp nuclease was proposed on the basis of published structural data and the results of mutational and biochemical analyses of Serratia nuclease.

  8. Surface properties of the Mars Science Laboratory candidate landing sites: characterization from orbit and predictions

    Science.gov (United States)

    Fergason, R.L.; Christensen, P.R.; Golombek, M.P.; Parker, T.J.

    2012-01-01

    This work describes the interpretation of THEMIS-derived thermal inertia data at the Eberswalde, Gale, Holden, and Mawrth Vallis Mars Science Laboratory (MSL) candidate landing sites and determines how thermophysical variations correspond to morphology and, when apparent, mineralogical diversity. At Eberswalde, the proportion of likely unconsolidated material relative to exposed bedrock or highly indurated surfaces controls the thermal inertia of a given region. At Gale, the majority of the landing site region has a moderate thermal inertia (250 to 410 J m-2 K-1 s-1/2), which is likely an indurated surface mixed with unconsolidated materials. The primary difference between higher and moderate thermal inertia surfaces may be due to the amount of mantling material present. Within the mound of stratified material in Gale, layers are distinguished in the thermal inertia data; the MSL rover could be traversing through materials that are both thermophysically and compositionally diverse. The majority of the Holden ellipse has a thermal inertia of 340 to 475 J m-2 K-1 s-1/2 and consists of bed forms with some consolidated material intermixed. Mawrth Vallis has a mean thermal inertia of 310 J m-2 K-1 s-1/2 and a wide variety of materials is present contributing to the moderate thermal inertia surfaces, including a mixture of bedrock, indurated surfaces, bed forms, and unconsolidated fines. Phyllosilicates have been identified at all four candidate landing sites, and these clay-bearing units typically have a similar thermal inertia value (400 to 500 J m-2 K-1 s-1/2), suggesting physical properties that are also similar.

  9. On the nature of Parr functions to predict the most reactive sites along organic polar reactions

    Science.gov (United States)

    Chamorro, Eduardo; Pérez, Patricia; Domingo, Luis R.

    2013-09-01

    Very recently, local electrophilic and nucleophilic “Parr functions” were empirically introduced (L.R. Domingo, P. Pérez, J.A. Saez RSC Adv. 3 (2013) 1486) in order to properly characterize the most reactive sites along polar chemical reactions. This Letter reports a theoretical advance to the new methodology by identifying these quantities with key Fukui descriptors of the spin-polarized density functional theory. Given such framework properly incorporates the treatment of both charge-transfer and spin-polarization, this finding provides a significant insight and substantial step forward within the field of a chemical reactivity theory based on the conceptual framework of density functional theory.

  10. Type 2 diabetes mellitus: phylogenetic motifs for predicting protein functional sites

    Indian Academy of Sciences (India)

    Ashok Sharma; Tanuja Rastogi; Meenakshi Bhartiya; A K Shasany; S P S Khanuja

    2007-08-01

    Diabetes mellitus, commonly referred to as diabetes, is a medical condition associated with abnormally high levels of glucose (or sugar) in the blood. Keeping this view, we demonstrate the phylogenetic motifs (PMs) identification in type 2 diabetes mellitus very likely corresponding to protein functional sites. In this article, we have identified PMs for all the candidate genes for type 2 diabetes mellitus. Glycine 310 remains conserved for glucokinase and potassium channel KCNJ11. Isoleucine 137 was conserved for insulin receptor and regulatory subunit of a phosphorylating enzyme. Whereas residues valine, leucine, methionine were highly conserved for insulin receptor. Occurrence of proline was very high for calpain 10 gene and glucose transporter

  11. [Prediction of 137Cs behaviour in the soil-plant system in the territory of Semipalatinsk test site].

    Science.gov (United States)

    Spiridonov, S I; Mukusheva, M K; Gontarenko, I A; Fesenko, S V; Baranov, S A

    2005-01-01

    A mathematical model of 137Cs behaviour in the soil-plant system is presented. The model has been parameterized for the area adjacent to the testing area Ground Zero of the Semipalatinsk Test Site. The model describes the main processes responsible for the changes in 137Cs content in the soil solution and, thereby, dynamics of the radionuclide uptake by vegetation. The results are taken from predictive and retrospective calculations that reflect the dynamics of 137Cs distribution by species in soil after nuclear explosions. The importance of factors governing 137Cs accumulation in plants within the STS area is assessed. The analysis of sensitivity of the output model variable to changes in its parameters revealed that the key soil properties significantly influence the results of prediction of 137Cs content in plants.

  12. Identification of off-target cleavage sites of zinc finger nucleases and TAL effector nucleases using predictive models.

    Science.gov (United States)

    Fine, Eli J; Cradick, Thomas J; Bao, Gang

    2014-01-01

    Using engineered nucleases, such as Zinc Finger Nucleases (ZFNs) or Transcription Activator-Like Effector Nucleases (TALENs), to make targeted genomic modifications has become a common technique to create new model organisms and custom cell lines, and has shown great promise for disease treatment. However, these nucleases have the potential for off-target cleavage that could confound interpretation of experimental results and be detrimental for therapeutic use. Here, we describe a method to test for nuclease cleavage at potential off-target sites predicted by bioinformatics models.

  13. Echocardiographic prediction of the site of coronary artery obstruction in acute myocardial infarction.

    Science.gov (United States)

    Pierard, L A; Sprynger, M; Carlier, J

    1987-02-01

    In 49 patients with acute myocardial infarction (AMI), the infarction topography was assessed by cross-sectional echocardiography and the location of coronary artery obstruction were correlated. A ventricular segmentation of 5 right and 16 left ventricular segments was used. The site of coronary obstruction was determined in 45 patients by coronary angiography and by necropsy in 4 patients. The exact location of the obstruction could not be found in 4 patients. The infarct related vessel was the left main artery in 1 patient, the left anterior descending artery (LAD) in 19, the left circumflex in 6 and the right coronary artery in 24. Specific segments were identified for each of the 3 coronary arteries: anteroseptal and anterior segments for LAD, right ventricular segments for the right coronary artery and basal anterolateral segment for the left circumflex. Specific segments (specificity 100%) were also identified for the principal coronary branches: basal anterior for the first anterior descending diagonal (sensitivity 71%), basal anteroseptal for the first septal perforator (83%), middle anterior for the second diagonal (100%), middle anteroseptal for the second septal (89%), basal posteroseptal for a dominant right coronary artery (89%), right ventricular anterolateral segment for the right ventricular marginal branch (83%). Echocardiographic identification of the topography of AMI can be useful in recognizing the infarct-related vessel and identifying the site of coronary artery obstruction.

  14. In Silico Structure Prediction of Human Fatty Acid Synthase-Dehydratase: A Plausible Model for Understanding Active Site Interactions.

    Science.gov (United States)

    John, Arun; Umashankar, Vetrivel; Samdani, A; Sangeetha, Manoharan; Krishnakumar, Subramanian; Deepa, Perinkulam Ravi

    2016-01-01

    Fatty acid synthase (FASN, UniProt ID: P49327) is a multienzyme dimer complex that plays a critical role in lipogenesis. Consequently, this lipogenic enzyme has gained tremendous biomedical importance. The role of FASN and its inhibition is being extensively researched in several clinical conditions, such as cancers, obesity, and diabetes. X-ray crystallographic structures of some of its domains, such as β-ketoacyl synthase, acetyl transacylase, malonyl transacylase, enoyl reductase, β-ketoacyl reductase, and thioesterase, (TE) are already reported. Here, we have attempted an in silico elucidation of the uncrystallized dehydratase (DH) catalytic domain of human FASN. This theoretical model for DH domain was predicted using comparative modeling methods. Different stand-alone tools and servers were used to validate and check the reliability of the predicted models, which suggested it to be a highly plausible model. The stereochemical analysis showed 92.0% residues in favorable region of Ramachandran plot. The initial physiological substrate β-hydroxybutyryl group was docked into active site of DH domain using Glide. The molecular dynamics simulations carried out for 20 ns in apo and holo states indicated the stability and accuracy of the predicted structure in solvated condition. The predicted model provided useful biochemical insights into the substrate-active site binding mechanisms. This model was then used for identifying potential FASN inhibitors using high-throughput virtual screening of the National Cancer Institute database of chemical ligands. The inhibitory efficacy of the top hit ligands was validated by performing molecular dynamics simulation for 20 ns, where in the ligand NSC71039 exhibited good enzyme inhibition characteristics and exhibited dose-dependent anticancer cytotoxicity in retinoblastoma cancer cells in vitro.

  15. Geospatial evaluation of lead bioaccessibility and distribution for site specific prediction of threshold limits.

    Science.gov (United States)

    Bower, Jennifer A; Lister, Sydney; Hazebrouck, Garrett; Perdrial, Nicolas

    2017-10-01

    Recent work identified the need for site-specific Pb bioaccessibility evaluation and scaled contaminant modeling. Pb heterogeneity has made bioaccessibility characterization difficult, and complicated distribution models. Using field testing, bioaccessibility measurement, Integrated Exposure Uptake and Biokinetic (IEUBK) modeling, and geospatial techniques, we propose a framework for conducting applied risk-based, multiscale assessment. This framework was tested and implemented in Burlington, VT, an area of old housing stock and high Pb burden (up to 15 000 mg kg(-1)) derived primarily from paint. After analyzing local soil samples for total and bioaccessible Pb, it was determined that bioaccessible and total Pb were well correlated in this area, through which an average bioaccessibility parameter was derived approximating Pb bioaccessibility for this soil type and Pb impact. This parameter was used with the IEUBK to recommend the local limit for residential soil Pb be reduced from 400 to 360 mg kg(-1), taking into consideration the lowering of the blood lead level threshold for Pb poisoning from 10 to 5 μg dL(-1) by the Centers for Disease Control (CDC). Geospatial investigation incorporated samples collected during this investigation and samples from a high school summer science academy, and relied on three techniques, used at different scales: kriging of total and background Pb alone, kriging of total and background Pb with housing age as a well-sampled, well-correlated secondary variable (cokriging), and inverse distance weighting of total and bioaccessible Pb. Modeling at different scales allowed for characterization of Pb impact at single sites as well as citywide. Model maps show positive correlation between areas of older housing and areas of high Pb burden, as well as potential at different scales for reducing the effects of Pb heterogeneity. Copyright © 2017 Elsevier Ltd. All rights reserved.

  16. Understanding Land-Atmosphere Coupling and its Predictability at the ARM Southern Great Plains Site

    Science.gov (United States)

    Ferguson, C. R.; Song, H. J.; Roundy, J. K.

    2015-12-01

    Ten years ago, the Global Energy and Water EXchanges Global Land Atmosphere Coupling Experiment (GLACE) spotlighted the Southern Great Plains (SGP) for being one of three hotspots globally for land-derived precipitation predictability. Since then, the GLACE results have served as the underlying motivation for numerous subsequent land-atmosphere (L-A) coupling studies over the SGP domain. The range of these studies includes: local point scale studies leveraging surface meteorological and flux measurements at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement SGP (ARM-SGP) Central Facility, regional pentad to monthly scale atmospheric moisture budget analyses based on atmospheric reanalysis, and regional limited duration (2-7 day) coupled model sensitivity experiments. This study has the following three objectives: (1) to provide the common historical context necessary for bridging past and future interdisciplinary characterizations of L-A coupling, (2) to isolate the mechanism(s) for the region's L-A coupling signal, and (3) to evaluate the short range (12-18hr) predictability of soil moisture-precipitation feedbacks. We produce a convective triggering potential—low-level humidity index (CTP-HI)—based climatology of L-A coupling at ARM-SGP for the period 1979-2014 using North American Regional Reanalysis and North American Land Data Assimilation System Phase 2 data. We link the underlying coupling regime classification timeseries to corresponding synoptic-mesoscale weather patterns and bulk atmospheric moisture budget analyses. On the whole, the region's precipitation variability is largely dependent on large-scale moisture transport and the role of the land is nominal. However, we show that surface sensible heat flux can play an important role in modulating diurnal precipitation cycle phase and amplitude—either directly (enhancing CTP) in water-limited conditions or indirectly (increasing HI) in energy-limited conditions. In fact, both 0700

  17. AthMethPre: a web server for the prediction and query of mRNA m(6)A sites in Arabidopsis thaliana.

    Science.gov (United States)

    Xiang, Shunian; Yan, Zhangming; Liu, Ke; Zhang, Yaou; Sun, Zhirong

    2016-10-18

    N(6)-Methyladenosine (m(6)A) is the most prevalent and abundant modification in mRNA that has been linked to many key biological processes. High-throughput experiments have generated m(6)A-peaks across the transcriptome of A. thaliana, but the specific methylated sites were not assigned, which impedes the understanding of m(6)A functions in plants. Therefore, computational prediction of mRNA m(6)A sites becomes emergently important. Here, we present a method to predict the m(6)A sites for A. thaliana mRNA sequence(s). To predict the m(6)A sites of an mRNA sequence, we employed the support vector machine to build a classifier using the features of the positional flanking nucleotide sequence and position-independent k-mer nucleotide spectrum. Our method achieved good performance and was applied to a web server to provide service for the prediction of A. thaliana m(6)A sites. The server also provides a comprehensive database of predicted transcriptome-wide m(6)A sites and curated m(6)A-seq peaks from the literature for query and visualization. The AthMethPre web server is the first web server that provides a user-friendly tool for the prediction and query of A. thaliana mRNA m(6)A sites, which is freely accessible for public use at .

  18. Impact Assessment of Mikania Micrantha on Land Cover and Maxent Modeling to Predict its Potential Invasion Sites

    Science.gov (United States)

    Baidar, T.; Shrestha, A. B.; Ranjit, R.; Adhikari, R.; Ghimire, S.; Shrestha, N.

    2017-05-01

    Mikania micrantha is one of the major invasive alien plant species in tropical moist forest regions of Asia including Nepal. Recently, this weed is spreading at an alarming rate in Chitwan National Park (CNP) and threatening biodiversity. This paper aims to assess the impacts of Mikania micrantha on different land cover and to predict potential invasion sites in CNP using Maxent model. Primary data for this were presence point coordinates and perceived Mikania micrantha cover collected through systematic random sampling technique. Rapideye image, Shuttle Radar Topographic Mission data and bioclimatic variables were acquired as secondary data. Mikania micrantha distribution maps were prepared by overlaying the presence points on image classified by object based image analysis. The overall accuracy of classification was 90 % with Kappa coefficient 0.848. A table depicting the number of sample points in each land cover with respective Mikania micrantha coverage was extracted from the distribution maps to show the impact. The riverine forest was found to be the most affected land cover with 85.98 % presence points and sal forest was found to be very less affected with only 17.02 % presence points. Maxent modeling predicted the areas near the river valley as the potential invasion sites with statistically significant Area Under the Receiver Operating Curve (AUC) value of 0.969. Maximum temperature of warmest month and annual precipitation were identified as the predictor variables that contribute the most to Mikania micrantha's potential distribution.

  19. Prediction of S-Nitrosylation Modification Sites Based on Kernel Sparse Representation Classification and mRMR Algorithm

    Directory of Open Access Journals (Sweden)

    Guohua Huang

    2014-01-01

    Full Text Available Protein S-nitrosylation plays a very important role in a wide variety of cellular biological activities. Hitherto, accurate prediction of S-nitrosylation sites is still of great challenge. In this paper, we presented a framework to computationally predict S-nitrosylation sites based on kernel sparse representation classification and minimum Redundancy Maximum Relevance algorithm. As much as 666 features derived from five categories of amino acid properties and one protein structure feature are used for numerical representation of proteins. A total of 529 protein sequences collected from the open-access databases and published literatures are used to train and test our predictor. Computational results show that our predictor achieves Matthews’ correlation coefficients of 0.1634 and 0.2919 for the training set and the testing set, respectively, which are better than those of k-nearest neighbor algorithm, random forest algorithm, and sparse representation classification algorithm. The experimental results also indicate that 134 optimal features can better represent the peptides of protein S-nitrosylation than the original 666 redundant features. Furthermore, we constructed an independent testing set of 113 protein sequences to evaluate the robustness of our predictor. Experimental result showed that our predictor also yielded good performance on the independent testing set with Matthews’ correlation coefficients of 0.2239.

  20. Parameter estimation method and updating of regional prediction equations for ungaged sites in the desert region of California

    Science.gov (United States)

    Barth, Nancy A.; Veilleux, Andrea G.

    2012-01-01

    The U.S. Geological Survey (USGS) is currently updating at-site flood frequency estimates for USGS streamflow-gaging stations in the desert region of California. The at-site flood-frequency analysis is complicated by short record lengths (less than 20 years is common) and numerous zero flows/low outliers at many sites. Estimates of the three parameters (mean, standard deviation, and skew) required for fitting the log Pearson Type 3 (LP3) distribution are likely to be highly unreliable based on the limited and heavily censored at-site data. In a generalization of the recommendations in Bulletin 17B, a regional analysis was used to develop regional estimates of all three parameters (mean, standard deviation, and skew) of the LP3 distribution. A regional skew value of zero from a previously published report was used with a new estimated mean squared error (MSE) of 0.20. A weighted least squares (WLS) regression method was used to develop both a regional standard deviation and a mean model based on annual peak-discharge data for 33 USGS stations throughout California’s desert region. At-site standard deviation and mean values were determined by using an expected moments algorithm (EMA) method for fitting the LP3 distribution to the logarithms of annual peak-discharge data. Additionally, a multiple Grubbs-Beck (MGB) test, a generalization of the test recommended in Bulletin 17B, was used for detecting multiple potentially influential low outliers in a flood series. The WLS regression found that no basin characteristics could explain the variability of standard deviation. Consequently, a constant regional standard deviation model was selected, resulting in a log-space value of 0.91 with a MSE of 0.03 log units. Yet drainage area was found to be statistically significant at explaining the site-to-site variability in mean. The linear WLS regional mean model based on drainage area had a Pseudo- 2 R of 51 percent and a MSE of 0.32 log units. The regional parameter

  1. Directed Hierarchical Patterning of Polycarbonate Bisphenol A Glass Surface along Predictable Sites

    Directory of Open Access Journals (Sweden)

    Mazen Khaled

    2015-01-01

    Full Text Available This paper reports a new approach in designing textured and hierarchical surfaces on polycarbonate bisphenol A type glass to improve hydrophobicity and dust repellent application for solar panels. Solvent- and vapor-induced crystallization of thermoplastic glass polycarbonate bisphenol A (PC is carried out to create hierarchically structured surfaces. In this approach dichloromethane (DCM and acetone are used in sequence. Samples are initially immersed in DCM liquid to generate nanopores, followed by exposing to acetone vapor resulting in the generation of hierarchical structure along the interporous sites. The effects of exposure time on the size, density, and distance of the generated spherules and gaps are studied and correlated with the optical transmittance and contact angle measurements at the surface. At optimized exposure time a contact angle of 98° was achieved with 80% optical transmittance. To further increase the hydrophobicity while maintaining optical properties, the hierarchical surfaces were coated with a transparent composite of tetraethyl orthosilicate as precursor and hexamethyldisilazane as silylation agent resulting in an average contact angle of 135.8° and transmittance of around 70%. FTIR and AFM characterization techniques are employed to study the composition and morphology of the generated surfaces.

  2. Unique Path Partitions

    DEFF Research Database (Denmark)

    Bessenrodt, Christine; Olsson, Jørn Børling; Sellers, James A.

    2013-01-01

    We give a complete classification of the unique path partitions and study congruence properties of the function which enumerates such partitions.......We give a complete classification of the unique path partitions and study congruence properties of the function which enumerates such partitions....

  3. Prediction of DtxR regulon: Identification of binding sites and operons controlled by Diphtheria toxin repressor in Corynebacterium diphtheriae

    Directory of Open Access Journals (Sweden)

    Hasnain Seyed

    2004-09-01

    Full Text Available Abstract Background The diphtheria toxin repressor, DtxR, of Corynebacterium diphtheriae has been shown to be an iron-activated transcription regulator that controls not only the expression of diphtheria toxin but also of iron uptake genes. This study aims to identify putative binding sites and operons controlled by DtxR to understand the role of DtxR in patho-physiology of Corynebacterium diphtheriae. Result Positional Shannon relative entropy method was used to build the DtxR-binding site recognition profile and the later was used to identify putative regulatory sites of DtxR within C. diphtheriae genome. In addition, DtxR-regulated operons were also identified taking into account the predicted DtxR regulatory sites and genome annotation. Few of the predicted motifs were experimentally validated by electrophoretic mobility shift assay. The analysis identifies motifs upstream to the novel iron-regulated genes that code for Formamidopyrimidine-DNA glycosylase (FpG, an enzyme involved in DNA-repair and starvation inducible DNA-binding protein (Dps which is involved in iron storage and oxidative stress defense. In addition, we have found the DtxR motifs upstream to the genes that code for sortase which catalyzes anchoring of host-interacting proteins to the cell wall of pathogenic bacteria and the proteins of secretory system which could be involved in translocation of various iron-regulated virulence factors including diphtheria toxin. Conclusions We have used an in silico approach to identify the putative binding sites and genes controlled by DtxR in Corynebacterium diphtheriae. Our analysis shows that DtxR could provide a molecular link between Fe+2-induced Fenton's reaction and protection of DNA from oxidative damage. DtxR-regulated Dps prevents lethal combination of Fe+2 and H2O2 and also protects DNA by nonspecific DNA-binding. In addition DtxR could play an important role in host interaction and virulence by regulating the levels of sortase

  4. Dopamine transporter comparative molecular modeling and binding site prediction using the LeuT(Aa) leucine transporter as a template.

    Science.gov (United States)

    Indarte, Martín; Madura, Jeffry D; Surratt, Christopher K

    2008-02-15

    Pharmacological and behavioral studies indicate that binding of cocaine and the amphetamines by the dopamine transporter (DAT) protein is principally responsible for initiating the euphoria and addiction associated with these drugs. The lack of an X-ray crystal structure for the DAT or any other member of the neurotransmitter:sodium symporter (NSS) family has hindered understanding of psychostimulant recognition at the atomic level; structural information has been obtained largely from mutagenesis and biophysical studies. The recent publication of a crystal structure for the bacterial leucine transporter LeuT(Aa), a distantly related NSS family homolog, provides for the first time a template for three-dimensional comparative modeling of NSS proteins. A novel computational modeling approach using the capabilities of the Molecular Operating Environment program MOE 2005.06 in conjunction with other comparative modeling servers generated the LeuT(Aa)-directed DAT model. Probable dopamine and amphetamine binding sites were identified within the DAT model using multiple docking approaches. Binding sites for the substrate ligands (dopamine and amphetamine) overlapped substantially with the analogous region of the LeuT(Aa) crystal structure for the substrate leucine. The docking predictions implicated DAT side chains known to be critical for high affinity ligand binding and suggest novel mutagenesis targets in elucidating discrete substrate and inhibitor binding sites. The DAT model may guide DAT ligand QSAR studies, and rational design of novel DAT-binding therapeutics.

  5. Mixed valency and site-preference chemistry for cerium and its compounds: A predictive density-functional theory study

    Energy Technology Data Exchange (ETDEWEB)

    Alam, Aftab [Ames Laboratory; Johnson, Duane D. [Ames Laboratory

    2014-06-01

    Cerium and its technologically relevant compounds are examples of anomalous mixed valency, originating from two competing oxidation states—itinerant Ce4+ and localized Ce3+. Under applied stress, anomalous transitions are observed but not well understood. Here we treat mixed valency as an “alloy” problem involving two valences with competing and numerous site-occupancy configurations. We use density-functional theory with Hubbard U (i.e., DFT+U) to evaluate the effective valence and predict properties, including controlling the valence by pseudoternary alloying. For Ce and its compounds, such as (Ce,La)2(Fe,Co)14B permanent magnets, we find a stable mixed-valent α state near the spectroscopic value of νs=3.53. Ce valency in compounds depends on its steric volume and local chemistry. For La doping, Ce valency shifts towards γ-like Ce3+, as expected from steric volume; for Co doping, valency depends on local Ce-site chemistry and steric volume. Our approach captures the key origins of anomalous valency and site-preference chemistry in complex compounds.

  6. Agenda Trending: Reciprocity and the Predictive Capacity of Social Networking Sites in Intermedia Agenda Setting across Topics over Time

    Directory of Open Access Journals (Sweden)

    Jacob Groshek

    2013-08-01

    Full Text Available In the contemporary converged media environment, agenda setting is being transformed by the dramatic growth of audiences that are simultaneously media users and producers. The study reported here addresses related gaps in the literature by first comparing the topical agendas of two leading traditional media outlets (New York Times and CNN with the most frequently shared stories and trending topics on two widely popular Social Networking Sites (Facebook and Twitter. Time-series analyses of the most prominent topics identify the extent to which traditional media sets the agenda for social media as well as reciprocal agenda-setting effects of social media topics entering traditional media agendas. In addition, this study examines social intermedia agenda setting topically and across time within social networking sites, and in so doing, adds a vital understanding of where traditional media, online uses, and social media content intersect around instances of focusing events, particularly elections. Findings identify core differences between certain traditional and social media agendas, but also within social media agendas that extend from uses examined here. Additional results further suggest important topical and event-oriented limitations upon the predictive capacit of social networking sites to shape traditional media agendas over time.

  7. Structure prediction and binding sites analysis of curcin protein of Jatropha curcas using computational approaches.

    Science.gov (United States)

    Srivastava, Mugdha; Gupta, Shishir K; Abhilash, P C; Singh, Nandita

    2012-07-01

    Ribosome inactivating proteins (RIPs) are defense proteins in a number of higher-plant species that are directly targeted toward herbivores. Jatropha curcas is one of the biodiesel plants having RIPs. The Jatropha seed meal, after extraction of oil, is rich in curcin, a highly toxic RIP similar to ricin, which makes it unsuitable for animal feed. Although the toxicity of curcin is well documented in the literature, the detailed toxic properties and the 3D structure of curcin has not been determined by X-ray crystallography, NMR spectroscopy or any in silico techniques to date. In this pursuit, the structure of curcin was modeled by a composite approach of 3D structure prediction using threading and ab initio modeling. Assessment of model quality was assessed by methods which include Ramachandran plot analysis and Qmean score estimation. Further, we applied the protein-ligand docking approach to identify the r-RNA binding residue of curcin. The present work provides the first structural insight into the binding mode of r-RNA adenine to the curcin protein and forms the basis for designing future inhibitors of curcin. Cloning of a future peptide inhibitor within J. curcas can produce non-toxic varieties of J. curcas, which would make the seed-cake suitable as animal feed without curcin detoxification.

  8. A class of edit kernels for SVMs to predict translation initiation sites in eukaryotic mRNAs.

    Science.gov (United States)

    Li, Haifeng; Jiang, Tao

    2005-01-01

    The prediction of translation initiation sites (TISs) in eukaryotic mRNAs has been a challenging problem in computational molecular biology. In this paper, we present a new algorithm to recognize TISs with a very high accuracy. Our algorithm includes two novel ideas. First, we introduce a class of new sequence-similarity kernels based on string editing, called edit kernels, for use with support vector machines (SVMs) in a discriminative approach to predict TISs. The edit kernels are simple and have significant biological and probabilistic interpretations. Although the edit kernels are not positive definite, it is easy to make the kernel matrix positive definite by adjusting the parameters. Second, we convert the region of an input mRNA sequence downstream to a putative TIS into an amino acid sequence before applying SVMs to avoid the high redundancy in the genetic code. The algorithm has been implemented and tested on previously published data. Our experimental results on real mRNA data show that both ideas improve the prediction accuracy greatly and that our method performs significantly better than those based on neural networks and SVMs with polynomial kernels or Salzberg kernels.

  9. A comprehensive software suite for protein family construction and functional site prediction

    Science.gov (United States)

    Haft, David Renfrew; Haft, Daniel H.

    2017-01-01

    In functionally diverse protein families, conservation in short signature regions may outperform full-length sequence comparisons for identifying proteins that belong to a subgroup within which one specific aspect of their function is conserved. The SIMBAL workflow (Sites Inferred by Metabolic Background Assertion Labeling) is a data-mining procedure for finding such signature regions. It begins by using clues from genomic context, such as co-occurrence or conserved gene neighborhoods, to build a useful training set from a large number of uncharacterized but mutually homologous proteins. When training set construction is successful, the YES partition is enriched in proteins that share function with the user’s query sequence, while the NO partition is depleted. A selected query sequence is then mined for short signature regions whose closest matches overwhelmingly favor proteins from the YES partition. High-scoring signature regions typically contain key residues critical to functional specificity, so proteins with the highest sequence similarity across these regions tend to share the same function. The SIMBAL algorithm was described previously, but significant manual effort, expertise, and a supporting software infrastructure were required to prepare the requisite training sets. Here, we describe a new, distributable software suite that speeds up and simplifies the process for using SIMBAL, most notably by providing tools that automate training set construction. These tools have broad utility for comparative genomics, allowing for flexible collection of proteins or protein domains based on genomic context as well as homology, a capability that can greatly assist in protein family construction. Armed with this new software suite, SIMBAL can serve as a fast and powerful in silico alternative to direct experimentation for characterizing proteins and their functional interactions. PMID:28182651

  10. Theoretical prediction of single-site enthalpies of surface protonation for oxides and silicates in water

    Energy Technology Data Exchange (ETDEWEB)

    Sverjensky, D.A.; Sahai, N. [Johns Hopkins Univ., Baltimore, MD (United States). Morton K. Blaustein Dept. of Earth and Planetary Sciences

    1998-12-01

    Surface protonation is the most fundamental adsorption process of geochemical interest. Yet remarkably little is known about protonation of mineral surfaces at temperatures greater than 25 C. Experimentally derived standard enthalpies of surface protonation, {Delta}H{degree}{sub r,1}, {Delta}H{degree}{sub r,2}, and {Delta}H{degree}{sub r,ZPC}, correspond to the reactions >SOH + H{sup +} = >SOH{sub 2}{sup +}; >SO{sup {minus}} + H{sup +} = >SOH; and >SO{sup {minus}} + 2H{sup +} = >SOH{sub 2}{sup +}, respectively, and provide a starting point for evaluating the role of surface protonation in geochemical processes at elevated temperatures. However, the experimental data for oxides do not have a theoretical explanation, and data are completely lacking for silicates other than SiO{sub 2}. In the present study, the combination of crystal chemical and Born solvation theory provides a theoretical basis for explaining the variation of the enthalpies of protonation of oxides. Experimental values of {Delta}H{degree}{sub r,1}, {Delta}H{degree}{sub r,2}, and {Delta}H{degree}{sub r,ZPC} consistent with the triple layer model can be expressed in terms of the inverse of the dielectric constant (1/{epsilon}) and the Pauling bond strength per angstrom (s/r{sub M-OH}) of each mineral. Predicted standard enthalpies of surface protonation for oxides and silicates extend over the ranges (in kcal/mole):{Delta}H{degree}{sub r,1} {approx} {minus}3 to {minus}15; {Delta}H{degree}{sub r,2} {approx} {minus}5 to {minus}18; {Delta}H{degree}{sub r,ZPC} {approx} {minus}4 to {minus}33.

  11. Sensitivity and predictive uncertainty of the ACASA model at a spruce forest site

    Directory of Open Access Journals (Sweden)

    K. Staudt

    2010-06-01

    Full Text Available The sensitivity and predictive uncertainty of the Advanced Canopy-Atmosphere-Soil Algorithm (ACASA was assessed by employing the Generalized Likelihood Uncertainty Estimation (GLUE method. ACASA is a stand-scale, multi-layer soil-vegetation-atmosphere transfer model that incorporates a third order closure method to simulate the turbulent exchange of energy and matter within and above the canopy. Fluxes simulated by the model were compared to sensible and latent heat fluxes as well as the net ecosystem exchange measured by an eddy-covariance system above the spruce canopy at the FLUXNET-station Waldstein-Weidenbrunnen in the Fichtelgebirge Mountains in Germany. From each of the intensive observation periods carried out within the EGER project (ExchanGE processes in mountainous Regions in autumn 2007 and summer 2008, five days of flux measurements were selected. A large number (20 000 of model runs using randomly generated parameter sets were performed and goodness of fit measures for all fluxes for each of these runs calculated. The 10% best model runs for each flux were used for further investigation of the sensitivity of the fluxes to parameter values and to calculate uncertainty bounds.

    A strong sensitivity of the individual fluxes to a few parameters was observed, such as the leaf area index. However, the sensitivity analysis also revealed the equifinality of many parameters in the ACASA model for the investigated periods. The analysis of two time periods, each representing different meteorological conditions, provided an insight into the seasonal variation of parameter sensitivity. The calculated uncertainty bounds demonstrated that all fluxes were well reproduced by the ACASA model. In general, uncertainty bounds encompass measured values better when these are conditioned on the respective individual flux only and not on all three fluxes concurrently. Structural weaknesses of the ACASA model concerning the soil respiration

  12. PROOF OF CONCEPT TEST OF A UNIQUE GASEOUS PERFLUROCARBON TRACER SYSTEM FOR VERIFICATION AND LONG TERM MONITORING OF CAPS AND COVER SYSTEMS CONDUCTED AT THE SAVANNAH RIVER SITE BENTONITE MAT TEST FACILITY.

    Energy Technology Data Exchange (ETDEWEB)

    HEISER,J.; SULLIVAN,T.; SERRATO,M.

    2002-02-24

    Engineered covers have been placed on top of buried/subsurface wastes to minimize water infiltration and therefore, release of hazardous contaminants. In order for the cover to protect the environment it must remain free of holes and breaches throughout its service life. Covers are subject to subsidence, erosion, animal intrusion, plant root infiltration, etc., all of which will affect the overall performance of the cover. The U.S. Department of Energy Environmental Management (DOE-EM) Program 2006 Accelerated Cleanup Plan is pushing for rapid closure of many of the DOE facilities. This will require a great number of new cover systems. Some of these new covers are expected to maintain their performance for periods of up to 1000 years. Long-term stewardship will require monitoring/verification of cover performance over the course of the designed lifetime. In addition, many existing covers are approaching the end of their design life and will need validation of current performance (if continued use is desired) or replacement (if degraded). The need for a reliable method of verification and long-term monitoring is readily apparent. Currently, failure is detected through monitoring wells downstream of the waste site. This is too late as the contaminants have already left the disposal area. The proposed approach is the use of gaseous Perfluorocarbon tracers (PFT) to verify and monitor cover performance. It is believed that PFTs will provide a technology that can verify a cover meets all performance objectives upon installation, be capable of predicting changes in cover performance and failure (defined as contaminants leaving the site) before it happens, and be cost-effective in supporting stewardship needs. The PFTs are injected beneath the cover and air samples taken above (either air samples or soil gas samples) at the top of the cover. The location, concentrations, and time of arrival of the tracer(s) provide a direct measure of cover performance. PFT technology can

  13. Predicting Social Networking Site Use and Online Communication Practices among Adolescents: The Role of Access and Device Ownership

    Directory of Open Access Journals (Sweden)

    Drew P. Cingel

    2014-06-01

    Full Text Available Given adolescents' heavy social media use, this study examined a number of predictors of adolescent social media use, as well as predictors of online communication practices. Using data collected from a national sample of 467 adolescents between the ages of 13 and 17, results indicate that demographics, technology access, and technology ownership are related to social media use and communication practices. Specifically, females log onto and use more constructive com-munication practices on Facebook compared to males. Additionally, adolescents who own smartphones engage in more constructive online communication practices than those who share regular cell phones or those who do not have access to a cell phone. Overall, results imply that ownership of mobile technologies, such as smartphones and iPads, may be more predictive of social networking site use and online communication practices than general ownership of technology.

  14. Predicting Social Networking Site Use and Online Communication Practices among Adolescents: The Role of Access and Device Ownership

    Directory of Open Access Journals (Sweden)

    Drew P. Cingel

    2014-01-01

    Full Text Available Given adolescents' heavy social media use, this study examined a number of predictors of adolescent social media use, as well as predictors of online communication practices. Using data collected from a national sample of 467 adolescents between the ages of 13 and 17, results indicate that demographics, technology access, and technology ownership are related to social media use and communication practices. Specifically, females log onto and use more constructive communication practices on Facebook compared to males. Additionally, adolescents who own smartphones engage in more constructive online communication practices than those who share regular cell phones or those who do not have access to a cell phone. Overall, results imply that ownership of mobile technologies, such as smartphones and iPads, may be more predictive of social networking site use and online communication practices than general ownership of technology.

  15. Predictive models of gas sorption in a metal-organic framework with open-metal sites and small pore sizes.

    Science.gov (United States)

    Pham, Tony; Forrest, Katherine A; Franz, Douglas M; Guo, Zhiyong; Chen, Banglin; Space, Brian

    2017-07-19

    Simulations of CO2 and H2 sorption were performed in UTSA-20, a metal-organic framework (MOF) having zyg topology and composed of Cu(2+) ions coordinated to 3,3',3'',5,5',5''-benzene-1,3,5-triyl-hexabenzoate (BHB) linkers. Previous experimental studies have shown that this MOF displays remarkable CO2 sorption properties and exhibits one of the highest gravimetric H2 uptakes at 77 K/1.0 atm (2.9 wt%) [Z. Guo, et al. Angew. Chem., Int. Ed., 2011, 50, 3178-3181]. For both sorbates, the simulations were executed with the inclusion of explicit many-body polarization interactions, which was necessary to reproduce sorption onto the open-metal sites. Non-polarizable potentials were also utilized for simulations of CO2 sorption as a control. The simulated excess sorption isotherms for both CO2 and H2 are in very good agreement with the corresponding experimental data over a wide range of temperatures and pressures, thus demonstrating the accuracy and predictive power of the polarizable potentials used herein. The theoretical isosteric heat of adsorption (Qst) values are also in good agreement with the newly reported experimental Qst values for the respective sorbates in UTSA-20. Sorption onto the more positively charged Cu(2+) ion of the [Cu2(O2CR)4] cluster was observed for both CO2 and H2. However, a binding site with energetics comparable to that for an open-metal site was also discovered for both sorbates. A radial distribution function (g(r)) analysis about the preferential Cu(2+) ions for CO2 and H2 revealed that both sorbates display different trends for the relative occupancy about such sites upon increasing/decreasing the pressure in the MOF. Overall, this study provides insights into the CO2 and H2 sorption mechanisms in this MOF containing open-metal sites and small pore sizes for the first time through a classical polarizable force field.

  16. The predicted 3D structure of the human D2 dopamine receptor and the binding site and binding affinities for agonists and antagonists

    Science.gov (United States)

    Kalani, M. Yashar S.; Vaidehi, Nagarajan; Hall, Spencer E.; Trabanino, Rene J.; Freddolino, Peter L.; Kalani, Maziyar A.; Floriano, Wely B.; Tak Kam, Victor Wai; Goddard, William A., III

    2004-03-01

    Dopamine neurotransmitter and its receptors play a critical role in the cell signaling process responsible for information transfer in neurons functioning in the nervous system. Development of improved therapeutics for such disorders as Parkinson's disease and schizophrenia would be significantly enhanced with the availability of the 3D structure for the dopamine receptors and of the binding site for dopamine and other agonists and antagonists. We report here the 3D structure of the long isoform of the human D2 dopamine receptor, predicted from primary sequence using first-principles theoretical and computational techniques (i.e., we did not use bioinformatic or experimental 3D structural information in predicting structures). The predicted 3D structure is validated by comparison of the predicted binding site and the relative binding affinities of dopamine, three known dopamine agonists (antiparkinsonian), and seven known antagonists (antipsychotic) in the D2 receptor to experimentally determined values. These structures correctly predict the critical residues for binding dopamine and several antagonists, identified by mutation studies, and give relative binding affinities that correlate well with experiments. The predicted binding site for dopamine and agonists is located between transmembrane (TM) helices 3, 4, 5, and 6, whereas the best antagonists bind to a site involving TM helices 2, 3, 4, 6, and 7 with minimal contacts to TM helix 5. We identify characteristic differences between the binding sites of agonists and antagonists.

  17. Prediction of translation initiation sites in human mRNA sequences with AUG start codon in weak Kozak context: A neural network approach.

    Science.gov (United States)

    Tikole, Suhas; Sankararamakrishnan, Ramasubbu

    2008-05-16

    Translation of eukaryotic mRNAs is often regulated by nucleotides around the start codon. A purine at position -3 and a guanine at position +4 contribute significantly to enhance the translation efficiency. Algorithms to predict the translation initiation site often fail to predict the start site if the sequence context is not present. We have developed a neural network method to predict the initiation site of mRNA sequences that lack the preferred nucleotides at the positions -3 and +4 surrounding the translation initiation site. Neural networks of various architectures comprising different number of hidden layers were designed and tested for various sizes of windows of nucleotides surrounding translation initiation sites. We found that the neural network with two hidden layers showed a sensitivity of 83% and specificity of 73% indicating a vastly improved performance in successfully predicting the translation initiation site of mRNA sequences with weak Kozak context. WeakAUG server is freely available at http://bioinfo.iitk.ac.in/AUGPred/.

  18. The probabilities of unique events.

    Directory of Open Access Journals (Sweden)

    Sangeet S Khemlani

    Full Text Available Many theorists argue that the probabilities of unique events, even real possibilities such as President Obama's re-election, are meaningless. As a consequence, psychologists have seldom investigated them. We propose a new theory (implemented in a computer program in which such estimates depend on an intuitive non-numerical system capable only of simple procedures, and a deliberative system that maps intuitions into numbers. The theory predicts that estimates of the probabilities of conjunctions should often tend to split the difference between the probabilities of the two conjuncts. We report two experiments showing that individuals commit such violations of the probability calculus, and corroborating other predictions of the theory, e.g., individuals err in the same way even when they make non-numerical verbal estimates, such as that an event is highly improbable.

  19. Unique Access to Learning

    Science.gov (United States)

    Goble, Don

    2009-01-01

    This article describes the many learning opportunities that broadcast technology students at Ladue Horton Watkins High School in St. Louis, Missouri, experience because of their unique access to technology and methods of learning. Through scaffolding, stepladder techniques, and trial by fire, students learn to produce multiple television programs,…

  20. Multiple repeats of Helicobacter pylori CagA EPIYA-C phosphorylation sites predict risk of gastric ulcer in Iran.

    Science.gov (United States)

    Honarmand-Jahromy, Sahar; Siavoshi, Farideh; Malekzadeh, Reza; Sattari, Taher Nejad; Latifi-Navid, Saeid

    2015-12-01

    Biological activity of Helicobacter pylori oncoprotein CagA is determined by a diversity in the tyrosine phosphorylation motif sites. In the present study, the diversity and the type of the H. pylori CagA EPIYA motifs and their association with gastric ulcer (GU) and duodenal ulcer (DU) in Iranian dyspeptic patients were assessed. PCR amplification, sequencing, and bioinformatic analysis were performed to determine the pattern of CagA EPIYA motifs. Of 168 H. pylori cagA(+) strains, the frequency of ABC was 93.50%, ABCCC 5.40%, ABC + ABCCC 0.6% and ABCC 0.6%. There was no EPIYA-D segment. The ABCCC pattern of EPIYA motif was more frequent in the H. pylori isolates from GU (8/50, 16%) than in those from chronic gastritis (CG) (0/81, 0%) (P = 0). In contrast, The ABC pattern of EPIYA motif was less frequent in the H. pylori isolates from GU (41/50, 82%) than in those from CG (80/81, 98.80%) (Age-sex-adjusted odds ratio (OR) = 0.020, 95% CI = 0.002-0.259; P = 0.003). The distribution of the ABC motif was almost the same in H. pylori isolates from CG (98.80%) and DU diseases (97.30%). There was no significant association between the number of CagA EPIYA-C segment and DU (P > 0.05). We have proposed that CagA from Iranian H. pylori strains were Western type and all strains had active phosphorylation sites. The three EPIYA-C motifs of CagA were more frequently observed in the H. pylori strains from GU; thus it might be an important biomarker for predicting the GU risk in Iran.

  1. Predicting summer site occupancy for an invasive species, the common brushtail possum (Trichosurus vulpecula, in an urban environment.

    Directory of Open Access Journals (Sweden)

    Amy L Adams

    Full Text Available Invasive species are often favoured in fragmented, highly-modified, human-dominated landscapes such as urban areas. Because successful invasive urban adapters can occupy habitat that is quite different from that in their original range, effective management programmes for invasive species in urban areas require an understanding of distribution, habitat and resource requirements at a local scale that is tailored to the fine-scale heterogeneity typical of urban landscapes. The common brushtail possum (Trichosurus vulpecula is one of New Zealand's most destructive invasive pest species. As brushtail possums traditionally occupy forest habitat, control in New Zealand has focussed on rural and forest habitats, and forest fragments in cities. However, as successful urban adapters, possums may be occupying a wider range of habitats. Here we use site occupancy methods to determine the distribution of brushtail possums across five distinguishable urban habitat types during summer, which is when possums have the greatest impacts on breeding birds. We collected data on possum presence/absence and habitat characteristics, including possible sources of supplementary food (fruit trees, vegetable gardens, compost heaps, and the availability of forest fragments from 150 survey locations. Predictive distribution models constructed using the programme PRESENCE revealed that while occupancy rates were highest in forest fragments, possums were still present across a large proportion of residential habitat with occupancy decreasing as housing density increased and green cover decreased. The presence of supplementary food sources was important in predicting possum occupancy, which may reflect the high nutritional value of these food types. Additionally, occupancy decreased as the proportion of forest fragment decreased, indicating the importance of forest fragments in determining possum distribution. Control operations to protect native birds from possum predation in

  2. Predicting summer site occupancy for an invasive species, the common brushtail possum (Trichosurus vulpecula), in an urban environment.

    Science.gov (United States)

    Adams, Amy L; Dickinson, Katharine J M; Robertson, Bruce C; van Heezik, Yolanda

    2013-01-01

    Invasive species are often favoured in fragmented, highly-modified, human-dominated landscapes such as urban areas. Because successful invasive urban adapters can occupy habitat that is quite different from that in their original range, effective management programmes for invasive species in urban areas require an understanding of distribution, habitat and resource requirements at a local scale that is tailored to the fine-scale heterogeneity typical of urban landscapes. The common brushtail possum (Trichosurus vulpecula) is one of New Zealand's most destructive invasive pest species. As brushtail possums traditionally occupy forest habitat, control in New Zealand has focussed on rural and forest habitats, and forest fragments in cities. However, as successful urban adapters, possums may be occupying a wider range of habitats. Here we use site occupancy methods to determine the distribution of brushtail possums across five distinguishable urban habitat types during summer, which is when possums have the greatest impacts on breeding birds. We collected data on possum presence/absence and habitat characteristics, including possible sources of supplementary food (fruit trees, vegetable gardens, compost heaps), and the availability of forest fragments from 150 survey locations. Predictive distribution models constructed using the programme PRESENCE revealed that while occupancy rates were highest in forest fragments, possums were still present across a large proportion of residential habitat with occupancy decreasing as housing density increased and green cover decreased. The presence of supplementary food sources was important in predicting possum occupancy, which may reflect the high nutritional value of these food types. Additionally, occupancy decreased as the proportion of forest fragment decreased, indicating the importance of forest fragments in determining possum distribution. Control operations to protect native birds from possum predation in cities should

  3. Ambulatory teaching: Do approaches to learning predict the site and preceptor characteristics valued by clerks and residents in the ambulatory setting?

    Directory of Open Access Journals (Sweden)

    Kirby John R

    2005-10-01

    Full Text Available Abstract Background In a study to determine the site and preceptor characteristics most valued by clerks and residents in the ambulatory setting we wished to confirm whether these would support effective learning. The deep approach to learning is thought to be more effective for learning than surface approaches. In this study we determined how the approaches to learning of clerks and residents predicted the valued site and preceptor characteristics in the ambulatory setting. Methods Postal survey of all medical residents and clerks in training in Ontario determining the site and preceptor characteristics most valued in the ambulatory setting. Participants also completed the Workplace Learning questionnaire that includes 3 approaches to learning scales and 3 workplace climate scales. Multiple regression analysis was used to predict the preferred site and preceptor characteristics as the dependent variables by the average scores of the approaches to learning and perception of workplace climate scales as the independent variables. Results There were 1642 respondents, yielding a 47.3% response rate. Factor analysis revealed 7 preceptor characteristics and 6 site characteristics valued in the ambulatory setting. The Deep approach to learning scale predicted all of the learners' preferred preceptor characteristics (β = 0.076 to β = 0.234, p Direction was more strongly associated with the Surface Rational approach (β = .252, p Surface Disorganized approach to learning (β = .154, p Deep approach. The Deep approach to learning scale predicted valued site characteristics of Office Management, Patient Logistics, Objectives and Preceptor Interaction (p Surface Rational approach to learning predicted valuing Learning Resources and Clinic Set-up (β = .09, p = .001; β = .197, p Surface Disorganized approach to learning weakly negatively predicted Patient Logistics (β = -.082, p = .003 and positively the Learning Resources (β = .088, p = .003. Climate

  4. eF-seek: prediction of the functional sites of proteins by searching for similar electrostatic potential and molecular surface shape

    Science.gov (United States)

    Kinoshita, Kengo; Murakami, Yoichi; Nakamura, Haruki

    2007-01-01

    We have developed a method to predict ligand-binding sites in a new protein structure by searching for similar binding sites in the Protein Data Bank (PDB). The similarities are measured according to the shapes of the molecular surfaces and their electrostatic potentials. A new web server, eF-seek, provides an interface to our search method. It simply requires a coordinate file in the PDB format, and generates a prediction result as a virtual complex structure, with the putative ligands in a PDB format file as the output. In addition, the predicted interacting interface is displayed to facilitate the examination of the virtual complex structure on our own applet viewer with the web browser (URL: http://eF-site.hgc.jp/eF-seek). PMID:17567616

  5. Development of a regression model to predict copper toxicity to Daphnia magna and site-specific copper criteria across multiple surface-water drainages in an arid landscape.

    Science.gov (United States)

    Fulton, Barry A; Meyer, Joseph S

    2014-08-01

    The water effect ratio (WER) procedure developed by the US Environmental Protection Agency is commonly used to derive site-specific criteria for point-source metal discharges into perennial waters. However, experience is limited with this method in the ephemeral and intermittent systems typical of arid climates. The present study presents a regression model to develop WER-based site-specific criteria for a network of ephemeral and intermittent streams influenced by nonpoint sources of Cu in the southwestern United States. Acute (48-h) Cu toxicity tests were performed concurrently with Daphnia magna in site water samples and hardness-matched laboratory waters. Median effect concentrations (EC50s) for Cu in site water samples (n=17) varied by more than 12-fold, and the range of calculated WER values was similar. Statistically significant (α=0.05) univariate predictors of site-specific Cu toxicity included (in sequence of decreasing significance) dissolved organic carbon (DOC), hardness/alkalinity ratio, alkalinity, K, and total dissolved solids. A multiple-regression model developed from a combination of DOC and alkalinity explained 85% of the toxicity variability in site water samples, providing a strong predictive tool that can be used in the WER framework when site-specific criteria values are derived. The biotic ligand model (BLM) underpredicted toxicity in site waters by more than 2-fold. Adjustments to the default BLM parameters improved the model's performance but did not provide a better predictive tool compared with the regression model developed from DOC and alkalinity.

  6. Predicting mutually exclusive spliced exons based on exon length, splice site and reading frame conservation, and exon sequence homology

    Directory of Open Access Journals (Sweden)

    Hammesfahr Björn

    2011-06-01

    Full Text Available Abstract Background Alternative splicing of pre-mature RNA is an important process eukaryotes utilize to increase their repertoire of different protein products. Several types of different alternative splice forms exist including exon skipping, differential splicing of exons at their 3'- or 5'-end, intron retention, and mutually exclusive splicing. The latter term is used for clusters of internal exons that are spliced in a mutually exclusive manner. Results We have implemented an extension to the WebScipio software to search for mutually exclusive exons. Here, the search is based on the precondition that mutually exclusive exons encode regions of the same structural part of the protein product. This precondition provides restrictions to the search for candidate exons concerning their length, splice site conservation and reading frame preservation, and overall homology. Mutually exclusive exons that are not homologous and not of about the same length will not be found. Using the new algorithm, mutually exclusive exons in several example genes, a dynein heavy chain, a muscle myosin heavy chain, and Dscam were correctly identified. In addition, the algorithm was applied to the whole Drosophila melanogaster X chromosome and the results were compared to the Flybase annotation and an ab initio prediction. Clusters of mutually exclusive exons might be subsequent to each other and might encode dozens of exons. Conclusions This is the first implementation of an automatic search for mutually exclusive exons in eukaryotes. Exons are predicted and reconstructed in the same run providing the complete gene structure for the protein query of interest. WebScipio offers high quality gene structure figures with the clusters of mutually exclusive exons colour-coded, and several analysis tools for further manual inspection. The genome scale analysis of all genes of the Drosophila melanogaster X chromosome showed that WebScipio is able to find all but two of the 28

  7. OH-PRED: prediction of protein hydroxylation sites by incorporating adapted normal distribution bi-profile Bayes feature extraction and physicochemical properties of amino acids.

    Science.gov (United States)

    Jia, Cang-Zhi; He, Wen-Ying; Yao, Yu-Hua

    2017-03-01

    Hydroxylation of proline or lysine residues in proteins is a common post-translational modification event, and such modifications are found in many physiological and pathological processes. Nonetheless, the exact molecular mechanism of hydroxylation remains under investigation. Because experimental identification of hydroxylation is time-consuming and expensive, bioinformatics tools with high accuracy represent desirable alternatives for large-scale rapid identification of protein hydroxylation sites. In view of this, we developed a supporter vector machine-based tool, OH-PRED, for the prediction of protein hydroxylation sites using the adapted normal distribution bi-profile Bayes feature extraction in combination with the physicochemical property indexes of the amino acids. In a jackknife cross validation, OH-PRED yields an accuracy of 91.88% and a Matthew's correlation coefficient (MCC) of 0.838 for the prediction of hydroxyproline sites, and yields an accuracy of 97.42% and a MCC of 0.949 for the prediction of hydroxylysine sites. These results demonstrate that OH-PRED increased significantly the prediction accuracy of hydroxyproline and hydroxylysine sites by 7.37 and 14.09%, respectively, when compared with the latest predictor PredHydroxy. In independent tests, OH-PRED also outperforms previously published methods.

  8. On the development of a model predicting the recrystallization texture of aluminum using the Taylor model for rolling textures and the coincidence lattice site theory

    Science.gov (United States)

    T, Morimoto; F, Yoshida; A, Yanagida; J, Yanagimoto

    2015-04-01

    First, hardening model in f.c.c. metals was formulated with collinear interactions slips, Hirth slips and Lomer-Cottrell slips. Using the Taylor and the Sachs rolling texture prediction model, the residual dislocation densities of cold-rolled commercial pure aluminum were estimated. Then, coincidence site lattice grains were investigated from observed cold rolling texture. Finally, on the basis of oriented nucleation theory and coincidence site lattice theory, the recrystallization texture of commercial pure aluminum after low-temperature annealing was predicted.

  9. Development and Validation of a Preprocedural Risk Score to Predict Access Site Complications After Peripheral Vascular Interventions Based on the Vascular Quality Initiative Database

    Directory of Open Access Journals (Sweden)

    Daniel Ortiz

    2016-01-01

    Full Text Available Purpose: Access site complications following peripheral vascular intervention (PVI are associated with prolonged hospitalization and increased mortality. Prediction of access site complication risk may optimize PVI care; however, there is no tool designed for this. We aimed to create a clinical scoring tool to stratify patients according to their risk of developing access site complications after PVI. Methods: The Society for Vascular Surgery’s Vascular Quality Initiative database yielded 27,997 patients who had undergone PVI at 131 North American centers. Clinically and statistically significant preprocedural risk factors associated with in-hospital, post-PVI access site complications were included in a multivariate logistic regression model, with access site complications as the outcome variable. A predictive model was developed with a random sample of 19,683 (70% PVI procedures and validated in 8,314 (30%. Results: Access site complications occurred in 939 (3.4% patients. The risk tool predictors are female gender, age > 70 years, white race, bedridden ambulatory status, insulin-treated diabetes mellitus, prior minor amputation, procedural indication of claudication, and nonfemoral arterial access site (model c-statistic = 0.638. Of these predictors, insulin-treated diabetes mellitus and prior minor amputation were protective of access site complications. The discriminatory power of the risk model was confirmed by the validation dataset (c-statistic = 0.6139. Higher risk scores correlated with increased frequency of access site complications: 1.9% for low risk, 3.4% for moderate risk and 5.1% for high risk. Conclusions: The proposed clinical risk score based on eight preprocedural characteristics is a tool to stratify patients at risk for post-PVI access site complications. The risk score may assist physicians in identifying patients at risk for access site complications and selection of patients who may benefit from bleeding avoidance

  10. Proteoglycan-based diversification of disease outcome in head and neck cancer patients identifies NG2/CSPG4 and syndecan-2 as unique relapse and overall survival predicting factors.

    Science.gov (United States)

    Farnedi, Anna; Rossi, Silvia; Bertani, Nicoletta; Gulli, Mariolina; Silini, Enrico Maria; Mucignat, Maria Teresa; Poli, Tito; Sesenna, Enrico; Lanfranco, Davide; Montebugnoli, Lucio; Leonardi, Elisa; Marchetti, Claudio; Cocchi, Renato; Ambrosini-Spaltro, Andrea; Foschini, Maria Pia; Perris, Roberto

    2015-05-03

    Tumour relapse is recognized to be the prime fatal burden in patients affected by head and neck squamous cell carcinoma (HNSCC), but no discrete molecular trait has yet been identified to make reliable early predictions of tumour recurrence. Expression of cell surface proteoglycans (PGs) is frequently altered in carcinomas and several of them are gradually emerging as key prognostic factors. A PG expression analysis at both mRNA and protein level, was pursued on primary lesions derived from 173 HNSCC patients from whom full clinical history and 2 years post-surgical follow-up was accessible. Gene and protein expression data were correlated with clinical traits and previously proposed tumour relapse markers to stratify high-risk patient subgroups. HNSCC lesions were indeed found to exhibit a widely aberrant PG expression pattern characterized by a variable expression of all PGs and a characteristic de novo transcription/translation of GPC2, GPC5 and NG2/CSPG4 respectively in 36%, 72% and 71% on 119 cases. Importantly, expression of NG2/CSPG4, on neoplastic cells and in the intralesional stroma (Hazard Ratio [HR], 6.76, p = 0.017) was strongly associated with loco-regional relapse, whereas stromal enrichment of SDC2 (HR, 7.652, p = 0.007) was independently tied to lymphnodal infiltration and disease-related death. Conversely, down-regulated SDC1 transcript (HR, 0.232, p = 0.013) uniquely correlated with formation of distant metastases. Altered expression of PGs significantly correlated with the above disease outcomes when either considered alone or in association with well-established predictors of poor prognosis (i.e. T classification, previous occurrence of precancerous lesions and lymphnodal metastasis). Combined alteration of all three PGs was found to be a reliable predictor of shorter survival. An unprecedented PG-based prognostic portrait is unveiled that incisively diversifies disease course in HNSCC patients beyond the currently known clinical and molecular

  11. Incorporation of Model and Parameter Uncertainty in Predicting Radionuclide Fluxes from the Climax Granite Intrusive, Nevada Test Site

    Science.gov (United States)

    Reeves, D. M.; Pohlmann, K. F.; Pohll, G. M.; Chapman, J. B.; Ye, M.

    2006-12-01

    The Yucca Flat-Climax Mine Corrective Action Unit requires the use of numerical models to predict radionuclide flux rates from three subsurface nuclear tests conducted in a fractured rock mass. Modeling flow and transport in the Climax granite intrusive (CGI) is unique; while attributes of rock fractures have been extensively characterized in subsurface tunnel and drift complexes, information on the saturated flow system, including the position of the water table within the CGI, is largely unknown. A modified version of the Death Valley Regional Flow System (DVRFS) model of Belcher et al. (2004) with refined discretization in the area of the CGI is used to provide boundary conditions and a calibration target for a local-scale stochastic continuum fracture flow and transport model. Uncertainty in the Climax DVRFS model is addressed by including five different geologic framework models, each weighted according to expert elicitation. Five ground water recharge models are then applied to each of the five geologic models, resulting in a total of 25 geologic/recharge models. The CGI fracture flow model consists of 3-D discrete fracture networks, randomly distributed according to probability distribution functions for fracture location, orientation, length and permeability. The networks are directly mapped onto a 3-D finite-difference grid and MODFLOW is used to simultaneously solve for fluid flow within the fracture network and rock matrix. Flow model calibration involved matching the geometric mean of total fluid flux through 200 Monte Carlo fracture network realizations to flux computed in the subsection of the Climax DVRFS model representing the area of the local-scale model domain. By maintaining a constant log_10 mean and variance of fracture conductivity, fracture density was altered until the geometric mean of flux from all 200 network realizations is within +/- 5% of the target flux from the regional model. Variability in flux for individual realizations

  12. NASA's unique networking environment

    Science.gov (United States)

    Johnson, Marjory J.

    1988-01-01

    Networking is an infrastructure technology; it is a tool for NASA to support its space and aeronautics missions. Some of NASA's networking problems are shared by the commercial and/or military communities, and can be solved by working with these communities. However, some of NASA's networking problems are unique and will not be addressed by these other communities. Individual characteristics of NASA's space-mission networking enviroment are examined, the combination of all these characteristics that distinguish NASA's networking systems from either commercial or military systems is explained, and some research areas that are important for NASA to pursue are outlined.

  13. Development of a Regression Kriging Model Conditioned with Sequential Gaussian Simulation to Predict the Spatial Distribution of Site Index for The Savannah River Site.

    Energy Technology Data Exchange (ETDEWEB)

    Edwards, Lloyd [USDA Forest Service, Southern Research Station; Parresol, Bernie [USDA Forest Service, Southern Research Station

    2012-09-17

    The primary research objective of the project is to determine an optimum model to spatially interpolate point derived tree site index (SI). This optimum model will use relevant data from 635 measured sample points to create continuous 40 meter SI raster layer of entire study extent.

  14. A UNIQUE FACTORIZATION DOMAIN

    African Journals Online (AJOL)

    Physics and financed by the Swedish Agency for Research Cooperation with Developing. Countries. .... In this paper, bounds for the efficiency of OLS relative to GLS estimator of 6 in ...... temperatures of the lakes using cloud free images at the National Meteorological ..... sites being investigated for geothermal energy.

  15. Predikin and PredikinDB: a computational framework for the prediction of protein kinase peptide specificity and an associated database of phosphorylation sites

    Directory of Open Access Journals (Sweden)

    Kemp Bruce E

    2008-05-01

    Full Text Available Abstract Background We have previously described an approach to predicting the substrate specificity of serine-threonine protein kinases. The method, named Predikin, identifies key conserved substrate-determining residues in the kinase catalytic domain that contact the substrate in the region of the phosphorylation site and so determine the sequence surrounding the phosphorylation site. Predikin was implemented originally as a web application written in Javascript. Results Here, we describe a new version of Predikin, completely revised and rewritten as a modular framework that provides multiple enhancements compared with the original. Predikin now consists of two components: (i PredikinDB, a database of phosphorylation sites that links substrates to kinase sequences and (ii a Perl module, which provides methods to classify protein kinases, reliably identify substrate-determining residues, generate scoring matrices and score putative phosphorylation sites in query sequences. The performance of Predikin as measured using receiver operator characteristic (ROC graph analysis equals or surpasses that of existing comparable methods. The Predikin website has been redesigned to incorporate the new features. Conclusion New features in Predikin include the use of SQL queries to PredikinDB to generate predictions, scoring of predictions, more reliable identification of substrate-determining residues and putative phosphorylation sites, extended options to handle protein kinase and substrate data and an improved web interface. The new features significantly enhance the ability of Predikin to analyse protein kinases and their substrates. Predikin is available at http://predikin.biosci.uq.edu.au.

  16. Prediction of Pseudo relative velocity response spectra at Yucca Mountain for underground nuclear explosions conducted in the Pahute Mesa testing area at the Nevada testing site; Yucca Mountain Site Characterization Project

    Energy Technology Data Exchange (ETDEWEB)

    Phillips, J.S.

    1991-12-01

    The Yucca Mountain Site Characterization Project (YMP), managed by the Office of Geologic Disposal of the Office of Civilian Radioactive Waste Management of the US Department of Energy, is examining the feasibility of siting a repository for commercial, high-level nuclear wastes at Yucca Mountain on and adjacent to the Nevada Test Site (NTS). This work, intended to extend our understanding of the ground motion at Yucca Mountain resulting from testing of nuclear weapons on the NTS, was funded by the Yucca Mountain project and the Military Applications Weapons Test Program. This report summarizes one aspect of the weapons test seismic investigations conducted in FY88. Pseudo relative velocity response spectra (PSRV) have been calculated for a large body of surface ground motions generated by underground nuclear explosions. These spectra have been analyzed and fit using multiple linear regression techniques to develop a credible prediction technique for surface PSRVs. In addition, a technique for estimating downhole PSRVs at specific stations is included. A data summary, data analysis, prediction development, prediction evaluation, software summary and FORTRAN listing of the prediction technique are included in this report.

  17. Role of culture of postoperative drainage fluid in the prediction of infection of the surgical site after major oncological operations of the head and neck.

    Science.gov (United States)

    Candau-Alvarez, A; Linares-Sicilia, M J; Dean-Ferrer, A; Pérez-Navero, J L

    2015-02-01

    Infection of the surgical site after major oncological operations of the head and neck increases mortality and morbidity. The aim of this prospective pilot study was to assess the efficacy of culturing the exudate from the drain after cervical neck dissection to see if it predicted such infection. We studied 40/112 patients with squamous cell cancer of the head and neck who were treated during the last two years and met our inclusion criteria. Six patients developed infections (15%). Reconstruction with pedicled rather than local or microvascular flaps, duration of operation of over 7 hours, the presence of a tracheostomy, and bilateral neck dissection were considered risk factors (p=0.01). Culture of drainage fluid on postoperative day 3 that grew no pathogens predicted that the site would not become infected, with a negative predictive value of 96%. Copyright © 2014 The British Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.

  18. Prediction

    CERN Document Server

    Sornette, Didier

    2010-01-01

    This chapter first presents a rather personal view of some different aspects of predictability, going in crescendo from simple linear systems to high-dimensional nonlinear systems with stochastic forcing, which exhibit emergent properties such as phase transitions and regime shifts. Then, a detailed correspondence between the phenomenology of earthquakes, financial crashes and epileptic seizures is offered. The presented statistical evidence provides the substance of a general phase diagram for understanding the many facets of the spatio-temporal organization of these systems. A key insight is to organize the evidence and mechanisms in terms of two summarizing measures: (i) amplitude of disorder or heterogeneity in the system and (ii) level of coupling or interaction strength among the system's components. On the basis of the recently identified remarkable correspondence between earthquakes and seizures, we present detailed information on a class of stochastic point processes that has been found to be particu...

  19. Report on the use of stability parameters and mesoscale modelling in short-term prediction[Wind speed at wind farm sites

    Energy Technology Data Exchange (ETDEWEB)

    Badger, J.; Giebel, G.; Guo Larsen, X.; Skov Nielsen, T.; Aalborg Nielsen, H.; Madsen, Henrik; Toefting, J.

    2007-06-15

    In this report investigations using atmospheric stability measures to improve wind speed predictions at wind farm sites are described. Various stability measures have been calculated based on numerical weather prediction model output. Their ability to improve the wind speed predictions is assessed at three locations. One of the locations is in complex terrain. Mesoscale modelling has been carried out using KAMM at this location. The characteristics of the measured winds are captured well by the mesoscale modelling. It can be seen that the atmospheric stability plays an important role in determining how the flow is influence by the terrain. A prediction system employing a look-up table approach based on wind class simulations is presented. The mesoscale modelling results produced by KAMM were validated using an alternative mesoscale model called WRF. A good agreement in the results of KAMM and WRF was found. It is shown that including a stability parameter in physical and/or statistical modelling can improve the wind speed predictions at a wind farm site. A concept for the inclusion of a stability measure in the WPPT prediction system is presented, and the testing of the concept is outlined. (au)

  20. Evaluation of pier-scour measurement methods and pier-scour predictions with observed scour measurements at selected bridge sites in New Hampshire, 1995-98

    Science.gov (United States)

    Boehmler, Erick M.; Olimpio, Joseph R.

    2000-01-01

    In a previous study, 44 of 48 bridge sites examined in New Hampshire were categorized as scour critical. In this study, the U.S. Geological Survey (USGS) evaluated pier-scour measurement methods and predictions at many of these sites. This evaluation included measurement of pier-scour depths at 20 bridge sites using Ground- Penetrating Radar (GPR) surveys. Pier scour was also measured during floods by teams at 5 of these 20 sites. At 4 of the 20 sites, fixed instruments were installed to monitor scour. At only one bridge site investigated by a team was any pier scour measurable during a flood event. A scour depth of 0.7 foot (0.21 m) was measured at a pier in the channel at the State Route 18 bridge over the Connecticut River in Littleton. Measurements made using GPR and (or) fixed instruments indicated pier scour for six sites. The GPR surveys indicated scour along the side of a pier and further upstream from the nose of a pier that was not detected by flood-team measurements at two sites. Most pier-scour equations selected for this examination were reviewed and published in previous scour investigations. Graphical comparison of residual pier-scour depths indicate that the Shen equation yielded pier-scour depth predictions closest to those measured, without underestimating. Measured depths of scour, however, were zero feet for 14 of the 20 sites. For the Blench-Inglis II equation and the Simplified Chinese equation, most differences between measured and predicted scour depths were within 5 feet. These two equations underpredicted scour for one of six sites with measurable scour. The underprediction, however, was within the resolution of the depth measurements. The Simplified Chinese equation is less sensitive than other equations to velocity and depth input variables, and is one of the few empirical equations to integrate the influence of flow competence, or a measure of the maximum streambed particle size that a stream is capable of transporting, in the

  1. Site specific prediction equations for peak acceleration of ground motion due to earthquakes induced by underground mining in Legnica-Głogów Copper District in Poland

    Science.gov (United States)

    Lasocki, Stanisław

    2013-10-01

    Ground motion database from the region of Żelazny Most tailings pond, the largest in Europe ore-flotation waste repository, is used to identify ground motion prediction equations (GMPE-s) for peak horizontal and peak vertical acceleration. A GMPE model including both geometrical spreading and anelastic damping terms cannot be correctly identified and the model with only spreading term is accepted. The analysis of variance of this model's residuals with station location as grouping variable indicates that station locations contribute significantly to the observed ground motion variability. Therefore, a site specific GMPE model with relative site amplifications is assessed. Despite short distances among stations, the amplification considerably vary from point to point, up to 1.8 times for the horizontal and 3.5 times for the vertical peak amplitude. The model including site effects enhances GMPE-s fit to observations, explains more than 60% dependent variables variability and correctly accounts for site effects.

  2. Scores of amino acid 0D-3D information as applied in cleavage site prediction and better specificity elucidation for human immunodeficiency virus type 1 protease

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    A new set of descriptors,namely score vectors of the zero dimension,one dimension,two dimensions and three dimensions(SZOTT),was derived from principle component analysis of a matrix of 1369 structural variables including 0D,1D,2D and 3D information for the 20 coded amino acids. SZOTT scales were then used in cleavage site prediction of human immunodeficiency virus type 1 protease. Linear discriminant analysis(LDA) and support vector machines(SVM) were applied to developing models to predict the cleavage sites. The results obtained by linear discriminant analysis(LDA) and support vector machines(SVM) are as follows. The Matthews correlation coefficients(MCC) by the resubstitution test,leave-one-out cross validation(LOOCV) and external validation are 0.879 and 0.911,0.849 and 0.901,0.822 and 0.846,respectively. The receiver operating characteristic(ROC) analysis showed that the SVM model possesses better simulative and predictive ability in comparison with the LDA model. Satisfactory results show that SZOTT descriptors can be further used to predict cleavage sites of human immunodeficiency virus type 1 protease.

  3. Scores of amino acid 0D-3D information as applied in cleavage site prediction and better specificity elucidation for human immunodeficiency virus type 1 protease

    Institute of Scientific and Technical Information of China (English)

    KANG LiFang; LIANG GuiZhao; SHU Mao; YANG ShanBin; LI ZhiLiang

    2008-01-01

    A new set of descriptors, namely score vectors of the zero dimension, one dimension, two dimensions and three dimensions (SZOTT), was derived from principle component analysis of a matrix of 1369 structural variables including 0D, 1D, 2D and 3D information for the 20 coded amino acids. SZOTT scales were then used in cleavage site prediction of human immunodeficiency virus type 1 protease. Linear discriminant analysis (LDA) and support vector machines (SVM) were applied to developing models to predict the cleavage sites. The results obtained by linear discriminant analysis (LDA) and support vector machines (SVM) are as follows. The Matthews correlation coefficients (MCC) by the resubstitution test, leave-one-out cross validation (LOOCV) and external validation are 0.879 and 0.911, 0.649 and 0.901, 0.822 and 0.846, respectively. The receiver operating characteristic (ROC) analysis showed that the SVM model possesses better simulative and predictive ability in comparison with the LDA model. Satisfactory results show that SZOTT descriptors can be further used to predict cleavage sites of human immunodeficiency virus type 1 protease.

  4. Structure of the unique SEFIR domain from human interleukin 17 receptor A reveals a composite ligand-binding site containing a conserved α-helix for Act1 binding and IL-17 signaling

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Bing [Oklahoma State University, Stillwater, OK 74078 (United States); Liu, Caini; Qian, Wen [Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH 44195 (United States); Han, Yue [Oklahoma State University, Stillwater, OK 74078 (United States); Li, Xiaoxia, E-mail: lix@ccf.org [Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH 44195 (United States); Deng, Junpeng, E-mail: lix@ccf.org [Oklahoma State University, Stillwater, OK 74078 (United States)

    2014-05-01

    Crystal structure of the SEFIR domain from human IL-17 receptor A provides new insights into IL-17 signaling. Interleukin 17 (IL-17) cytokines play a crucial role in mediating inflammatory and autoimmune diseases. A unique intracellular signaling domain termed SEFIR is found within all IL-17 receptors (IL-17Rs) as well as the key adaptor protein Act1. SEFIR-mediated protein–protein interaction is a crucial step in IL-17 cytokine signaling. Here, the 2.3 Å resolution crystal structure of the SEFIR domain of IL-17RA, the most commonly shared receptor for IL-17 cytokine signaling, is reported. The structure includes the complete SEFIR domain and an additional α-helical C-terminal extension, which pack tightly together to form a compact unit. Structural comparison between the SEFIR domains of IL-17RA and IL-17RB reveals substantial differences in protein topology and folding. The uniquely long insertion between strand βC and helix αC in IL-17RA SEFIR is mostly well ordered, displaying a helix (αCC′{sub ins}) and a flexible loop (CC′). The DD′ loop in the IL-17RA SEFIR structure is much shorter; it rotates nearly 90° with respect to the counterpart in the IL-17RB SEFIR structure and shifts about 12 Å to accommodate the αCC′{sub ins} helix without forming any knots. Helix αC was identified as critical for its interaction with Act1 and IL-17-stimulated gene expression. The data suggest that the heterotypic SEFIR–SEFIR association via helix αC is a conserved and signature mechanism specific for IL-17 signaling. The structure also suggests that the downstream motif of IL-17RA SEFIR together with helix αC could provide a composite ligand-binding surface for recruiting Act1 during IL-17 signaling.

  5. Apply Woods Model in the Predictions of Ambient Air Particles and Metallic Elements (Mn, Fe, Zn, Cr, and Cu at Industrial, Suburban/Coastal, and Residential Sampling Sites

    Directory of Open Access Journals (Sweden)

    Guor-Cheng Fang

    2012-01-01

    Full Text Available The main purpose for this study was to monitor ambient air particles and metallic elements (Mn, Fe, Zn, Cr, and Cu in total suspended particulates (TSPs concentration, dry deposition at three characteristic sampling sites of central Taiwan. Additionally, the calculated/measured dry deposition flux ratios of ambient air particles and metallic elements were calculated with Woods models at these three characteristic sampling sites during years of 2009-2010. As for ambient air particles, the results indicated that the Woods model generated the most accurate dry deposition prediction results when particle size was 18 μm in this study. The results also indicated that the Woods model exhibited better dry deposition prediction performance when the particle size was greater than 10 μm for the ambient air metallic elements in this study. Finally, as for Quan-xing sampling site, the main sources were many industrial factories under process around these regions and were severely polluted areas. In addition, the highest average dry deposition for Mn, Fe, Zn, and Cu species occurred at Bei-shi sampling site, and the main sources were the nearby science park, fossil fuel combustion, and Taichung thermal power plant (TTPP. Additionally, as for He-mei sampling site, the main sources were subjected to traffic mobile emissions.

  6. Random forest algorithm yields accurate quantitative prediction models of benthic light at intertidal sites affected by toxic Lyngbya majuscula blooms

    NARCIS (Netherlands)

    Kehoe, M.J.; O’ Brien, K.; Grinham, A.; Rissik, D.; Ahern, K.S.; Maxwell, P.

    2012-01-01

    It is shown that targeted high frequency monitoring and modern machine learning methods lead to highly predictive models of benthic light flux. A state-of-the-art machine learning technique was used in conjunction with a high frequency data set to calibrate and test predictive benthic lights models

  7. Random forest algorithm yields accurate quantitative prediction models of benthic light at intertidal sites affected by toxic Lyngbya majuscula blooms

    NARCIS (Netherlands)

    Kehoe, M.J.; O’ Brien, K.; Grinham, A.; Rissik, D.; Ahern, K.S.; Maxwell, P.

    2012-01-01

    It is shown that targeted high frequency monitoring and modern machine learning methods lead to highly predictive models of benthic light flux. A state-of-the-art machine learning technique was used in conjunction with a high frequency data set to calibrate and test predictive benthic lights models

  8. Ab Initio Prediction of Adsorption Isotherms for Gas Mixtures by Grand Canonical Monte Carlo Simulations on a Lattice of Sites.

    Science.gov (United States)

    Kundu, Arpan; Sillar, Kaido; Sauer, Joachim

    2017-06-15

    Gibbs free energies of adsorption on individual sites and the lateral (adsorbate-adsorbate) interaction energies are obtained from quantum chemical ab initio methods and molecular statistics. They define a Grand Canonical Monte Carlo (GCMC) Hamiltonian for simulations of gas mixtures on a lattice of adsorption sites. Coadsorption of CO2 and CH4 at Mg(2+) sites in the pores of the metal-organic framework CPO-27-Mg (Mg-MOF-74) is studied as an example. Simulations with different approximations as made in widely used coadsorption models such as the ideal adsorbed solution theory (IAST) show their limitations in describing adsorption selectivities for binary mixtures.

  9. Predicting ambient aerosol thermal-optical reflectance (TOR measurements from infrared spectra: extending the predictions to different years and different sites

    Directory of Open Access Journals (Sweden)

    M. Reggente

    2015-11-01

    We also propose a method to anticipate the prediction error: we calculate the squared Mahalanobis distance in the feature space (scores determined by PLSR between new spectra and spectra in the calibration set. The squared Mahalanobis distance provides a crude method for assessing the magnitude of mean error when applying a calibration model to a new set of samples.

  10. Predicting Bird and Bat Fatality Risk at Wind Farms and Proposed Wind Farm Sites Using Acoustic-Ultrasonic Recorders

    Data.gov (United States)

    US Fish and Wildlife Service, Department of the Interior — This project has three objectives: (1) evaluate the ability of dual acoustic-ultrasonic recorders to capture nocturnal calls of birds and bats at wind power sites;...

  11. Prediction of outcome of tubal ectopic pregnancy on the basis of site of implantation of embryo in the fallopian tube

    Directory of Open Access Journals (Sweden)

    Rajshree D. Katke

    2015-10-01

    Conclusions: Early detection of tubal ectopic and its site of implantation can help in deciding further management especially to go for conservative or surgical management. [Int J Reprod Contracept Obstet Gynecol 2015; 4(5.000: 1431-1435

  12. Ventrogluteal versus dorsogluteal site selection: A cross-sectional study of muscle and subcutaneous fat thicknesses and an algorithm incorporating demographic and anthropometric data to predict injection outcome.

    Science.gov (United States)

    Larkin, Theresa A; Ashcroft, Elfriede; Elgellaie, Asmahan; Hickey, Blake A

    2017-06-01

    The dorsogluteal and ventrogluteal intramuscular injection sites both have their use in clinical practice; however, it has not been established in whom one or the other should be preferentially targeted or avoided. There is a need for an evidence-based approach towards site selection for a successful intramuscular injection outcome and to avoid unwanted injection outcomes of inadvertent subcutaneous injection or bone contact. Injection outcome is dependent on injection site subcutaneous fat thickness and muscle thickness; these are likely influenced by gender and anthropometry. To determine whether subcutaneous fat, muscle, and total tissue thicknesses differ between the dorsogluteal and ventrogluteal sites, and whether theoretical injection outcome (intramuscular, subcutaneous, or bone contact) can be predicted by demographic and anthropometric data and described by an algorithm. Cross-sectional study design. University in Australia. 145 volunteers (57% female) of at least 18 years of age recruited through the university community. Anthropometric data was collected and subcutaneous fat and muscle thicknesses were quantified by ultrasonography. Anthropometric differences between theoretical injection outcome groups (bone contact versus intramuscular versus subcutaneous at the ventrogluteal and dorsogluteal sites) was determined for each gender (ANOVA). Multiple regression analysis was conducted to determine the influence of demographic and anthropometric data on theoretical intramuscular injection outcome. An algorithm to guide site selection was developed for each gender, based on the anthropometric measures that best discriminated between injection outcomes. Subcutaneous fat, muscle and total tissue were significantly thicker at the dorsogluteal site than the ventrogluteal site, and subcutaneous fat was significantly thicker in females than males at both sites (all psubcutaneous fat thickness at both sites; male gender was a significant predictor of dorsogluteal

  13. CYP1B1: a unique gene with unique characteristics.

    Science.gov (United States)

    Faiq, Muneeb A; Dada, Rima; Sharma, Reetika; Saluja, Daman; Dada, Tanuj

    2014-01-01

    CYP1B1, a recently described dioxin inducible oxidoreductase, is a member of the cytochrome P450 superfamily involved in the metabolism of estradiol, retinol, benzo[a]pyrene, tamoxifen, melatonin, sterols etc. It plays important roles in numerous physiological processes and is expressed at mRNA level in many tissues and anatomical compartments. CYP1B1 has been implicated in scores of disorders. Analyses of the recent studies suggest that CYP1B1 can serve as a universal/ideal cancer marker and a candidate gene for predictive diagnosis. There is plethora of literature available about certain aspects of CYP1B1 that have not been interpreted, discussed and philosophized upon. The present analysis examines CYP1B1 as a peculiar gene with certain distinctive characteristics like the uniqueness in its chromosomal location, gene structure and organization, involvement in developmentally important disorders, tissue specific, not only expression, but splicing, potential as a universal cancer marker due to its involvement in key aspects of cellular metabolism, use in diagnosis and predictive diagnosis of various diseases and the importance and function of CYP1B1 mRNA in addition to the regular translation. Also CYP1B1 is very difficult to express in heterologous expression systems, thereby, halting its functional studies. Here we review and analyze these exceptional and startling characteristics of CYP1B1 with inputs from our own experiences in order to get a better insight into its molecular biology in health and disease. This may help to further understand the etiopathomechanistic aspects of CYP1B1 mediated diseases paving way for better research strategies and improved clinical management.

  14. An integrative computational framework based on a two-step random forest algorithm improves prediction of zinc-binding sites in proteins.

    Directory of Open Access Journals (Sweden)

    Cheng Zheng

    Full Text Available Zinc-binding proteins are the most abundant metalloproteins in the Protein Data Bank where the zinc ions usually have catalytic, regulatory or structural roles critical for the function of the protein. Accurate prediction of zinc-binding sites is not only useful for the inference of protein function but also important for the prediction of 3D structure. Here, we present a new integrative framework that combines multiple sequence and structural properties and graph-theoretic network features, followed by an efficient feature selection to improve prediction of zinc-binding sites. We investigate what information can be retrieved from the sequence, structure and network levels that is relevant to zinc-binding site prediction. We perform a two-step feature selection using random forest to remove redundant features and quantify the relative importance of the retrieved features. Benchmarking on a high-quality structural dataset containing 1,103 protein chains and 484 zinc-binding residues, our method achieved >80% recall at a precision of 75% for the zinc-binding residues Cys, His, Glu and Asp on 5-fold cross-validation tests, which is a 10%-28% higher recall at the 75% equal precision compared to SitePredict and zincfinder at residue level using the same dataset. The independent test also indicates that our method has achieved recall of 0.790 and 0.759 at residue and protein levels, respectively, which is a performance better than the other two methods. Moreover, AUC (the Area Under the Curve and AURPC (the Area Under the Recall-Precision Curve by our method are also respectively better than those of the other two methods. Our method can not only be applied to large-scale identification of zinc-binding sites when structural information of the target is available, but also give valuable insights into important features arising from different levels that collectively characterize the zinc-binding sites. The scripts and datasets are available at http://protein.cau.edu.cn/zincidentifier/.

  15. Prediction of Post-Closure Water Balance for Monolithic Soil Covers at Waste Disposal Sites in the Greater Accra Metropolitan Area of Ghana

    OpenAIRE

    Kodwo Beedu Keelson

    2014-01-01

    The Ghana Landfill Guidelines require the provision of a final cover system during landfill closure as a means of minimizing the harmful environmental effects of uncontrolled leachate discharges. However, this technical manual does not provide explicit guidance on the material types or configurations that would be suitable for the different climatic zones in Ghana. The aim of this study was to simulate and predict post-closure landfill cover water balance for waste disposal sites located i...

  16. Incorporating root hydraulic redistribution in CLM4.5: Effects on predicted site and global evapotranspiration, soil moisture, and water storage

    Science.gov (United States)

    Tang, Jinyun; Riley, William J.; Niu, Jie

    2015-12-01

    We implemented the Amenu-Kumar model in the Community Land Model (CLM4.5) to simulate plant Root Hydraulic Redistribution (RHR) and analyzed its influence on CLM hydrology from site to global scales. We evaluated two numerical implementations: the first solved the coupled equations of root and soil water transport concurrently, while the second solved the two equations sequentially. Through sensitivity analysis, we demonstrate that the sequentially coupled implementation (SCI) is numerically incorrect, whereas the tightly coupled implementation (TCI) is numerically robust with numerical time steps varying from 1 to 30 min. At the site-level, we found the SCI approach resulted in better agreement with measured evapotranspiration (ET) at the AmeriFlux Blodgett Forest site, California, whereas the two approaches resulted in equally poor agreement between predicted and measured ET at the LBA Tapajos KM67 Mature Forest site in Amazon, Brazil. Globally, the SCI approach overestimated annual land ET by as much as 3.5 mm d-1 in some grid cells when compared to the TCI estimates. These comparisons demonstrate that TCI is a more robust numerical implementation of RHR. However, we found, even with TCI, that incorporating RHR resulted in worse agreement with measured soil moisture at both the Blodgett Forest and Tapajos sites and degraded the agreement between simulated terrestrial water storage anomaly and Gravity Recovery and Climate Experiment (GRACE) observations. We find including RHR in CLM4.5 improved ET predictions compared with the FLUXNET-MTE estimates north of 20° N but led to poorer predictions in the tropics. The biases in ET were robust and significant regardless of the four different pedotransfer functions or of the two meteorological forcing data sets we applied. We also found that the simulated water table was unrealistically sensitive to RHR. Therefore, we contend that further structural and data improvements are warranted to improve the hydrological

  17. Imbalanced multi-modal multi-label learning for subcellular localization prediction of human proteins with both single and multiple sites.

    Directory of Open Access Journals (Sweden)

    Jianjun He

    Full Text Available It is well known that an important step toward understanding the functions of a protein is to determine its subcellular location. Although numerous prediction algorithms have been developed, most of them typically focused on the proteins with only one location. In recent years, researchers have begun to pay attention to the subcellular localization prediction of the proteins with multiple sites. However, almost all the existing approaches have failed to take into account the correlations among the locations caused by the proteins with multiple sites, which may be the important information for improving the prediction accuracy of the proteins with multiple sites. In this paper, a new algorithm which can effectively exploit the correlations among the locations is proposed by using gaussian process model. Besides, the algorithm also can realize optimal linear combination of various feature extraction technologies and could be robust to the imbalanced data set. Experimental results on a human protein data set show that the proposed algorithm is valid and can achieve better performance than the existing approaches.

  18. Multi-Site Validation of the SWAT Model on the Bani Catchment: Model Performance and Predictive Uncertainty

    Directory of Open Access Journals (Sweden)

    Jamilatou Chaibou Begou

    2016-04-01

    Full Text Available The objective of this study was to assess the performance and predictive uncertainty of the Soil and Water Assessment Tool (SWAT model on the Bani River Basin, at catchment and subcatchment levels. The SWAT model was calibrated using the Generalized Likelihood Uncertainty Estimation (GLUE approach. Potential Evapotranspiration (PET and biomass were considered in the verification of model outputs accuracy. Global Sensitivity Analysis (GSA was used for identifying important model parameters. Results indicated a good performance of the global model at daily as well as monthly time steps with adequate predictive uncertainty. PET was found to be overestimated but biomass was better predicted in agricultural land and forest. Surface runoff represents the dominant process on streamflow generation in that region. Individual calibration at subcatchment scale yielded better performance than when the global parameter sets were applied. These results are very useful and provide a support to further studies on regionalization to make prediction in ungauged basins.

  19. Uniqueness is Important in Competition

    Institute of Scientific and Technical Information of China (English)

    FENG Ai-Xia; XV Xiu-Lian; HE Da-Ren

    2009-01-01

    We propose a quantitative network description on the function of uniqueness in a competition system. Two statistical parameters, competition ability and uniqueness are defined, and their relationship in ordinary cases is analytically discussed. The competition between Chinese regional universities is taken as an example. The empirical investigation results show that the uniqueness of a university is really important in competition. Also,uniqueness is very helpful in the promotion of the university overall quality.

  20. On Uniqueness of coalitional equilibria

    NARCIS (Netherlands)

    Finus, M.; Mouche, van P.H.M.; Rundshagen, B.

    2014-01-01

    For the so-called "new approach" of coalitio formation it is important that coalitional equilibria are unique. Uniqueness comes down to existene and to semi-uniqueness, i.e.\\\\that there exists at most one equilibrium. Although conditions for existence are not problematic, conditions for semi-uniquen

  1. Macrophage inflammatory protein-1α shows predictive value as a risk marker for subjects and sites vulnerable to bone loss in a longitudinal model of aggressive periodontitis.

    Directory of Open Access Journals (Sweden)

    Daniel H Fine

    Full Text Available Improved diagnostics remains a fundamental goal of biomedical research. This study was designed to assess cytokine biomarkers that could predict bone loss (BL in localized aggressive periodontitis. 2,058 adolescents were screened. Two groups of 50 periodontally healthy adolescents were enrolled in the longitudinal study. One group had Aggregatibacter actinomycetemcomitans (Aa, the putative pathogen, while the matched cohort did not. Cytokine levels were assessed in saliva and gingival crevicular fluid (GCF. Participants were sampled, examined, and radiographed every 6 months for 2-3 years. Disease was defined as radiographic evidence of BL. Saliva and GCF was collected at each visit, frozen, and then tested retrospectively after detection of BL. Sixteen subjects with Aa developed BL. Saliva from Aa-positive and Aa-negative healthy subjects was compared to subjects who developed BL. GCF was collected from 16 subjects with BL and from another 38 subjects who remained healthy. GCF from BL sites in the 16 subjects was compared to healthy sites in these same subjects and to healthy sites in subjects who remained healthy. Results showed that cytokines in saliva associated with acute inflammation were elevated in subjects who developed BL (i.e., MIP-1α MIP-1β IL-α, IL-1β and IL-8; p<0.01. MIP-1α was elevated 13-fold, 6 months prior to BL. When MIP-1α levels were set at 40 pg/ml, 98% of healthy sites were below that level (Specificity; whereas, 93% of sites with BL were higher (Sensitivity, with comparable Predictive Values of 98%; p<0.0001; 95% C.I. = 42.5-52.7. MIP-1α consistently showed elevated levels as a biomarker for BL in both saliva and GCF, 6 months prior to BL. MIP-1α continues to demonstrate its strong candidacy as a diagnostic biomarker for both subject and site vulnerability to BL.

  2. DR-predictor: incorporating flexible docking with specialized electronic reactivity and machine learning techniques to predict CYP-mediated sites of metabolism.

    Science.gov (United States)

    Huang, Tao-wei; Zaretzki, Jed; Bergeron, Charles; Bennett, Kristin P; Breneman, Curt M

    2013-12-23

    Computational methods that can identify CYP-mediated sites of metabolism (SOMs) of drug-like compounds have become required tools for early stage lead optimization. In recent years, methods that combine CYP binding site features with CYP/ligand binding information have been sought in order to increase the prediction accuracy of such hybrid models over those that use only one representation. Two challenges that any hybrid ligand/structure-based method must overcome are (1) identification of the best binding pose for a specific ligand with a given CYP and (2) appropriately incorporating the results of docking with ligand reactivity. To address these challenges we have created Docking-Regioselectivity-Predictor (DR-Predictor)--a method that incorporates flexible docking-derived information with specialized electronic reactivity and multiple-instance-learning methods to predict CYP-mediated SOMs. In this study, the hybrid ligand-structure-based DR-Predictor method was tested on substrate sets for CYP 1A2 and CYP 2A6. For these data, the DR-Predictor model was found to identify the experimentally observed SOM within the top two predicted rank-positions for 86% of the 261 1A2 substrates and 83% of the 100 2A6 substrates. Given the accuracy and extendibility of the DR-Predictor method, we anticipate that it will further facilitate the prediction of CYP metabolism liabilities and aid in in-silico ADMET assessment of novel structures.

  3. Monte carlo simulation of base and nucleotide excision repair of clustered DNA damage sites. II. Comparisons of model predictions to measured data.

    Science.gov (United States)

    Semenenko, V A; Stewart, R D

    2005-08-01

    Clustered damage sites other than double-strand breaks (DSBs) have the potential to contribute to deleterious effects of ionizing radiation, such as cell killing and mutagenesis. In the companion article (Semenenko et al., Radiat. Res. 164, 180-193, 2005), a general Monte Carlo framework to simulate key steps in the base and nucleotide excision repair of DNA damage other than DSBs is proposed. In this article, model predictions are compared to measured data for selected low-and high-LET radiations. The Monte Carlo model reproduces experimental observations for the formation of enzymatic DSBs in Escherichia coli and cells of two Chinese hamster cell lines (V79 and xrs5). Comparisons of model predictions with experimental values for low-LET radiation suggest that an inhibition of DNA backbone incision at the sites of base damage by opposing strand breaks is active over longer distances between the damaged base and the strand break in hamster cells (8 bp) compared to E. coli (3 bp). Model estimates for the induction of point mutations in the human hypoxanthine guanine phosphoribosyl transferase (HPRT) gene by ionizing radiation are of the same order of magnitude as the measured mutation frequencies. Trends in the mutation frequency for low- and high-LET radiation are predicted correctly by the model. The agreement between selected experimental data sets and simulation results provides some confidence in postulated mechanisms for excision repair of DNA damage other than DSBs and suggests that the proposed Monte Carlo scheme is useful for predicting repair outcomes.

  4. Acetylcholine-Provoked Coronary Spasm at Site of Significant Organic Stenosis Predicts Poor Prognosis in Patients With Coronary Vasospastic Angina.

    Science.gov (United States)

    Ishii, Masanobu; Kaikita, Koichi; Sato, Koji; Tanaka, Tomoko; Sugamura, Koichi; Sakamoto, Kenji; Izumiya, Yasuhiro; Yamamoto, Eiichiro; Tsujita, Kenichi; Yamamuro, Megumi; Kojima, Sunao; Soejima, Hirofumi; Hokimoto, Seiji; Matsui, Kunihiko; Ogawa, Hisao

    2015-09-08

    Coronary artery spasm contributes to the pathogenesis of variant angina and ischemic heart disease and may play a role in the progression of atherosclerosis. It is unclear whether the location of spasm is related to outcome. This study compared the clinical features and prognosis of patients with coronary spasm at the site of significant atherosclerotic stenosis with patients with spasm at sites without stenosis or nonsignificant stenosis. This was a retrospective, observational study of 1,877 consecutive patients with typical or atypical angina-like chest pain undergoing acetylcholine (ACh)-provocation testing. A total of 1,760 patients were eligible for analysis. ACh-provoked coronary spasm and significant organic stenosis were observed in 873 and 358 patients, respectively. In patients with significant atherosclerotic stenosis, ACh-positive patients (n = 233) were younger and without diabetes mellitus compared with nonspasm patients (n = 125). In patients without organic stenosis, ACh-positive patients (n = 640) were older, had dyslipidemia, and were more likely to have a family history of ischemic heart disease than nonspasm patients (n = 762). Multiple logistic regression analysis identified ST-segment elevation during anginal attacks, organic stenosis of the left anterior descending artery, and multivessel spasm as correlates of spasm at sites of significant organic stenosis (n = 192). Multivariate analysis identified ACh-provoked spasm at the site of significant stenosis and use of nitrates as the 2 prognostic factors for major adverse cardiac events. The clinical features and prognosis of patients with ACh-provoked coronary spasm were different when it occurred at the site of significant atherosclerotic stenosis compared with patients with spasm elsewhere. Both spasm at the site of significant organic stenosis and nitrate use were significant predictors of major adverse cardiac events. Copyright © 2015 American College of Cardiology Foundation. Published

  5. A unique restriction site in the flaA gene allows rapid differentiation of group I and group II Clostridium botulinum strains by PCR-restriction fragment length polymorphism analysis.

    Science.gov (United States)

    Paul, Catherine J; Tran, Shulin; Tam, Kevin J; Austin, John W

    2007-09-01

    Clostridium botulinum produces the potent botulinum neurotoxin, the causative agent of botulism. Based on distinctive physiological traits, strains of C. botulinum can be divided into four groups: however, only groups I and II are associated with human illness. Alignment of the flaA gene sequences from 40 group I and 40 group II strains identified a single BsrG1 restriction cut site that was present at base pair 283 in all group II flaA sequences and was not found in any group I sequence. The flaA gene was amplified by rapid colony PCR from 22 group I strains and 18 group II strains and digested with BsrGI restriction enzyme. Standard agarose gel electrophoresis with ethidium bromide staining showed two fragments, following restriction digestion of group II flaA gene amplicons with BsrGI, but only a single band of uncut flaA from group I strains. Combining rapid colony PCR with BsrGI restriction digest of the flaA gene at 60 degrees C is a significant improvement over current methods, such as meat digestion or amplified fragment length polymorphism, as a strain can be identified as either group I or group II in under 5 h when starting with a visible plated C. botulinum colony.

  6. Two Domain Flow Method for Leachate PredictionThrough Municipal Solid Waste Layers in Al–Amari Landfill Site

    Directory of Open Access Journals (Sweden)

    Hayder Mohammed Abdul–Hameed

    2008-01-01

    Full Text Available Existing leachate models over–or underestimates leachate generation by up to three orders of magnitude. Practical experiments show that channeled flow in waste leads to rapid discharge of large leachate volumes and heterogeneous moisture distribution. In order to more accurately predict leachate generation, leachate models must be improved. To predict moisture movement through waste, the two–domain PREFLO, are tested. Experimental waste and leachate flow values are compared with model predictions. When calibrated with experimental parameters, the PREFLO provides estimates of breakthrough time. In the short term, field capacity has to be reduced to 0.12 and effective storage and hydraulic conductivity of the waste must be increased to 0.12 and effective storage and hydraulic conductivity of the wasted must be increased to 0.2 and 2.2 cm/s respectively. In the long term, a new modeling approach must be developed to adequately describe the moisture movement mechanisms.

  7. A GIS-based approach for the long-term prediction of human health risks at contaminated sites

    NARCIS (Netherlands)

    Bien, J.D.; Meer, J.; Rulkens, W.H.; Rijnaarts, H.H.M.

    2004-01-01

    A Health Index/Risk Evaluation Tool (HIRET) has been developed for the integration of risk assessment and spatial planning using GIS capabilities. The method is meant to assist decision makers and site owners in the evaluation of potential human health risk with respect to land use. Human health

  8. Interactome-Wide Prediction of Protein-Protein Binding Sites Reveals Effects of Protein Sequence Variation in Arabidopsis thaliana

    NARCIS (Netherlands)

    Valentim, F.L.; Neven, F.; Boyen, P.; Dijk, van A.D.J.

    2012-01-01

    The specificity of protein-protein interactions is encoded in those parts of the sequence that compose the binding interface. Therefore, understanding how changes in protein sequence influence interaction specificity, and possibly the phenotype, requires knowing the location of binding sites in thos

  9. LRRK2 Kinase Activity and Biology are Not Uniformly Predicted by its Autophosphorylation and Cellular Phosphorylation Site Status

    Directory of Open Access Journals (Sweden)

    April eReynolds

    2014-06-01

    Full Text Available Missense mutations in the Leucine Rich Repeat protein Kinase 2 (LRRK2 gene are the most common genetic predisposition to develop Parkinson’s disease (PD LRRK2 is a large multi-domain phosphoprotein with a GTPase domain and a serine/threonine protein kinase domain whose activity is implicated in neuronal toxicity; however the precise mechanism is unknown. LRRK2 autophosphorylates on several serine/threonine residues across the enzyme and is found constitutively phosphorylated on Ser910, Ser935, Ser955 and Ser973, which are proposed to be regulated by upstream kinases. Here we investigate the phosphoregulation at these sites by analyzing the effects of disease-associated mutations Arg1441Cys, Arg1441Gly, Ala1442Pro, Tyr1699Cys, Ile2012Thr, Gly2019Ser, and Ile2020Thr. We also studied alanine substitutions of phosphosite serines 910, 935, 955 and 973 and specific LRRK2 inhibition on autophosphorylation of LRRK2 Ser1292, Thr1491, Thr2483 and phosphorylation at the cellular sites. We found that mutants in the Roc-COR domains, including Arg1441Cys, Arg1441His, Ala1442Pro and Tyr1699Cys, can positively enhance LRRK2 kinase activity while concomitantly inducing the dephosphorylation of the cellular sites. Mutation of the cellular sites individually did not affect LRRK2 intrinsic kinase activity; however, Ser910/935/955/973Ala mutations trended toward increased kinase activity of LRRK2. Increased cAMP levels did not lead to increased LRRK2 cellular site phosphorylation, 14-3-3 binding or kinase activity. In cells, inhibition of LRRK2 kinase activity leads to dephosphorylation of Ser1292 by Calyculin A and okadaic acid sensitive phosphatases, while the cellular sites are dephosphorylated by Calyculin A sensitive phosphatases. These findings indicate that comparative analysis of both Ser1292 and Ser910/935/955/973 phosphorylation sites will provide important and distinct measures of LRRK2 kinase and biological activity in vitro and in vivo.

  10. A-line, bispectral index, and estimated effect-site concentrations: a prediction of clinical end-points of anesthesia.

    NARCIS (Netherlands)

    Kreuer, S.; Bruhn, J.; Larsen, R.; Buchinger, H.; Wilhelm, W.

    2006-01-01

    Autoregressive modeling with exogenous input of middle-latency auditory evoked potentials (A-Line AEP index, AAI) has been developed for monitoring depth of anesthesia. We investigated the prediction of recovery and dose-response relationship of desflurane and AAI or bispectral index (BIS) values.

  11. Soil erosion model predictions using parent material/soil texture-based parameters compared to using site-specific parameters

    Science.gov (United States)

    R. B. Foltz; W. J. Elliot; N. S. Wagenbrenner

    2011-01-01

    Forested areas disturbed by access roads produce large amounts of sediment. One method to predict erosion and, hence, manage forest roads is the use of physically based soil erosion models. A perceived advantage of a physically based model is that it can be parameterized at one location and applied at another location with similar soil texture or geological parent...

  12. GENOMEMASKER package for designing unique genomic PCR primers

    Directory of Open Access Journals (Sweden)

    Kaplinski Lauris

    2006-03-01

    Full Text Available Abstract Background The design of oligonucleotides and PCR primers for studying large genomes is complicated by the redundancy of sequences. The eukaryotic genomes are particularly difficult to study due to abundant repeats. The speed of most existing primer evaluation programs is not sufficient for large-scale experiments. Results In order to improve the efficiency and success rate of automatic primer/oligo design, we created a novel method which allows rapid masking of repeats in large sequence files, for example in eukaryotic genomes. It also allows the detection of all alternative binding sites of PCR primers and the prediction of PCR products. The new method was implemented in a collection of efficient programs, the GENOMEMASKER package. The performance of the programs was compared to other similar programs. We also modified the PRIMER3 program, to be able to design primers from lowercase-masked sequences. Conclusion The GENOMEMASKER package is able to mask the entire human genome for non-unique primers within 6 hours and find locations of all binding sites for 10 000 designed primer pairs within 10 minutes. Additionally, it predicts all alternative PCR products from large genomes for given primer pairs.

  13. Predicting the Metabolic Sites by Flavin-Containing Monooxygenase on Drug Molecules Using SVM Classification on Computed Quantum Mechanics and Circular Fingerprints Molecular Descriptors

    Science.gov (United States)

    Fu, Chien-wei; Lin, Thy-Hou

    2017-01-01

    As an important enzyme in Phase I drug metabolism, the flavin-containing monooxygenase (FMO) also metabolizes some xenobiotics with soft nucleophiles. The site of metabolism (SOM) on a molecule is the site where the metabolic reaction is exerted by an enzyme. Accurate prediction of SOMs on drug molecules will assist the search for drug leads during the optimization process. Here, some quantum mechanics features such as the condensed Fukui function and attributes from circular fingerprints (called Molprint2D) are computed and classified using the support vector machine (SVM) for predicting some potential SOMs on a series of drugs that can be metabolized by FMO enzymes. The condensed Fukui function fA− representing the nucleophilicity of central atom A and the attributes from circular fingerprints accounting the influence of neighbors on the central atom. The total number of FMO substrates and non-substrates collected in the study is 85 and they are equally divided into the training and test sets with each carrying roughly the same number of potential SOMs. However, only N-oxidation and S-oxidation features were considered in the prediction since the available C-oxidation data was scarce. In the training process, the LibSVM package of WEKA package and the option of 10-fold cross validation are employed. The prediction performance on the test set evaluated by accuracy, Matthews correlation coefficient and area under ROC curve computed are 0.829, 0.659, and 0.877 respectively. This work reveals that the SVM model built can accurately predict the potential SOMs for drug molecules that are metabolizable by the FMO enzymes. PMID:28072829

  14. Practical Cost-Optimization of Characterization and Remediation Decisions at DNAPL Sites with Consideration of Prediction Uncertainty

    Science.gov (United States)

    2011-05-01

    many refinements through the project to simulate electron donor-limited biodecay, thermal remediation, and other processes . Mike Cardiff, under the...were undertaken to reduce source zone uncertainty. The method was also used to optimize source and plume bioremediation at the EGDY site, using whey ...with a 93% probability of success when using relatively low whey injection rates. The methodology was applied to Dover AFB Area 5 to optimize

  15. In Vitro Analysis of Predicted DNA-Binding Sites for the Stl Repressor of the Staphylococcus aureus SaPIBov1 Pathogenicity Island.

    Directory of Open Access Journals (Sweden)

    Veronika Papp-Kádár

    Full Text Available The regulation model of the Staphylococcus aureus pathogenicity island SaPIbov1 transfer was recently reported. The repressor protein Stl obstructs the expression of SaPI proteins Str and Xis, latter which is responsible for mobilization initiation. Upon Φ11 phage infection of S. aureus. phage dUTPase activates the SaPI transfer via Stl-dUTPase complex formation. Our aim was to predict the binding sites for the Stl repressor within the S. aureus pathogenicity island DNA sequence. We found that Stl was capable to bind to three 23-mer oligonucleotides, two of those constituting sequence segments in the stl-str, while the other corresponding to sequence segment within the str-xis intergenic region. Within these oligonucleotides, mutational analysis revealed that the predicted binding site for the Stl protein exists as a palindromic segment in both intergenic locations. The palindromes are built as 6-mer repeat sequences involved in Stl binding. The 6-mer repeats are separated by a 5 oligonucleotides long, nonspecific sequence. Future examination of the interaction between Stl and its binding sites in vivo will provide a molecular explanation for the mechanisms of gene repression and gene activation exerted simultaneously by the Stl protein in regulating transfer of the SaPIbov1 pathogenicity island in S. aureus.

  16. Predictions of tracer transport in interwell tracer tests at the C-Hole complex. Yucca Mountain site characterization project report milestone 4077

    Energy Technology Data Exchange (ETDEWEB)

    Reimus, P.W.

    1996-09-01

    This report presents predictions of tracer transport in interwell tracer tests that are to be conducted at the C-Hole complex at the Nevada Test Site on behalf of the Yucca Mountain Site Characterization Project. The predictions are used to make specific recommendations about the manner in which the tracer test should be conducted to best satisfy the needs of the Project. The objective of he tracer tests is to study flow and species transport under saturated conditions in the fractured tuffs near Yucca Mountain, Nevada, the site of a potential high-level nuclear waste repository. The potential repository will be located in the unsaturated zone within Yucca Mountain. The saturated zone beneath and around the mountain represents the final barrier to transport to the accessible environment that radionuclides will encounter if they breach the engineered barriers within the repository and the barriers to flow and transport provided by the unsaturated zone. Background information on the C-Holes is provided in Section 1.1, and the planned tracer testing program is discussed in Section 1.2.

  17. Effects of soil depth and subsurface flow along the subsurface topography on shallow landslide predictions at the site of a small granitic hillslope

    Science.gov (United States)

    Kim, Min Seok; Onda, Yuichi; Uchida, Taro; Kim, Jin Kwan

    2016-10-01

    Shallow landslides are affected by various conditions, including soil depth and subsurface flow via an increase in the pore water pressure. In this study, we evaluate the effect of soil depth and subsurface flow on shallow landslide prediction using the shallow landslide stability (SHALSTAB) model. Three detailed soil depth data-the average soil depth, weathered soil depth, and bedrock soil depth-were collected using a knocking pole test at a small hillslope site composed of granite in the Republic of Korea. The SHALSTAB model was applied to a ground surface topographic digital elevation model (DEM) using the three soil depths and upslope contributing area (SCA) assuming subsurface flow calculated from four DEMs: a ground surface topography (GSTO) DEM, weathered soil topography (WSTO) DEM, bedrock topography (BSTO) DEM, and low-level bedrock topography (EBSTO) DEM. The model performance was measured using a receiver operating characteristic (ROC) analysis. While evaluating the effect of the soil depth with SCA using GSTO DEM, it was found that the bedrock soil depth had higher prediction accuracy compared to that of the average soil depth or weathered soil depth. To evaluate the saturated subsurface flow between the soil and bedrock, SCAs calculated using WSTO and BSTO DEMs were applied. From these simulations, we found that SCA from BSTO DEM and the bedrock soil depth affect the shallow landslide prediction; however, these prediction effects are not significantly increased by large differences in the elevation (between the lowest and highest elevation values). Therefore, we considered the influence of the bedrock depression and SCA from EBSTO DEM. In applying SCA from EBSTO, the prediction accuracy was significantly increased compared to the other predictions. Our results demonstrate that the influence of the bedrock topography on the prediction of shallow landslides may be particularly significant at the scale of a hillslope.

  18. In silico prediction of the site of oxidation by cytochrome P450 3A4 that leads to the formation of the toxic metabolites of pyrrolizidine alkaloids.

    Science.gov (United States)

    Fashe, Muluneh M; Juvonen, Risto O; Petsalo, Aleksanteri; Vepsäläinen, Jouko; Pasanen, Markku; Rahnasto-Rilla, Minna

    2015-04-20

    In humans, the metabolic bioactivation of pyrrolizidine alkaloids (PAs) is mediated mainly by cytochrome P450 3A4 (CYP3A4) via the hydroxylation of their necine bases at C3 or C8 of heliotridine- and retronecine-type PAs or at the N atom of the methyl substituent of otonecine-type PAs. However, no attempts have been made to identify which C atom is the most favorable site for hydroxylation in silico. Here, in order to determine the site of hydroxylation that eventually leads to the formation of the toxic metabolites produced from lasiocarpine, retrorsine, and senkirkin, we utilized the ligand-based electrophilic Fukui function f(-)(r) and hydrogen-bond dissociation energies (BDEs) as well as structure-based molecular docking. The ligand-based computations revealed that the C3 and C8 atoms of lasiocarpine and retrorsine and the C26 atom of senkirkin were chemically the most susceptible locations for electrophilic oxidizing reactions. Similarly, according to the predicted binding orientation in the active site of the crystal structure of human CYP3A4 (PDB code: 4I4G ), the alkaloids were positioned in such a way that the C3 atom of lasiocarpine and retrorsine and the C26 of senkirkin were closest to the catalytic heme Fe. Thus, it is concluded that the C3 atom of lasiocarpine and retrorsine and C26 of senkirkin are the most favored sites of hydroxylation that lead to the production of their toxic metabolites.

  19. Rapid on-site evaluation of endoscopic ultrasound core biopsy specimens has excellent specificity and positive predictive value for gastrointestinal lesions.

    Science.gov (United States)

    Krishnan, Kumar; Dalal, Sharvari; Nayar, Ritu; Keswani, Rajesh N; Keefer, Laurie; Komanduri, Srinadh

    2013-07-01

    Endoscopic ultrasound (EUS) with fine needle aspiration (FNA) is a safe and effective way to sample lesions in the gastrointestinal tract. Rapid on-site specimen evaluation (ROSE) improves the accuracy of EUS-FNA. While data suggests that EUS with fine-needle biopsy (EUS-FNB) is effective, it remains unclear if ROSE is predictive of a final diagnosis when obtaining core specimens. The aim of this study was to investigate the utility of ROSE in achieving a final diagnosis for EUS-FNB core specimens. We evaluated 60 consecutive patients referred for EUS guided sampling of lesions within or adjacent to the gastrointestinal tract. All patients underwent EUS-FNB to evaluate the additive value of ROSE to the diagnostic accuracy of specimens obtained using a core biopsy needle. EUS-FNA was also performed in a majority of cases. EUS-FNB was feasible in all 60 cases; on-site specimen adequacy and final diagnostic accuracy was 58 % [95 % confidence intervals (CI) 45.1-71.2] and 83 % (95 % CI 71.9-91.5), respectively. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value of ROSE for core biopsies were 65, 100, 100, and 39 %, respectively. On-site adequacy and diagnostic accuracy for EUS-FNA was 38 % (95 % CI 22.2-53.5) and 63 % (95 % CI 50.1-75.8), respectively. There were no significant complications. EUS-FNB is safe, feasible, and effective. ROSE of the core biopsy provides excellent PPV; however, an inadequate ROSE appears to be of limited value. Further prospective studies are needed to assess the optimal handling and onsite processing of core specimens to determine whether ROSE is beneficial for EUS-FNB.

  20. Using transcranial magnetic stimulation of the undamaged brain to identify lesion sites that predict language outcome after stroke.

    Science.gov (United States)

    Lorca-Puls, Diego L; Gajardo-Vidal, Andrea; Seghier, Mohamed L; Leff, Alexander P; Sethi, Varun; Prejawa, Susan; Hope, Thomas M H; Devlin, Joseph T; Price, Cathy J

    2017-06-01

    Transcranial magnetic stimulation focused on either the left anterior supramarginal gyrus or opercular part of the left inferior frontal gyrus has been reported to transiently impair the ability to perform phonological more than semantic tasks. Here we tested whether phonological processing abilities were also impaired following lesions to these regions in right-handed, English speaking adults, who were investigated at least 1 year after a left-hemisphere stroke. When our regions of interest were limited to 0.5 cm3 of grey matter centred around sites that had been identified with transcranial magnetic stimulation-based functional localization, phonological impairments were observed in 74% (40/54) of patients with damage to the regions and 21% (21/100) of patients sparing these regions. This classification accuracy was better than that observed when using regions of interest centred on activation sites in previous functional magnetic resonance imaging studies of phonological processing, or transcranial magnetic stimulation sites that did not use functional localization. New regions of interest were generated by redefining the borders of each of the transcranial magnetic stimulation sites to include areas that were consistently damaged in the patients with phonological impairments. This increased the incidence of phonological impairments in the presence of damage to 85% (46/54) and also reduced the incidence of phonological impairments in the absence of damage to 15% (15/100). The difference in phonological processing abilities between those with and without damage to these 'transcranial magnetic stimulation-guided' regions remained highly significant even after controlling for the effect of lesion size. The classification accuracy of the transcranial magnetic stimulation-guided regions was validated in a second sample of 108 patients and found to be better than that for (i) functional magnetic resonance imaging-guided regions; (ii) a region identified from an

  1. Single-Nucleotide Mutation Matrix: A New Model for Predicting the NF-κB DNA Binding Sites

    OpenAIRE

    Wenxin Du; Jing Gao; Tingting Wang; Jinke Wang

    2014-01-01

    In this study, we established a single nucleotide mutation matrix (SNMM) model based on the relative binding affinities of NF-κB p50 homodimer to a wild-type binding site (GGGACTTTCC) and its all single-nucleotide mutants detected with the double-stranded DNA microarray. We evaluated this model by scoring different groups of 10-bp DNA sequences with this model and analyzing the correlations between the scores and the relative binding affinities detected with three wet experiments, including t...

  2. Receptor site topographies for phencyclidine-like and sigma drugs: predictions from quantitative conformational, electrostatic potential, and radioreceptor analyses.

    Science.gov (United States)

    Manallack, D T; Wong, M G; Costa, M; Andrews, P R; Beart, P M

    1988-12-01

    Computer-assisted molecular modelling techniques and electrostatic analyses of a wide range of phenycyclidine (PCP) and sigma ligands, in conjunction with radioreceptor studies, were used to determine the topographies of the PCP and sigma receptors. The PCP receptor model was defined using key molecules from the arylcyclohexylamine, benzomorphan, bridged benz[f]isoquinoline, and dibenzocycloalkenimine drug classes. Hypothetical receptor points (R1, R2) were constructed onto the aromatic ring of each compound to represent hydrophobic interactions with the receptor, along with an additional receptor point (R3) representing a hydrogen bond between the nitrogen atom and the receptor. The superimposition of these key molecules gave the coordinates of the receptor points and nitrogen defining the primary PCP pharmacophore as follows: R1 (0.00, 3.50, 0.00), R2 (0.00, -3.50, 0.00), R3 (6.66, -1.13, 0.00), and N (3.90, -1.46, -0.32). Additional analyses were used to describe secondary binding sites for an additional hydrogen bonding site and two lipophilic clefts. Similarly, the sigma receptor model was constructed from ligands of the benzomorphan, octahydrobenzo[f]quinoline, phenylpiperidine, and diphenylguanidine drug classes. Coordinates for the primary sigma pharmacophore are as follows: R1 (0.00, 3.50, 0.00), R2 (0.00, -3.50, 0.00), R3 (6.09, 2.09, 0.00), and N (4.9, -0.12, -1.25). Secondary binding sites for sigma ligands were proposed for the interaction of aromatic ring substituents and large N-substituted lipophilic groups with the receptor. The sigma receptor model differs from the PCP model in the position of nitrogen atom, direction of the nitrogen lone pair vector, and secondary sigma binding sites. This study has thus demonstrated that the differing quantitative structure-activity relationships of PCP and sigma ligands allow the definition of discrete receptors. These models may be used in conjunction with rational drug design techniques to design novel PCP

  3. Prediction of altered 3'- UTR miRNA-binding sites from RNA-Seq data: the swine leukocyte antigen complex (SLA as a model region.

    Directory of Open Access Journals (Sweden)

    Marie-Laure Endale Ahanda

    Full Text Available THE SLA (swine leukocyte antigen, MHC: SLA genes are the most important determinants of immune, infectious disease and vaccine response in pigs; several genetic associations with immunity and swine production traits have been reported. However, most of the current knowledge on SLA is limited to gene coding regions. MicroRNAs (miRNAs are small molecules that post-transcriptionally regulate the expression of a large number of protein-coding genes in metazoans, and are suggested to play important roles in fine-tuning immune mechanisms and disease responses. Polymorphisms in either miRNAs or their gene targets may have a significant impact on gene expression by abolishing, weakening or creating miRNA target sites, possibly leading to phenotypic variation. We explored the impact of variants in the 3'-UTR miRNA target sites of genes within the whole SLA region. The combined predictions by TargetScan, PACMIT and TargetSpy, based on different biological parameters, empowered the identification of miRNA target sites and the discovery of polymorphic miRNA target sites (poly-miRTSs. Predictions for three SLA genes characterized by a different range of sequence variation provided proof of principle for the analysis of poly-miRTSs from a total of 144 M RNA-Seq reads collected from different porcine tissues. Twenty-four novel SNPs were predicted to affect miRNA-binding sites in 19 genes of the SLA region. Seven of these genes (SLA-1, SLA-6, SLA-DQA, SLA-DQB1, SLA-DOA, SLA-DOB and TAP1 are linked to antigen processing and presentation functions, which is reminiscent of associations with disease traits reported for altered miRNA binding to MHC genes in humans. An inverse correlation in expression levels was demonstrated between miRNAs and co-expressed SLA targets by exploiting a published dataset (RNA-Seq and small RNA-Seq of three porcine tissues. Our results support the resource value of RNA-Seq collections to identify SNPs that may lead to altered mi

  4. Prediction of altered 3'- UTR miRNA-binding sites from RNA-Seq data: the swine leukocyte antigen complex (SLA) as a model region.

    Science.gov (United States)

    Endale Ahanda, Marie-Laure; Fritz, Eric R; Estellé, Jordi; Hu, Zhi-Liang; Madsen, Ole; Groenen, Martien A M; Beraldi, Dario; Kapetanovic, Ronan; Hume, David A; Rowland, Robert R R; Lunney, Joan K; Rogel-Gaillard, Claire; Reecy, James M; Giuffra, Elisabetta

    2012-01-01

    THE SLA (swine leukocyte antigen, MHC: SLA) genes are the most important determinants of immune, infectious disease and vaccine response in pigs; several genetic associations with immunity and swine production traits have been reported. However, most of the current knowledge on SLA is limited to gene coding regions. MicroRNAs (miRNAs) are small molecules that post-transcriptionally regulate the expression of a large number of protein-coding genes in metazoans, and are suggested to play important roles in fine-tuning immune mechanisms and disease responses. Polymorphisms in either miRNAs or their gene targets may have a significant impact on gene expression by abolishing, weakening or creating miRNA target sites, possibly leading to phenotypic variation. We explored the impact of variants in the 3'-UTR miRNA target sites of genes within the whole SLA region. The combined predictions by TargetScan, PACMIT and TargetSpy, based on different biological parameters, empowered the identification of miRNA target sites and the discovery of polymorphic miRNA target sites (poly-miRTSs). Predictions for three SLA genes characterized by a different range of sequence variation provided proof of principle for the analysis of poly-miRTSs from a total of 144 M RNA-Seq reads collected from different porcine tissues. Twenty-four novel SNPs were predicted to affect miRNA-binding sites in 19 genes of the SLA region. Seven of these genes (SLA-1, SLA-6, SLA-DQA, SLA-DQB1, SLA-DOA, SLA-DOB and TAP1) are linked to antigen processing and presentation functions, which is reminiscent of associations with disease traits reported for altered miRNA binding to MHC genes in humans. An inverse correlation in expression levels was demonstrated between miRNAs and co-expressed SLA targets by exploiting a published dataset (RNA-Seq and small RNA-Seq) of three porcine tissues. Our results support the resource value of RNA-Seq collections to identify SNPs that may lead to altered miRNA regulation patterns.

  5. Prediction of Altered 3′- UTR miRNA-Binding Sites from RNA-Seq Data: The Swine Leukocyte Antigen Complex (SLA) as a Model Region

    Science.gov (United States)

    Endale Ahanda, Marie-Laure; Fritz, Eric R.; Estellé, Jordi; Hu, Zhi-Liang; Madsen, Ole; Groenen, Martien A. M.; Beraldi, Dario; Kapetanovic, Ronan; Hume, David A.; Rowland, Robert R. R.; Lunney, Joan K.; Rogel-Gaillard, Claire; Reecy, James M.; Giuffra, Elisabetta

    2012-01-01

    The SLA (swine leukocyte antigen, MHC: SLA) genes are the most important determinants of immune, infectious disease and vaccine response in pigs; several genetic associations with immunity and swine production traits have been reported. However, most of the current knowledge on SLA is limited to gene coding regions. MicroRNAs (miRNAs) are small molecules that post-transcriptionally regulate the expression of a large number of protein-coding genes in metazoans, and are suggested to play important roles in fine-tuning immune mechanisms and disease responses. Polymorphisms in either miRNAs or their gene targets may have a significant impact on gene expression by abolishing, weakening or creating miRNA target sites, possibly leading to phenotypic variation. We explored the impact of variants in the 3′-UTR miRNA target sites of genes within the whole SLA region. The combined predictions by TargetScan, PACMIT and TargetSpy, based on different biological parameters, empowered the identification of miRNA target sites and the discovery of polymorphic miRNA target sites (poly-miRTSs). Predictions for three SLA genes characterized by a different range of sequence variation provided proof of principle for the analysis of poly-miRTSs from a total of 144 M RNA-Seq reads collected from different porcine tissues. Twenty-four novel SNPs were predicted to affect miRNA-binding sites in 19 genes of the SLA region. Seven of these genes (SLA-1, SLA-6, SLA-DQA, SLA-DQB1, SLA-DOA, SLA-DOB and TAP1) are linked to antigen processing and presentation functions, which is reminiscent of associations with disease traits reported for altered miRNA binding to MHC genes in humans. An inverse correlation in expression levels was demonstrated between miRNAs and co-expressed SLA targets by exploiting a published dataset (RNA-Seq and small RNA-Seq) of three porcine tissues. Our results support the resource value of RNA-Seq collections to identify SNPs that may lead to altered miRNA regulation

  6. Predicting the right spacing between protein immobilization sites on self-assembled monolayers to optimize ligand binding.

    Science.gov (United States)

    Perez, Javier Batista; Tyagi, Deependra; Yang, Mo; Calvo, Loany; Perez, Rolando; Moreno, Ernesto; Zhu, Jinsong

    2015-09-01

    Self-assembled monolayers designed to immobilize capture antibodies are usually prepared using a mixture of functional and inactive linkers. Here, using low molar ratios (1:1 to 1:100) of the two linkers resulted in loss of binding capability of the anti-EGFR (epidermal growth factor receptor) antibody nimotuzumab, as assessed by surface plasmon resonance imaging. We then developed a simple theoretical model to predict the optimal surface density of the functional linker, taking into account the antibody size and linker diameter. A high (1:1000) dilution of the functional linker yielded the best results. As an advantage, this approach does not require chemical modification of the protein.

  7. Prediction of residual stress due to early age behaviour of massive concrete structures: on site experiments and macroscopic modelling

    CERN Document Server

    Zreiki, Jihad; Chaouche, Mohend; Moranville, Micheline

    2008-01-01

    Early age behaviour of concrete is based on complex multi-physical and multiscale phenomena. The predication of both cracking risk and residual stresses in hardened concrete structures is still a challenging task. We propose in this paper a practical method to characterize in the construction site the material parameters and to identify a macroscopic model from simple tests. We propose for instance to use a restrained shrinkage ring test to identify a basic early age creep model based on a simple ageing visco-elastic Kelvin model. The strain data obtained from this test can be treated through an early age finite element incremental procedure such that the fitting parameters of the creep law can be quickly identified. The others properties of concrete have been measured at different ages (elastic properties, hydration kinetics, and coefficient of thermal expansion). From the identified early age model, we computed the temperature rise and the stress development in a non reinforced concrete stress for nuclear w...

  8. A GIS-based prediction and assessment system of off-site accident consequence for Guangdong nuclear power plant.

    Science.gov (United States)

    Wang, X Y; Qu, J Y; Shi, Z Q; Ling, Y S

    2003-01-01

    GNARD (Guangdong Nuclear Accident Real-time Decision support system) is a decision support system for off-site emergency management in the event of an accidental release from the nuclear power plants located in Guangdong province, China. The system is capable of calculating wind field, concentrations of radionuclide in environmental media and radiation doses. It can also estimate the size of the area where protective actions should be taken and provide other information about population distribution and emergency facilities available in the area. Furthermore, the system can simulate and evaluate the effectiveness of countermeasures assumed and calculate averted doses by protective actions. All of the results can be shown and analysed on the platform of a geographical information system (GIS).

  9. Identification and Validation of Novel Hedgehog-Responsive Enhancers Predicted by Computational Analysis of Ci/Gli Binding Site Density.

    Directory of Open Access Journals (Sweden)

    Katherine Gurdziel

    Full Text Available The Hedgehog (Hh signaling pathway directs a multitude of cellular responses during embryogenesis and adult tissue homeostasis. Stimulation of the pathway results in activation of Hh target genes by the transcription factor Ci/Gli, which binds to specific motifs in genomic enhancers. In Drosophila, only a few enhancers (patched, decapentaplegic, wingless, stripe, knot, hairy, orthodenticle have been shown by in vivo functional assays to depend on direct Ci/Gli regulation. All but one (orthodenticle contain more than one Ci/Gli site, prompting us to directly test whether homotypic clustering of Ci/Gli binding sites is sufficient to define a Hh-regulated enhancer. We therefore developed a computational algorithm to identify Ci/Gli clusters that are enriched over random expectation, within a given region of the genome. Candidate genomic regions containing Ci/Gli clusters were functionally tested in chicken neural tube electroporation assays and in transgenic flies. Of the 22 Ci/Gli clusters tested, seven novel enhancers (and the previously known patched enhancer were identified as Hh-responsive and Ci/Gli-dependent in one or both of these assays, including: Cuticular protein 100A (Cpr100A; invected (inv, which encodes an engrailed-related transcription factor expressed at the anterior/posterior wing disc boundary; roadkill (rdx, the fly homolog of vertebrate Spop; the segment polarity gene gooseberry (gsb; and two previously untested regions of the Hh receptor-encoding patched (ptc gene. We conclude that homotypic Ci/Gli clustering is not sufficient information to ensure Hh-responsiveness; however, it can provide a clue for enhancer recognition within putative Hedgehog target gene loci.

  10. Theoretical prediction of single-site surface-protonation equilibrium constants for oxides and silicates in water

    Energy Technology Data Exchange (ETDEWEB)

    Sverjensky, D.A.; Sahai, N. [Johns Hopkins Univ., Baltimore, MD (United States)

    1996-10-01

    The equilibrium constants for surface protonation of solid oxides and silicates can be estimated from theoretical considerations and known properties of the solids for use in the constant capacitance, diffuse double layer or triple layer models of surface complexation. The theoretical considerations take into account Born solvation theory for the adsorbing proton, electrostatic interactions of the adsorbing proton with a surface oxygen and an underlying metal, and an intrinsic binding of the proton to the surface. As a consequence, the equilibrium constants for the {nu}th ({nu} = 1 or 2) surface protonation reaction on the kth solid can be expressed in terms of the inverse of the dielectric constant of the solid (1/{epsilon}{sub k}) and an average Pauling bond strength per angstrom (s/r{sub M-OH}) for the solid according to log K{sub {nu}} = M{sub {nu}}(1/{epsilon}{sub k}) - B{sub {nu}}(s/r{sub M-OH}) + log K{sub ii,{nu}}{sup {double_prime}}, where the coefficients M{sub {nu}} B{sub {nu}} and K{sub ii{nu}}{sup {double_prime}} are constants characteristic of all oxides and silicates for each surface complexation model. Evaluation of these constants using experimental data for TiO{sub 2}, {gamma}-alumina, Al{sub 2}O{sub 3} FeOOH, Fe(OH){sub 3}, silica, quartz. and kaolinite permits widespread prediction of surface protonation equilibrium constants from the known bulk structure properties 1/{epsilon}{sub k} and s/r{sub M-OH}. Such predictions should replace attempts to estimate surface protonation equilibrium constants for solids from empirical correlations with aqueous equilibrium constants. Surface protonation constants should also not be estimated from correlations with only the Pauling bond strength because these neglect specific treatment of salvation. 92 refs., 14 figs., 4 tabs.

  11. Data-Model Assimilation at the FACE and AmeriFlux Sites Toward Predictive Understanding of Carbon Sequestration at Ecosystem and Regional Scales

    Energy Technology Data Exchange (ETDEWEB)

    Luo, Yiqi [Univ. of Oklahoma, Norman, OK (United States)

    2013-01-09

    The project was conducted during the period from 9/1/2007 to 8/31/2011 with three major tasks: (1) development of data assimilation (DA) techniques for terrestrial carbon research; (2) applications of DA techniques to analysis of carbon cycle at Duke and other FACE sites; and (3) inverse analysis at AmeriFlux sites. During this period, we have developed a variety of techniques, including (1) ensemble Kalman filter to estimate model parameters or state variables (Gao et al. 2011), (2) Conditional inversion to estimate parameters of a carbon cycle model (Wu et al. 2009), and (3) various methods to quantify uncertainty of estimated parameters and predicted C sinks (e.g., Weng et al. 2011), and (4) information theory to evaluate information content of different model structures and data sets (Weng and Luo 2011). We applied the DA techniques to and did modeling at the Duke FACE and other global change experimental sites. We addressed the following issues: (1) interactive effects of CO2, warming and precipitation on ecosystem processes (e.g., Luo et al. 2008, Weng and Luo 2008, Zhou et al. 2008), (2) effects of warming on estimated parameters related to photosynthesis and residence times (Zhou et al. 2010); and (3) uncertainty in estimated parameters and predicted C sequestration (Gao et al. 2011, Weng and Luo 2011). In addition, we have done data assimilation to estimate carbon residence and carbon sequestration in US continent (Zhou and Luo 2008) and temperature sensitivity at the global scale (Zhou et al. 2009).

  12. Use of Mutual Information Arrays to Predict Coevolving Sites in the Full Length HIV gp120 Protein for Subtypes B and C

    Institute of Scientific and Technical Information of China (English)

    Bo Wei; Na Han; Hai-zhou Liu; Anthony Rayner; Simon Rayner

    2011-01-01

    It is well established that different sites within a protein evolve at different rates according to their role within the protein; identification of these correlated mutations can aid in tasks such as ab initio protein structure,structure function analysis or sequence alignment.Mutual Information is a standard measure for coevolution between two sites but its application is limited by signal to noise ratio.In this work we report a preliminary study to investigate whether larger sequence sets could circumvent this problem by calculating mutual information arrays for two sets of drug naive sequences from the HIV gp120 protein for the B and C subtypes.Our results suggest that while the larger sequences sets can improve the signal to noise ratio,the gain is offset by the high mutation rate of the HIV virus which makes it more difficult to achieve consistent alignments.Nevertheless,we were able to predict a number of coevolving sites that were supported by previous experimental studies as well as a region close to the C terminal of the protein that was highly variable in the C subtype but highly conserved in the B subtype.

  13. Prediction of site-specific interactions in antibody-antigen complexes: the proABC method and server.

    KAUST Repository

    Olimpieri, Pier Paolo

    2013-06-26

    MOTIVATION: Antibodies or immunoglobulins are proteins of paramount importance in the immune system. They are extremely relevant as diagnostic, biotechnological and therapeutic tools. Their modular structure makes it easy to re-engineer them for specific purposes. Short of undergoing a trial and error process, these experiments, as well as others, need to rely on an understanding of the specific determinants of the antibody binding mode. RESULTS: In this article, we present a method to identify, on the basis of the antibody sequence alone, which residues of an antibody directly interact with its cognate antigen. The method, based on the random forest automatic learning techniques, reaches a recall and specificity as high as 80% and is implemented as a free and easy-to-use server, named prediction of Antibody Contacts. We believe that it can be of great help in re-design experiments as well as a guide for molecular docking experiments. The results that we obtained also allowed us to dissect which features of the antibody sequence contribute most to the involvement of specific residues in binding to the antigen. AVAILABILITY: http://www.biocomputing.it/proABC. CONTACT: anna.tramontano@uniroma1.it or paolo.marcatili@gmail.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

  14. Predicting ESR Peaks in Copper (II Chelates Having Quadrupolar Coordinating Sites by NMR, ESR and NQR Techniques: A DFT Study

    Directory of Open Access Journals (Sweden)

    Harminder Singh

    2015-06-01

    Full Text Available Computational chemistry was helpful in predicting the number of ESR peaks in Cu (II complexes having a large number of spatially different NMR and ESR active nuclei. The presence of the large Jahn-Teller effect and the high value of spin-orbit coupling constant of the metal ion made the experimental determination of the exact number of ESR peaks quite difficult in such complexes. Fourteen distorted poly-dentate chelating Cu(II complexes included in this study were of two types such as [Cu(gly2] , [Cu(edta]4-,[Cu(tpyX2] (X= Cl, Br, I, NCS and [Cu(en2]2+, [Cu(teta]2+, Cu(tepa]2+ ,[Cu(peha]2+, [Cu(detaX2] (X= Cl, Br, I, NCS.The latter eight complexes belonged to an important class of ligands called polyethylene polyamines. Density functional theory implemented in ADF: 2010.02 was applied. Three parameters of both the ESR (A ten and NQR (NQCC, for the Cu(II and the coordinating atoms of the ligands were obtained from “ESR/EPR program” and two NMR parameters namely the shielding constants (σ and chemical shifts (δ were obtained from “NMR/EPR program” after optimization of the complexes. The species having the same values of these 5 parameters were expected to be spatially equivalent to undergo the same hyperfine interaction with Cu (II.

  15. Palatal Augmentation Technique: A Predictable Method to Increase the Palatal Connective Tissue at Donor Sites- A Consecutive Case Series.

    Science.gov (United States)

    Carnio, João; Koutouzis, Theofilos

    2015-01-01

    The palatal masticatory mucosa between the canine and first molar is the main source of connective tissue graft (CTG) for use in periodontal plastic surgery. The purpose of this study was to evaluate the palatal augmentation technique (PAT) to increase the palatal connective tissue donor area using a collagen sponge inserted between the palatal flap and bone. The 26 patients enrolled in this study were referred for root coverage and ridge augmentation procedures. All patients lacked adequate donor palatal tissue thickness. The PAT uses a full-thickness flap and insertion of a sterile lyophilized bovine collagen sponge between the flap and bone. The palatal thickness was clinically assessed before and after collagen sponge insertion. A manual probe was inserted in the mucosal surface perpendicular to the long axis of each tooth approximately 6 mm from the gingival margin. Probing depth (PD) and recession (REC) were also recorded. Treatment with PAT resulted in a statistically significant increase in the palatal thickness. The overall mean increase was from 2.03 mm before surgery to 3.57 mm after surgery, with no major alterations in PD and REC. Healing proceeded uneventfully and occurred by primary intention. PAT appeared to be a predictable procedure to create connective tissue donor graft in deficient areas and had uneventful postoperative healing.

  16. Uniqueness property for quasiharmonic functions

    Directory of Open Access Journals (Sweden)

    Sevdiyor A. Imomkulov

    2014-10-01

    Full Text Available In this paper we consider a class of continuous functions, called quasiaharmonic functions, admitting best approximations by harmonic polynomials. In this class we prove a uniqueness theorem by analogy with the analytic functions.

  17. Diabetes: Unique to Older Adults

    Science.gov (United States)

    ... Stroke Urinary Incontinence Related Documents PDF Choosing Wisely: Diabetes Tests and Treatments Download Related Video Join our e-newsletter! Aging & Health A to Z Diabetes Unique to Older Adults This section provides information ...

  18. Osteoporosis: Unique to Older Adults

    Science.gov (United States)

    ... our e-newsletter! Aging & Health A to Z Osteoporosis Unique to Older Adults This section provides information ... and widely-prescribed medications for the treatment of osteoporosis. Some serious side effects of these medication have ...

  19. Nutrition: Unique to Older Adults

    Science.gov (United States)

    ... our e-newsletter! Aging & Health A to Z Nutrition Unique to Older Adults This section provides information ... teeth that are needed for grinding up food, nutrition suffers. If you are unable to chew and ...

  20. PSNO: Predicting Cysteine S-Nitrosylation Sites by Incorporating Various Sequence-Derived Features into the General Form of Chou’s PseAAC

    Directory of Open Access Journals (Sweden)

    Jian Zhang

    2014-06-01

    Full Text Available S-nitrosylation (SNO is one of the most universal reversible post-translational modifications involved in many biological processes. Malfunction or dysregulation of SNO leads to a series of severe diseases, such as developmental abnormalities and various diseases. Therefore, the identification of SNO sites (SNOs provides insights into disease progression and drug development. In this paper, a new bioinformatics tool, named PSNO, is proposed to identify SNOs from protein sequences. Firstly, we explore various promising sequence-derived discriminative features, including the evolutionary profile, the predicted secondary structure and the physicochemical properties. Secondly, rather than simply combining the features, which may bring about information redundancy and unwanted noise, we use the relative entropy selection and incremental feature selection approach to select the optimal feature subsets. Thirdly, we train our model by the technique of the k-nearest neighbor algorithm. Using both informative features and an elaborate feature selection scheme, our method, PSNO, achieves good prediction performance with a mean Mathews correlation coefficient (MCC value of about 0.5119 on the training dataset using 10-fold cross-validation. These results indicate that PSNO can be used as a competitive predictor among the state-of-the-art SNOs prediction tools. A web-server, named PSNO, which implements the proposed method, is freely available at http://59.73.198.144:8088/PSNO/.

  1. Habitat composition and connectivity predicts bat presence and activity at foraging sites in a large UK conurbation.

    Directory of Open Access Journals (Sweden)

    James D Hale

    Full Text Available BACKGROUND: Urbanization is characterized by high levels of sealed land-cover, and small, geometrically complex, fragmented land-use patches. The extent and density of urbanized land-use is increasing, with implications for habitat quality, connectivity and city ecology. Little is known about densification thresholds for urban ecosystem function, and the response of mammals, nocturnal and cryptic taxa are poorly studied in this respect. Bats (Chiroptera are sensitive to changing urban form at a species, guild and community level, so are ideal model organisms for analyses of this nature. METHODOLOGY/PRINCIPAL FINDINGS: We surveyed bats around urban ponds in the West Midlands conurbation, United Kingdom (UK. Sites were stratified between five urban land classes, representing a gradient of built land-cover at the 1 km(2 scale. Models for bat presence and activity were developed using land-cover and land-use data from multiple radii around each pond. Structural connectivity of tree networks was used as an indicator of the functional connectivity between habitats. All species were sensitive to measures of urban density. Some were also sensitive to landscape composition and structural connectivity at different spatial scales. These results represent new findings for an urban area. The activity of Pipistrellus pipistrellus (Schreber 1774 exhibited a non-linear relationship with the area of built land-cover, being much reduced beyond the threshold of ∼60% built surface. The presence of tree networks appears to mitigate the negative effects of urbanization for this species. CONCLUSIONS/SIGNIFICANCE: Our results suggest that increasing urban density negatively impacts the study species. This has implications for infill development policy, built density targets and the compact city debate. Bats were also sensitive to the composition and structure of the urban form at a range of spatial scales, with implications for land-use planning and management

  2. Monte Carlo simulation of base and nucleotide excision repair of clustered DNA damage sites. I. Model properties and predicted trends

    Energy Technology Data Exchange (ETDEWEB)

    Semenenko, Vladimir; Stewart, Robert D.; Ackerman, Eric J.

    2005-12-31

    Single-cell irradiators and new experimental assays are rapidly expanding our ability to quantify the molecular mechanisms responsible for phenomena such as toxicant-induced adaptations in DNA repair and signal-mediated changes to the genome stability of cells not directly damaged by radiation (i.e., bystander cells). To advance our understanding of, and ability to predict and mitigate, the potentially harmful effects of radiological agents, effective strategies must be devised to incorporate information from molecular and cellular studies into mechanism-based, hierarchical models. A key advantage of the hierarchical modeling approach is that information from DNA repair and other in vitro assays can be systematically integrated into higher-level cell transformation and, eventually, carcinogenesis models. This presentation will outline the hierarchical modeling strategy used to integrate information from in vitro studies into the Virtual Cell (VC) radiobiology software (see Endnote). A new multi-path genomic instability model will be introduced and used to link biochemical processing of double strand breaks (DSBs) to neoplastic cell transformation. Bystander and directly damaged cells are treated explicitly in the model using a microdosimetric approach, although many of the details of the bystander response model are of a necessarily preliminary nature. The new model will be tested against several published radiobiological datasets. Results illustrating how hypothesized bystander mechanisms affect the shape of dose-response curves for neoplastic transformation as a function of Linear Energy Transfer (LET) will be presented. EndNote: R.D. Stewart, Virtual Cell (VC) Radiobiology Software. PNNL-13579, July 2001. Available at http://www.pnl.gov/berc/kbem/vc/ The DNA repair model used in the VC computer program is based on the Two-Lesion Kinetic (TLK) model [Radiat. Res. 156(4), 365-378 October 2001].

  3. Quantum coupled mutation finder: predicting functionally or structurally important sites in proteins using quantum Jensen-Shannon divergence and CUDA programming.

    Science.gov (United States)

    Gültas, Mehmet; Düzgün, Güncel; Herzog, Sebastian; Jäger, Sven Joachim; Meckbach, Cornelia; Wingender, Edgar; Waack, Stephan

    2014-04-03

    The identification of functionally or structurally important non-conserved residue sites in protein MSAs is an important challenge for understanding the structural basis and molecular mechanism of protein functions. Despite the rich literature on compensatory mutations as well as sequence conservation analysis for the detection of those important residues, previous methods often rely on classical information-theoretic measures. However, these measures usually do not take into account dis/similarities of amino acids which are likely to be crucial for those residues. In this study, we present a new method, the Quantum Coupled Mutation Finder (QCMF) that incorporates significant dis/similar amino acid pair signals in the prediction of functionally or structurally important sites. The result of this study is twofold. First, using the essential sites of two human proteins, namely epidermal growth factor receptor (EGFR) and glucokinase (GCK), we tested the QCMF-method. The QCMF includes two metrics based on quantum Jensen-Shannon divergence to measure both sequence conservation and compensatory mutations. We found that the QCMF reaches an improved performance in identifying essential sites from MSAs of both proteins with a significantly higher Matthews correlation coefficient (MCC) value in comparison to previous methods. Second, using a data set of 153 proteins, we made a pairwise comparison between QCMF and three conventional methods. This comparison study strongly suggests that QCMF complements the conventional methods for the identification of correlated mutations in MSAs. QCMF utilizes the notion of entanglement, which is a major resource of quantum information, to model significant dissimilar and similar amino acid pair signals in the detection of functionally or structurally important sites. Our results suggest that on the one hand QCMF significantly outperforms the previous method, which mainly focuses on dissimilar amino acid signals, to detect essential sites

  4. User comment behavior prediction in social networking sites%社交网站中用户评论行为预测

    Institute of Scientific and Technical Information of China (English)

    孔庆超; 毛文吉; 张育浩

    2015-01-01

    Social networking sites provide a convenient way for users to communicate with others and to present opin⁃ions. Related researches on modeling and predicting user behaviors in social networking sites are of vital importance for many applications in the domains of security and business. The aim of this paper is to predict user comment behav⁃ior based on postings in social networking sites. A feature⁃based machine learning approach is employed, which in⁃cludes features from the postings, content, user behaviors and social relations, and introduces a parameter to control the imbalanceness of the dataset. Real⁃world datasets from Douban Group were used in the experiments. The experi⁃mental results showed that the user behavior and social relation features and the imbalance processing technique effec⁃tively improved the prediction performance of user comment behaviors. This further demonstrates that the user com⁃ment behavior is largely affected by their behavior history and social network.%社交网站为用户相互交流、发表意见和观点提供了非常便利的平台。对社交网站的用户行为进行建模和预测对于安全、商业等多个领域具有十分重要的社会意义和应用价值,近年来逐渐得到研究者的重视。面向社交网站中用户评论行为,预测用户是否会参与讨论。采用基于特征的机器学习方法,其中特征包括讨论帖子及其内容、用户行为特征和社交关系,并引入参数控制数据集的不平衡性。实验采用来自豆瓣小组的真实数据。实验结果表明,新提出的用户行为和社交关系特征以及对不平衡数据集的处理方法能够有效提高用户评论行为的预测效果,进一步说明用户的历史行为和所在的社交关系网络对当前的评论行为有较大影响。

  5. Prediction and conformation by synthesis of two antigenic sites in human haemoglobin by extrapolation from the known antigenic structure of sperm-whale myoglobin.

    Science.gov (United States)

    Kazim, A L; Atassi, M Z

    1977-10-01

    The complete antigenic structure of sperm-whale myoglobin was previously determined in our laboratory. By structural analogy with myoglobin, two regions in human haemoglobin were predicted to comprise antigenic sites. One region was on the alpha-chain [alpha-(15-23)] and the other on the beta-chain [beta-(16-23)]. These two regions were synthesized, purified and characterized, and their immunochemistry was studied. Each peptide was able specifically to bind considerable amounts of haemoglobin antibodies. In a set of homologous proteins, barring any drastic conformational or electrostatic inductive effects exerted by the substitutions, and allowing for obstruction due to subunit interaction, the determination of the antigenic structure of one protein may serve as a useful starting model for the others.

  6. Prediction of Post-Closure Water Balance for Monolithic Soil Covers at Waste Disposal Sites in the Greater Accra Metropolitan Area of Ghana

    Directory of Open Access Journals (Sweden)

    Kodwo Beedu Keelson

    2014-04-01

    Full Text Available The Ghana Landfill Guidelines require the provision of a final cover system during landfill closure as a means of minimizing the harmful environmental effects of uncontrolled leachate discharges. However, this technical manual does not provide explicit guidance on the material types or configurations that would be suitable for the different climatic zones in Ghana. The aim of this study was to simulate and predict post-closure landfill cover water balance for waste disposal sites located in the Greater Accra Metropolitan Area using the USGS Thornthwaite monthly water balance computer program. Five different cover soil types were analyzed under using historical climatic data for the metropolis from 1980 to 2001. The maximum annual percolation and evapotranspiration rates for the native soil type were 337 mm and 974 mm respectively. Monthly percolation rates exhibited a seasonal pattern similar to the bimodal precipitation regime whereas monthly evapotranspiration did not. It was also observed that even though soils with a high clay content would be the most suitable option as landfill cover material in the Accra metropolis the maximum thickness of 600 mm recommended in the Ghana Landfill Guidelines do not seem to provide significant reduction in percolation rates into the buried waste mass when the annual rainfall exceeds 700 mm. The findings from this research should provide additional guidance to landfill managers on the specification of cover designs for waste disposal sites with similar climatic conditions.

  7. Genetic variants in microRNAs and microRNA target sites predict biochemical recurrence after radical prostatectomy in localized prostate cancer.

    Science.gov (United States)

    Huang, Shu-Pin; Lévesque, Eric; Guillemette, Chantal; Yu, Chia-Cheng; Huang, Chao-Yuan; Lin, Victor C; Chung, I-Che; Chen, Lih-Chyang; Laverdière, Isabelle; Lacombe, Louis; Fradet, Yves; Chang, Ta-Yuan; Lee, Hong-Zin; Juang, Shin-Hun; Bao, Bo-Ying

    2014-12-01

    Recent evidence indicates that microRNAs might participate in prostate cancer initiation, progression and treatment response. Germline variations in microRNAs might alter target gene expression and modify the efficacy of prostate cancer therapy. To determine whether genetic variants in microRNAs and microRNA target sites are associated with the risk of biochemical recurrence (BCR) after radical prostatectomy (RP). We retrospectively studied two independent cohorts composed of 320 Asian and 526 Caucasian men with pathologically organ-confined prostate cancer who had a median follow-up of 54.7 and 88.8 months after RP, respectively. Patients were systematically genotyped for 64 single-nucleotide polymorphisms (SNPs) in microRNAs and microRNA target sites, and their prognostic significance on BCR was assessed by Kaplan-Meier analysis and Cox regression model. After adjusting for known clinicopathologic risk factors, two SNPs (MIR605 rs2043556 and CDON rs3737336) remained associated with BCR. The numbers of risk alleles showed a cumulative effect on BCR [perallele hazard ratio (HR) 1.60, 95% confidence interval (CI) 1.16-2.21, p for trend = 0.005] in Asian cohort, and the risk was replicated in Caucasian cohort (HR 1.55, 95% CI 1.15-2.08, p for trend = 0.004) and in combined analysis (HR 1.57, 95% CI 1.26-1.96, p for trend microRNAs and microRNA target sites can be predictive biomarkers for BCR after RP.

  8. Exploring the predicted effect of social networking site use on perceived social capital and psychological well-being of Chinese international students in Japan.

    Science.gov (United States)

    Guo, Yu; Li, Yiwei; Ito, Naoya

    2014-01-01

    This study investigated how social networking sites (SNSs) use by Chinese international students in Japan influenced their perceived social capital and psychological well-being. In addition, it examined how, as sojourners, Chinese international students' perceived acculturative stress varied. Data were collected from 142 Chinese international students. The results indicated that the intensity of SNS use was unable to predict individuals' perceived social capital and psychological well-being. The effect of SNS use varied according to the functions it serves. Specifically, SNS use for social and informational functions (SIF) increased individuals' levels of perceived bridging social capital and perceived life satisfaction, while SNS use for entertaining recreational functions (ERF) was unable to predict perceived social capital but increased individuals' levels of loneliness. It was also found that, in the intercultural environment, Chinese international students' levels of perceived acculturative stress were decreased by their perceived bonding social capital and increased by their perceived loneliness but had no relationship with their SNS use. Findings of the study suggest that individuals using SNSs to stay informed and connected will benefit with regard to their social network building and psychological well-being.

  9. Clinical and economic burden of surgical site infection (SSI) and predicted financial consequences of elimination of SSI from an English hospital.

    Science.gov (United States)

    Jenks, P J; Laurent, M; McQuarry, S; Watkins, R

    2014-01-01

    Although surgical site infections (SSIs) are known to be associated with increased length of stay (LOS) and additional cost, their impact on the profitability of surgical procedures is unknown. To determine the clinical and economic burden of SSI over a two-year period and to predict the financial consequences of their elimination. SSI surveillance and Patient Level Information and Costing System (PLICS) datasets for patients who underwent major surgical procedures at Plymouth Hospitals NHS Trust between April 2010 and March 2012 were consolidated. The main outcome measures were the attributable postoperative length of stay (LOS), cost, and impact on the margin differential (profitability) of SSI. A secondary outcome was the predicted financial consequence of eliminating all SSIs. The median additional LOS attributable to SSI was 10 days [95% confidence interval (CI): 7-13 days] and a total of 4694 bed-days were lost over the two-year period. The median additional cost attributable to SSI was £5,239 (95% CI: 4,622-6,719) and the aggregate extra cost over the study period was £2,491,424. After calculating the opportunity cost of eliminating all SSIs that had occurred in the two-year period, the combined overall predicted financial benefit of doing so would have been only £694,007. For seven surgical categories, the hospital would have been financially worse off if it had successfully eliminated all SSIs. SSI causes significant clinical and economic burden. Nevertheless the current system of reimbursement provided a financial disincentive to their reduction. Copyright © 2013 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.

  10. Rufus Choate: A Unique Orator.

    Science.gov (United States)

    Markham, Reed

    Rufus Choate, a Massachusetts lawyer and orator, has been described as a "unique and romantic phenomenon" in America's history. Born in 1799 in Essex, Massachusetts, Choate graduated from Dartmouth College and attended Harvard Law School. Choate's goal was to be the top in his profession. Daniel Webster was Choate's hero. Choate became well…

  11. Uniqueness of PL Minimal Surfaces

    Institute of Scientific and Technical Information of China (English)

    Yi NI

    2007-01-01

    Using a standard fact in hyperbolic geometry, we give a simple proof of the uniqueness of PL minimal surfaces, thus filling in a gap in the original proof of Jaco and Rubinstein. Moreover, in order to clarify some ambiguity, we sharpen the definition of PL minimal surfaces, and prove a technical lemma on the Plateau problem in the hyperbolic space.

  12. On the Nagumo uniqueness theorem

    OpenAIRE

    Octavian G. Mustafa; O'Regan, Donal

    2011-01-01

    By a convenient reparametrisation of the integral curves of a nonlinear ordinary differential equation (ODE), we are able to improve the conclusions of the recent contribution [A. Constantin, Proc. Japan Acad. {\\bf 86(A)} (2010), 41--44]. In this way, we establish a flexible uniqueness criterion for ODEs without Lipschitz-like nonlinearities.

  13. The Lasso Problem and Uniqueness

    CERN Document Server

    Tibshirani, Ryan J

    2012-01-01

    The lasso is a popular tool for sparse linear regression, especially for problems in which the number of variables p exceeds the number of observations n. But when p>n, the lasso criterion is not strictly convex, and hence it may not have a unique minimum. An important question is: when is the lasso solution well-defined (unique)? We review results from the literature, which show that if the predictor variables are drawn from a continuous probability distribution, then there is a unique lasso solution with probability one, regardless of the sizes of n and p. We also show that this result extends easily to $\\ell_1$ penalized minimization problems over a wide range of loss functions. A second important question is: how can we deal with the case of non-uniqueness in lasso solutions? In light of the aforementioned result, this case really only arises when some of the predictor variables are discrete, or when some post-processing has been performed on continuous predictor measurements. Though we certainly cannot c...

  14. A new method for predicting the subcellular localization of eukaryotic proteins with both single and multiple sites: Euk-mPLoc 2.0.

    Directory of Open Access Journals (Sweden)

    Kuo-Chen Chou

    Full Text Available Information of subcellular locations of proteins is important for in-depth studies of cell biology. It is very useful for proteomics, system biology and drug development as well. However, most existing methods for predicting protein subcellular location can only cover 5 to 12 location sites. Also, they are limited to deal with single-location proteins and hence failed to work for multiplex proteins, which can simultaneously exist at, or move between, two or more location sites. Actually, multiplex proteins of this kind usually posses some important biological functions worthy of our special notice. A new predictor called "Euk-mPLoc 2.0" is developed by hybridizing the gene ontology information, functional domain information, and sequential evolutionary information through three different modes of pseudo amino acid composition. It can be used to identify eukaryotic proteins among the following 22 locations: (1 acrosome, (2 cell wall, (3 centriole, (4 chloroplast, (5 cyanelle, (6 cytoplasm, (7 cytoskeleton, (8 endoplasmic reticulum, (9 endosome, (10 extracell, (11 Golgi apparatus, (12 hydrogenosome, (13 lysosome, (14 melanosome, (15 microsome (16 mitochondria, (17 nucleus, (18 peroxisome, (19 plasma membrane, (20 plastid, (21 spindle pole body, and (22 vacuole. Compared with the existing methods for predicting eukaryotic protein subcellular localization, the new predictor is much more powerful and flexible, particularly in dealing with proteins with multiple locations and proteins without available accession numbers. For a newly-constructed stringent benchmark dataset which contains both single- and multiple-location proteins and in which none of proteins has pairwise sequence identity to any other in a same location, the overall jackknife success rate achieved by Euk-mPLoc 2.0 is more than 24% higher than those by any of the existing predictors. As a user-friendly web-server, Euk-mPLoc 2.0 is freely accessible at http

  15. An experiment on Lowest Unique Integer Games

    Science.gov (United States)

    Yamada, Takashi; Hanaki, Nobuyuki

    2016-12-01

    We experimentally study Lowest Unique Integer Games (LUIGs) to determine if and how subjects self-organize into different behavioral classes. In a LUIG, N(≥ 3) players submit a positive integer up to M and the player choosing the smallest number not chosen by anyone else wins. LUIGs are simplified versions of real systems such as Lowest/Highest Unique Bid Auctions that have been attracting attention from scholars, yet experimental studies are scarce. Furthermore, LUIGs offer insights into choice patterns that can shed light on the alleviation of congestion problems. Here, we consider four LUIGs with N = { 3 , 4 } and M = { 3 , 4 } . We find that (a) choices made by more than 1/3 of subjects were not significantly different from what a symmetric mixed-strategy Nash equilibrium (MSE) predicts; however, (b) subjects who behaved significantly differently from what the MSE predicts won the game more frequently. What distinguishes subjects was their tendencies to change their choices following losses.

  16. Uniqueness theorems in linear elasticity

    CERN Document Server

    Knops, Robin John

    1971-01-01

    The classical result for uniqueness in elasticity theory is due to Kirchhoff. It states that the standard mixed boundary value problem for a homogeneous isotropic linear elastic material in equilibrium and occupying a bounded three-dimensional region of space possesses at most one solution in the classical sense, provided the Lame and shear moduli, A and J1 respectively, obey the inequalities (3 A + 2 J1) > 0 and J1>O. In linear elastodynamics the analogous result, due to Neumann, is that the initial-mixed boundary value problem possesses at most one solution provided the elastic moduli satisfy the same set of inequalities as in Kirchhoffs theorem. Most standard textbooks on the linear theory of elasticity mention only these two classical criteria for uniqueness and neglect altogether the abundant literature which has appeared since the original publications of Kirchhoff. To remedy this deficiency it seems appropriate to attempt a coherent description ofthe various contributions made to the study of uniquenes...

  17. The core and unique proteins of haloarchaea

    Directory of Open Access Journals (Sweden)

    Capes Melinda D

    2012-01-01

    Full Text Available Abstract Background Since the first genome of a halophilic archaeon was sequenced in 2000, biologists have been advancing the understanding of genomic characteristics that allow for survival in the harsh natural environments of these organisms. An increase in protein acidity and GC-bias in the genome have been implicated as factors in tolerance to extreme salinity, desiccation, and high solar radiation. However, few previous attempts have been made to identify novel genes that would permit survival in such extreme conditions. Results With the recent release of several new complete haloarchaeal genome sequences, we have conducted a comprehensive comparative genomic analysis focusing on the identification of unique haloarchaeal conserved proteins that likely play key roles in environmental adaptation. Using bioinformatic methods, we have clustered 31,312 predicted proteins from nine haloarchaeal genomes into 4,455 haloarchaeal orthologous groups (HOGs. We assigned likely functions by association with established COG and KOG databases in NCBI. After identifying homologs in four additional haloarchaeal genomes, we determined that there were 784 core haloarchaeal protein clusters (cHOGs, of which 83 clusters were found primarily in haloarchaea. Further analysis found that 55 clusters were truly unique (tucHOGs to haloarchaea and qualify as signature proteins while 28 were nearly unique (nucHOGs, the vast majority of which were coded for on the haloarchaeal chromosomes. Of the signature proteins, only one example with any predicted function, Ral, involved in desiccation/radiation tolerance in Halobacterium sp. NRC-1, was identified. Among the core clusters, 33% was predicted to function in metabolism, 25% in information transfer and storage, 10% in cell processes and signaling, and 22% belong to poorly characterized or general function groups. Conclusion Our studies have established conserved groups of nearly 800 protein clusters present in all

  18. Uniqueness and Non-uniqueness in the Einstein Constraints

    CERN Document Server

    Pfeiffer, H P; Pfeiffer, Harald P.; York, James W.

    2005-01-01

    We examine numerically a sequence of free data for the conformal thin sandwich (CTS) equations representing non-linearly perturbed Minkowski spacetimes. We find only one solution for the standard (four) CTS equations; however, we find {\\em two} distinct solutions for the same free data when the lapse is determined by a fifth elliptic equation arising from specification of the time derivative of the mean curvature. For a given {\\em physical} (conformally scaled) amplitude of the perturbation, the solution for the physical data $g_{ij}, K_{ij}$ nevertheless appears to be unique.

  19. Ground motions recorded in Rome during the April 2009 L’Aquila seismic sequence: site response and comparison with ground‐motion predictions based on a global dataset

    Science.gov (United States)

    Caserta, Arrigo; Boore, David; Rovelli, Antonio; Govoni, Aladino; Marra, Fabrizio; Monica, Gieseppe Della; Boschi, Enzo

    2013-01-01

    The mainshock and moderate‐magnitude aftershocks of the 6 April 2009 M 6.3 L’Aquila seismic sequence, about 90 km northeast of Rome, provided the first earthquake ground‐motion recordings in the urban area of Rome. Before those recordings were obtained, the assessments of the seismic hazard in Rome were based on intensity observations and theoretical considerations. The L’Aquila recordings offer an unprecedented opportunity to calibrate the city response to central Apennine earthquakes—earthquakes that have been responsible for the largest damage to Rome in historical times. Using the data recorded in Rome in April 2009, we show that (1) published theoretical predictions of a 1 s resonance in the Tiber valley are confirmed by observations showing a significant amplitude increase in response spectra at that period, (2) the empirical soil‐transfer functions inferred from spectral ratios are satisfactorily fit through 1D models using the available geological, geophysical, and laboratory data, but local variability can be large for individual events, (3) response spectra for the motions recorded in Rome from the L’Aquila earthquakes are significantly amplified in the radial component at periods near 1 s, even at a firm site on volcanic rocks, and (4) short‐period response spectra are smaller than expected when compared to ground‐motion predictions from equations based on a global dataset, whereas the observed response spectra are higher than expected for periods near 1 s.

  20. Computed tomography evidence of fluid in the hernia sac predicts surgical site infection following mesh repair of acutely incarcerated ventral and groin hernias.

    Science.gov (United States)

    Loftus, Tyler J; Go, Kristina L; Jordan, Janeen R; Croft, Chasen A; Smith, R Stephen; Moore, Frederick A; Efron, Philip A; Mohr, Alicia M; Brakenridge, Scott C

    2017-07-01

    Mesh placement during repair of acutely incarcerated ventral and groin hernias is associated with high rates of surgical site infection (SSI). The utility of preoperative computed tomography (CT) in this setting is unclear. We hypothesized that CT evidence of bowel wall compromise would predict SSI while accounting for physiologic parameters. We performed a 4-year retrospective cohort analysis of 50 consecutive patients who underwent mesh repair of acutely incarcerated ventral or groin hernias. We analyzed chronic disease burden, acute illness severity, CT findings, operative management, and herniorrhaphy-specific outcomes within 180 days. The primary outcome was SSI by the Centers for Disease Control and Prevention criteria. Multiple logistic regression was performed to identify independent predictors of SSI. Eighty-four percent of all patients were American Society of Anesthesiologists class III or IV, 28% were active smokers, and mean body mass index (BMI) was 35 kg/m. Fifty-four percent had ventral hernias, 40% had inguinal hernias, and 6% had femoral or combined inguinal/ femoral hernias. Seventy percent of preoperative CT scans had features suggesting bowel compromise, abdominal free fluid, or fluid in the hernia sac. Surgical site infection occurred in 32% of all patients (8% superficial, 24% deep or organ/space). The strongest predictors of SSI were CT evidence of fluid in the hernia sac (odds ratio [OR], 8.3; 95% confidence interval [CI], 1.7-41), initial heart rate 90 beats/min or greater (OR, 6.3; 95% CI, 1.1-34), and BMI 35 kg/m or greater (OR, 5.8; 95% CI, 1.2-28). Surgical site infection rates were significantly higher among patients who had CT evidence of fluid in the hernia sac (56% vs. 19%, p = 0.012). More than half of all patients with CT scan evidence of fluid in the hernia sac developed an SSI. Computed tomography evidence of fluid in the hernia sac was the strongest predictor of SSI, followed by heart rate and BMI. Together, these parameters

  1. Executive Functioning Skills Uniquely Predict Chinese Word Reading

    Science.gov (United States)

    Chung, Kevin K. H.; McBride-Chang, Catherine

    2011-01-01

    Eighty-five Hong Kong Chinese children were tested across both the 2nd and 3rd years of kindergarten (ages 4-5 years) on tasks of inhibitory control, working memory, vocabulary knowledge, phonological awareness, morphological awareness, and word reading. With age, vocabulary knowledge, and metalinguistic skills statistically controlled, the…

  2. Predicting distinct organization of transcription factor binding sites on the promoter regions: a new genome-based approach to expand human embryonic stem cell regulatory network.

    Science.gov (United States)

    Hosseinpour, Batool; Bakhtiarizadeh, Mohammad Reza; Khosravi, Pegah; Ebrahimie, Esmaeil

    2013-12-01

    Self-proliferation and differentiation into distinct cell types have been made stem cell as a promising target for regenerative medicine. Several key genes can regulate self-renewal and pluripotency of embryonic stem cells (hESCs). They work together and build a transcriptional hierarchy. Coexpression and coregulation of genes control by common regulatory elements on the promoter regions. Consequently, distinct organization and combination of transcription factor binding sites (TFBSs modules) on promoter regions, in view of order and distance, lead to a common specific expression pattern within a set of genes. To gain insights into transcriptional regulation of hESCs, we selected promoter regions of eleven common expressed hESC genes including SOX2, LIN28, STAT3, NANOG, LEFTB, TDGF1, POU5F1, FOXD3, TERF1, REX1 and GDF3 to predict activating regulatory modules on promoters and discover key corresponding transcription factors. Then, promoter regions in human genome were explored for modules and 328 genes containing the same modules were detected. Using microarray data, we verified that 102 of 328 genes commonly upregulate in hESCs. Also, using output data of DNA-protein interaction assays, we found that 42 of all predicted genes are targets of SOX2, NANOG and POU5F1. Additionally, a protein interaction network of hESC genes was constructed based on biological processes, and interestingly, 126 downregulated genes along with upregulated ones identified by promoter analysis were predicted in the network. Based on the results, we suggest that the identified genes, coregulating with common hESC genes, represent a novel approach for gene discovery based on whole genome promoter analysis irrespective of gene expression. Altogether, promoter profiling can be used to expand hESC transcriptional regulatory circuitry by analysis of shared functional sequences between genes. This approach provides a clear image on underlying regulatory mechanism of gene expression profile and

  3. Protein–Protein interaction site prediction in Homo sapiens and E. coli using an interaction-affinity based membership function in fuzzy SVM

    Indian Academy of Sciences (India)

    Brijesh Kumar Sriwastava; Subhadip Basu; Ujjwal Maulik

    2015-10-01

    Protein–protein interaction (PPI) site prediction aids to ascertain the interface residues that participate in interaction processes. Fuzzy support vector machine (F-SVM) is proposed as an effective method to solve this problem, and we have shown that the performance of the classical SVM can be enhanced with the help of an interaction-affinity based fuzzy membership function. The performances of both SVM and F-SVM on the PPI databases of the Homo sapiens and E. coli organisms are evaluated and estimated the statistical significance of the developed method over classical SVM and other fuzzy membership-based SVM methods available in the literature. Our membership function uses the residue-level interaction affinity scores for each pair of positive and negative sequence fragments. The average AUC scores in the 10-fold cross-validation experiments are measured as 79.94% and 80.48% for the Homo sapiens and E. coli organisms respectively. On the independent test datasets, AUC scores are obtained as 76.59% and 80.17% respectively for the two organisms. In almost all cases, the developed F-SVM method improves the performances obtained by the corresponding classical SVM and the other classifiers, available in the literature.

  4. Protein-protein interaction site prediction in Homo sapiens and E. coli using an interaction-affinity based membership function in fuzzy SVM.

    Science.gov (United States)

    Sriwastava, Brijesh Kumar; Basu, Subhadip; Maulik, Ujjwal

    2015-10-01

    Protein-protein interaction (PPI) site prediction aids to ascertain the interface residues that participate in interaction processes. Fuzzy support vector machine (F-SVM) is proposed as an effective method to solve this problem, and we have shown that the performance of the classical SVM can be enhanced with the help of an interaction-affinity based fuzzy membership function. The performances of both SVM and F-SVM on the PPI databases of the Homo sapiens and E. coli organisms are evaluated and estimated the statistical significance of the developed method over classical SVM and other fuzzy membership-based SVM methods available in the literature. Our membership function uses the residue-level interaction affinity scores for each pair of positive and negative sequence fragments. The average AUC scores in the 10-fold cross-validation experiments are measured as 79.94% and 80.48% for the Homo sapiens and E. coli organisms respectively. On the independent test datasets, AUC scores are obtained as 76.59% and 80.17% respectively for the two organisms. In almost all cases, the developed F-SVM method improves the performances obtained by the corresponding classical SVM and the other classifiers, available in the literature.

  5. Lithium nephropathy: unique sonographic findings.

    Science.gov (United States)

    Di Salvo, Donald N; Park, Joseph; Laing, Faye C

    2012-04-01

    This case series describes a unique sonographic appearance consisting of numerous microcysts and punctate echogenic foci seen on renal sonograms of 10 adult patients receiving chronic lithium therapy. Clinically, chronic renal insufficiency was present in 6 and nephrogenic diabetes insipidus in 2. Sonography showed numerous microcysts and punctate echogenic foci. Computed tomography in 5 patients confirmed microcysts and microcalcifications, which were fewer in number than on sonography. Magnetic resonance imaging in 2 patients confirmed microcysts in each case. Renal biopsy in 1 patient showed chronic interstitial nephritis, microcysts, and tubular dilatation. The diagnosis of lithium nephropathy should be considered when sonography shows these findings.

  6. Mucormycosis in India: unique features.

    Science.gov (United States)

    Chakrabarti, Arunaloke; Singh, Rachna

    2014-12-01

    Mucormycosis remains a devastating invasive fungal infection, with high mortality rates even after active management. The disease is being reported at an alarming frequency over the past decades from India. Indian mucormycosis has certain unique features. Rhino-orbito-cerebral presentation associated with uncontrolled diabetes is the predominant characteristic. Isolated renal mucormycosis has emerged as a new clinical entity. Apophysomyces elegans and Rhizopus homothallicus are emerging species in this region and uncommon agents such as Mucor irregularis and Thamnostylum lucknowense are also being reported. This review focuses on these distinct features of mucormycosis observed in India.

  7. UNIQUE ORAL DRUG DELIVERY SYSTEM

    Institute of Scientific and Technical Information of China (English)

    Raphael M. Ottenbrite; ZHAO Ruifeng; Sam Milstein

    1995-01-01

    An oral drug delivery system using proteinoid microspheres is discussed with respect to its unique dependence on pH. It has been found that certain drugs such as insulin and heparin can be encapsulated in proteinoid spheres at stomach pH's (1-3). These spheres also dissemble at intestinal pH's (6-7) releasing the drug for absorption. Using this technique low molecular weight heparin and human growth hormone have been orally delivered successfully to several animal species. Future work has been proposed to study the interaction and binding of the specific drugs with synthesized oligopeptides.

  8. Analysis of unique beta transitions

    DEFF Research Database (Denmark)

    Eman, B.; Krmpotic, F.; Tadic, D;

    1967-01-01

    The Heidelberg group measurements [For abstr. see Phys. Rev. Nucl. Sci. Vol. 15 (1965)] of unique forbidden transitions have been analysed. It has been found that experimental shape factors can be reproduced only with the induced pseudoscalar form factor d ...-non-conserving tensor form factor b > 0. In the former case they contradict Daniel's results [See abstr. 1966A10720] for 0- rarr 0+ transitions, whereas in the latter they are in disagreement with other known analyses of mu-meson capture, allowed and forbidden transitions. The conclusion appears to be independent...

  9. New Solutions of Translation Initiation Site Prediction for Prokaryotic Genomes%原核基因翻译起始位点预测的新方法

    Institute of Scientific and Technical Information of China (English)

    胡钢清; 刘永初; 郑晓斌; 杨一帆; 余振苏; 朱怀球

    2008-01-01

    翻译起始位点(TIS,即基因5′端)的精确定位是原核生物基因预测的一个关键问题,而基因组GC含量和翻译起始机制的多样性是影响当前TIS预测水平的重要因素.结合基因组结构的复杂信息(包括GC含量、TIS邻近序列及上游调控信号、序列编码潜能、操纵子结构等),发展刻画翻译起始机制的数学统计模型,据此设计TIS预测的新算法MED-StartPlus.并将MED-StartPlus与同类方法RBSfinder、GS-Finder、MED-Start、TiCo和Hon-yaku等进行系统地比较和评价.测试针对两种数据集进行:当前14个已知的TIS被确认的基因数据集,以及300个物种中功能已知的基因数据集.测试结果表明,MED-StartPlus的预测精度在总体上超过同类方法.尤其是对高GC含量基因组以及具有复杂翻译起始机制的基因组,MED-StartPlus具有明显的优势.%Accurate prediction of the translation initiation site (TIS) is an important issue for prokaryotic genome annotation. However, it is still a challenge for the existing methods to predict the TIS in the genomes over a wide variety of GC content. Besides, the existing methods have not yet undergone a comprehensive evaluation, leaving prediction reliability as a largely open problem. A new algorithm MED-StartPlus, a tool that predicts TIS in prokaryotic genomes with a wide variety of GC content was presented. It makes several efforts to model the nucleotide composition bias, the regulatory motifs upstream of the TIS, the sequence patterns around the TIS, and the operon structure. Tests on hundreds of reliable data sets, with TISs confirmed by experiments or having annotated functions, show that the new method achieves a totally high accuracy of TIS prediction. Compared with existing TIS predictors, the method reports a totally higher performance, especially for genomes that are GC-rich or have complex initiation mechanisms. The potential application of the method to improve the TIS annotation

  10. Injectable hydrogels as unique biomedical materials.

    Science.gov (United States)

    Yu, Lin; Ding, Jiandong

    2008-08-01

    A concentrated fish soup could be gelled in the winter and re-solled upon heating. In contrast, some synthetic copolymers exhibit an inverse sol-gel transition with spontaneous physical gelation upon heating instead of cooling. If the transition in water takes place below the body temperature and the chemicals are biocompatible and biodegradable, such gelling behavior makes the associated physical gels injectable biomaterials with unique applications in drug delivery and tissue engineering etc. Various therapeutic agents or cells can be entrapped in situ and form a depot merely by a syringe injection of their aqueous solutions at target sites with minimal invasiveness and pain. This tutorial review summarizes and comments on this soft matter, especially thermogelling poly(ethylene glycol)-(biodegradable polyester) block copolymers. The main types of injectable hydrogels are also briefly introduced, including both physical gels and chemical gels.

  11. Astronomy Outreach for Large and Unique Audiences

    Science.gov (United States)

    Lubowich, D.; Sparks, R. T.; Pompea, S. M.; Kendall, J. S.; Dugan, C.

    2013-04-01

    In this session, we discuss different approaches to reaching large audiences. In addition to star parties and astronomy events, the audiences for some of the events include music concerts or festivals, sick children and their families, minority communities, American Indian reservations, and tourist sites such as the National Mall. The goal is to bring science directly to the public—to people who attend astronomy events and to people who do not come to star parties, science museums, or science festivals. These programs allow the entire community to participate in astronomy activities to enhance the public appreciation of science. These programs attract large enthusiastic crowds often with young children participating in these family learning experiences. The public will become more informed, educated, and inspired about astronomy and will also be provided with information that will allow them to continue to learn after this outreach activity. Large and unique audiences often have common problems, and their solutions and the lessons learned will be presented. Interaction with the participants in this session will provide important community feedback used to improve astronomy outreach for large and unique audiences. New ways to expand astronomy outreach to new large audiences will be discussed.

  12. Analysis of K-net and Kik-net data: implications for ground motion prediction - acceleration time histories, response spectra and nonlinear site response; Analyse des donnees accelerometriques de K-net et Kik-net: implications pour la prediction du mouvement sismique - accelerogrammes et spectres de reponse - et la prise en compte des effets de site non-lineaire

    Energy Technology Data Exchange (ETDEWEB)

    Pousse, G

    2005-10-15

    This thesis intends to characterize ground motion during earthquake. This work is based on two Japanese networks. It deals with databases of shallow events, depth less than 25 km, with magnitude between 4.0 and 7.3. The analysis of K-net allows to compute a spectral ground motion prediction equation and to review the shape of the Eurocode 8 design spectra. We show the larger amplification at short period for Japanese data and bring in light the soil amplification that takes place at large period. In addition, we develop a new empirical model for simulating synthetic stochastic nonstationary acceleration time histories. By specifying magnitude, distance and site effect, this model allows to produce many time histories, that a seismic event is liable to produce at the place of interest. Furthermore, the study of near-field borehole records of the Kik-net allows to explore the validity domain of predictive equations and to explain what occurs by extrapolating ground motion predictions. Finally, we show that nonlinearity reduces the dispersion of ground motion at the surface. (author)

  13. Organizing the spatially and temporally unique hydrosphere

    Science.gov (United States)

    Berghuijs, Wouter

    2016-04-01

    Growing anthropogenic activity is quickly changing the hydrosphere. Panta Rhei calls for improved understanding of changing hydrosphere dynamics in their connection with human systems. I argue that progress within the Panta Rhei initiative is strongly limited by the absence of hydrological principles that help to organise our spatially and temporally unique hydrosphere; without guiding principles (e.g. classification systems) hydrology will continue to be a case study dominated science that will have a hard time to efficiently improve understanding, estimation and prediction of human affected systems. Exposing such organising principles should not be considered as a step backwards into the recent PUB decade. Instead, it should be regarded as an exciting scientific challenge that is becoming increasingly relevant now the hydrosphere is quickly changing.

  14. Hue discrimination, unique hues and naming.

    Science.gov (United States)

    Bachy, Romain; Dias, Jérôme; Alleysson, David; Bonnardel, Valérie

    2012-02-01

    The hue discrimination curve (HDC) that characterizes performances over the entire hue circle was determined by using sinusoidally modulated spectral power distributions of 1.5 c/300 nm with fixed amplitude and twelve reference phases. To investigate relationship between hue discrimination and appearance, observers further performed a free color naming and unique hue tasks. The HDC consistently displayed two minima and two maxima; discrimination is optimal at the yellow/orange and blue/magenta boundaries and pessimal in green and in the extra-spectral magenta colors. A linear model based on Müller zone theory correctly predicts a periodical profile but with a phase-opponency (minima/maxima at 180° apart) which is inconsistent with the empirical HDC's profile.

  15. Advanced Primary Epithelial Ovarian and Peritoneal Carcinoma-Does Diagnostic Accuracy of Preoperative CT Scan for Detection of Peritoneal Metastatic Sites Reflect into Prediction of Suboptimal Debulking? A Prospective Study.

    Science.gov (United States)

    Bagul, Kiran; Vijaykumar, D K; Rajanbabu, Anupama; Antony, Mitchelle Aline; Ranganathan, Venkatesan

    2017-06-01

    Ovarian cancer is the seventh most common cancer in females worldwide. Optimal debulking is the standard treatment but possible only in 30-85% of advanced stages. Knowing exactly the disease extent preoperatively may predict suboptimal debulking. We analyzed diagnostic accuracy of preoperative CT scan in disease mapping and prediction of suboptimal debulking in a prospective observational study from March 2013 to May 2015 in a tertiary hospital. Adults below the age of 75 years with ECOG PS-0, 1, 2, clinically/radiologically newly diagnosed stage IIIc epithelial ovarian (EOC), and primary peritoneal carcinoma (PPC) were included. Neoadjuvant chemotherapy recipients were excluded. Preoperative multidetector CT (MDCT) scan showing deposits at 19 predetermined abdominopelvic sites were compared with the same sites seen at laparotomy and corresponding accuracies of CT scan calculated. Primary debulking surgery was done to achieve debulking to nil or less than 1-cm residual disease. Stepwise logistic regression models were used to determine the frequent suboptimal debulking sites and the predictive performance of the clinical and CT scan findings. A total of 36 patients were enrolled. The optimal debulking rate was 50%. The CT scan could detect the disease-bearing sites with overall sensitivity of 68.29%, specificity of 89%, accuracy of 78.07%, and positive and negative predictive values of 99 and 50.1%, respectively. Upon multivariate analysis, bowel mesentery (p 0.011) and omental extension (p 0.025) were associated with suboptimal debulking. CT scan accuracy at these sites (predictive performance) was 86.1%. We identified small bowel mesentery and omental extension (to spleen/stomach/colon) as sites associated with suboptimal debulking. MDCT accurately depicts peritoneal metastases, although sensitivity is reduced in certain areas of significance for optimal debulking. Further validation with more number of patients is warranted.

  16. Unique Features of Mobile Commerce

    Institute of Scientific and Technical Information of China (English)

    DING Xiaojun; IIJIMA Junichi; HO Sho

    2004-01-01

    While the market potentials and impacts of web-based e-commerce are still in the ascendant, the advances in wireless technologies and mobile networks have brought about a new business opportunity and research attention, what is termed mobile commerce. Commonly, mobile commerce is considered to be another new application of existing web-based e-commerce onto wireless networks, but as an independent business area, mobile commerce has its own advantages and challenges as opposed to traditional e-commerce applications. This paper focuses on exploring the unique features of mobile commerce as. Compared with traditional e-commerce. Also, there are still some limitations arisen in m-commerce in contrast to web-based e-commerce. Finally, current state of mobile commerce in Japan is presented in brief, with an introduction of several cases involving mobile commerce applications in today 's marketplace.

  17. Unique features of space reactors

    Science.gov (United States)

    Buden, David

    Space reactors are designed to meet a unique set of requirements; they must be sufficiently compact to be launched in a rocket to their operational location, operate for many years without maintenance and servicing, operate in extreme environments, and reject heat by radiation to space. To meet these restrictions, operating temperatures are much greater than in terrestrial power plants, and the reactors tend to have a fast neutron spectrum. Currently, a new generation of space reactor power plants is being developed. The major effort is in the SP-100 program, where the power plant is being designed for seven years of full power, and no maintenance operation at a reactor outlet operating temperature of 1350 K.

  18. The Evolution of Human Uniqueness.

    Science.gov (United States)

    Boyd, Robert

    2017-01-09

    The human species is an outlier in the natural world. Two million years ago our ancestors were a slightly odd apes. Now we occupy the largest ecological and geographical range of any species, have larger biomass, and process more energy. Usually, this transformation is explained in terms of cognitive ability-people are just smarter than all the rest. In this paper I argue that culture, our ability to learn from each other, and cooperation, our ability to make common cause with large groups of unrelated individuals are the real roots of human uniqueness, and sketch an evolutionary account of how these crucial abilities co-evolved with each other and with other features of our life histories.

  19. Water Quality, Cyanobacteria, and Environmental Factors and Their Relations to Microcystin Concentrations for Use in Predictive Models at Ohio Lake Erie and Inland Lake Recreational Sites, 2013-14

    Science.gov (United States)

    Francy, Donna S.; Graham, Jennifer L.; Stelzer, Erin A.; Ecker, Christopher D.; Brady, Amie M G.; Pam Struffolino,; Loftin, Keith A.

    2015-11-06

    Harmful cyanobacterial “algal” blooms (cyanoHABs) and associated toxins, such as microcystin, are a major water-quality issue for Lake Erie and inland lakes in Ohio. Predicting when and where a bloom may occur is important to protect the public that uses and consumes a water resource; however, predictions are complicated and likely site specific because of the many factors affecting toxin production. Monitoring for a variety of environmental and water-quality factors, for concentrations of cyanobacteria by molecular methods, and for algal pigments such as chlorophyll and phycocyanin by using optical sensors may provide data that can be used to predict the occurrence of cyanoHABs.

  20. Does perceived risk predict breast cancer screening use? Findings from a prospective cohort study of female relatives from the Ontario site of the Breast Cancer Family Registry

    Science.gov (United States)

    Walker, Meghan J.; Mirea, Lucia; Glendon, Gord; Ritvo, Paul; Andrulis, Irene L.; Knight, Julia A.; Chiarelli, Anna M.

    2014-01-01

    Summary Objective While the relationship between perceived risk and adherence to breast cancer screening guidelines has been studied extensively, the majority of studies are cross-sectional. We prospectively examined this relationship among women with familial risk. Materials and Methods The prospective association between perceived risk and screening behaviors was examined in 913 women aged 25 to 72, with varying levels of familial breast cancer risk from the Ontario site of the Breast Cancer Family Registry. Associations between perceived lifetime breast cancer risk and subsequent use of screening mammography, clinical breast examination (CBE) and genetic testing were assessed using logistic regression. Results Overall, perceived risk did not predict subsequent use of screening mammography, CBE or genetic testing. Women at moderate/high familial risk who perceived their risk as greater than 50% were significantly less likely to have a CBE (odds ratio (OR) = 0.52, 95% confidence interval (CI): 0.30–0.91, p=0.04), and less likely to have a mammogram (OR = 0.70, 95% CI: 0.40–1.20, p=0.70) or genetic test (OR = 0.61, 95% CI: 0.34–1.10, p=0.09) compared to women who perceive their risk as 50%. In contrast, women at low familial risk who perceived their risk as greater than 50% were non-significantly more likely to have a mammogram (OR = 1.13, 95% CI: 0.59–2.16, p=0.78), CBE (OR = 1.11, 95% CI: 0.63–1.95, p=0.74) or genetic test (OR = 1.29, 95% CI: 0.50– 3.33, p=0.35) compared to women who perceive their risk as 50%. Conclusion Perceived risk did not significantly predict subsequent screening use overall, however this relationship may be moderated by level of familial risk. Results may inform risk education and management strategies among women with varying levels of familial breast cancer risk. PMID:24821458

  1. Beliefs about optimal age and screening frequency predict breast screening adherence in a prospective study of female relatives from the Ontario Site of the Breast Cancer Family Registry

    Directory of Open Access Journals (Sweden)

    Ritvo Paul

    2012-07-01

    Full Text Available Abstract Background Although few studies have linked cognitive variables with adherence to mammography screening in women with family histories of breast and/or ovarian cancer, research studies suggest cognitive phenomena can be powerful adherence predictors. Methods This prospective study included 858 women aged 30 to 71 years from the Ontario site of the Breast Cancer Family Registry with at least one first-degree relative diagnosed with breast and/or ovarian cancer. Data on beliefs about breast cancer screening and use of mammography were obtained from annual telephone interviews spanning three consecutive years. Self-reported mammogram dates were confirmed with medical imaging reports. Associations between beliefs about breast cancer screening and adherence with annual mammography were estimated using polytomous logistic regression models corrected for familial correlation. Models compared adherers (N = 329 with late-screeners (N = 382 and never-screeners (N = 147. Results Women who believed mammography screening should occur annually were more likely to adhere to annual screening recommendations than women who believed it should happen less often (OR: 5.02; 95% CI: 2.97-8.49 for adherers versus late-screeners; OR: 6.82; 95% CI: 3.29-14.16 for adherers versus never-screeners. Women who believed mammography screening should start at or before age 50 (rather than after (OR: 9.72; 95% CI: 3.26-29.02 were significantly more likely to adhere when compared with never-screeners. Conclusions Study results suggest that women with a family history of breast cancer should be strongly communicated recommendations about initial age of screening and screening intervals as related beliefs significantly predict adequate adherence.

  2. Glycopeptide-preferring polypeptide GalNAc transferase 10 (ppGalNAc T10), involved in mucin-type O-glycosylation, has a unique GalNAc-O-Ser/Thr-binding site in its catalytic domain not found in ppGalNAc T1 or T2.

    Science.gov (United States)

    Perrine, Cynthia L; Ganguli, Anjali; Wu, Peng; Bertozzi, Carolyn R; Fritz, Timothy A; Raman, Jayalakshmi; Tabak, Lawrence A; Gerken, Thomas A

    2009-07-24

    Mucin-type O-gly co sy la tion is initiated by a large family of UDP-GalNAc:polypeptide alpha-N-acetylgalactosaminyltransferases (ppGalNAc Ts) that transfer GalNAc from UDP-GalNAc to the Ser and Thr residues of polypeptide acceptors. Some members of the family prefer previously gly co sylated peptides (ppGalNAc T7 and T10), whereas others are inhibited by neighboring gly co sy la tion (ppGalNAc T1 and T2). Characterizing their peptide and glycopeptide substrate specificity is critical for understanding the biological role and significance of each isoform. Utilizing a series of random peptide and glycopeptide substrates, we have obtained the peptide and glycopeptide specificities of ppGalNAc T10 for comparison with ppGalNAc T1 and T2. For the glycopeptide substrates, ppGalNAc T10 exhibited a single large preference for Ser/Thr-O-GalNAc at the +1 (C-terminal) position relative to the Ser or Thr acceptor site. ppGalNAc T1 and T2 revealed no significant enhancements suggesting Ser/Thr-O-GalNAc was inhibitory at most positions for these isoforms. Against random peptide substrates, ppGalNAc T10 revealed no significant hydrophobic or hydrophilic residue enhancements, in contrast to what has been reported previously for ppGalNAc T1 and T2. Our results reveal that these transferases have unique peptide and glycopeptide preferences demonstrating their substrate diversity and their likely roles ranging from initiating transferases to filling-in transferases.

  3. Prediction of the flooding process at the Ronneburg site - results of an integrated approach; Flutungsprognose am Standort Ronneburg - Ergebnisse eines integrierten Modellansatzes

    Energy Technology Data Exchange (ETDEWEB)

    Paul, M.; Saenger, H.-J.; Snagowski, S. [Wismut GmbH, Chemnitz (Germany); Maerten, H. [UIT Dresden (Germany); Eckart, M. [Geocontrol Gera (Germany)

    1998-12-31

    The flooding process of the Ronneburg uranium mine (WISMUT) was initiated at the turn of the year 1997 to 1998. In order to prepare the flooding process and to derive and optimize technological measures an integrated modelling approach was chosen which includes several coupled modules. The most important issues to be answered are: (1) prediction of the flooding time (2) prediction of the groundwater level at the post-flooding stage, assessment of amount, location and quality of flooding waters entering the receiving streams at the final stage (3) water quality prediction within the mine during the flooding process (4) definition of technological measures and assessment of their efficiency A box model which includes the three-dimensional distribution of the cavity volume in the mine represents the model core. The model considers the various types of dewatered cavity volumes for each mine level / mining field and the degree of vertical and horizontal connection between the mining fields. Different types of open mine space as well as the dewatered geological pore and joint volume are considered taking into account the contour of the depression cone prior to flooding and the characteristics of the different rock types. Based on the mine water balance and the flooding technology the model predicts the rise of the water table over time during the flooding process for each mine field separately. In order to predict the mine water quality and the efficiency of in-situ water treatment the box model was linked to a geochemical model (PHREEQC). A three-dimensional flow model is used to evaluate the post-flooding situation at the Ronneburg site. This model is coupled to the box model. The modelling results of various flooding scenarios show that a prediction of the post-flooding geohydraulic situation is possible despite of uncertainties concerning the input parameters which still exist. The post-flooding water table in the central part of the Ronneburg mine will be 270 m

  4. Investigation of unique hue setting changes with ageing

    Institute of Scientific and Technical Information of China (English)

    Chenyang Fu; Kaida Xiao; Dimosthenis Karatzas; Sophie Wuerger

    2011-01-01

    Clromatic sensitivity along the protan, deutan, and tritan lines and the loci of the unique hues (red, green,yellow, blue) for a very large sample (n = 185) of colour-normal observers ranging from 18 to 75 years of age are assessed. Visual judgments are obtained under normal viewing conditions using colour patches on self-luminous display under controlled adaptation conditions. Trivector discrimination thresholds show an increase as a function of age along the protan, deutan, and tritan axes, with the largest increase present along the tritan line, less pronounced shifts in unique hue settings are also observed. Based on the chromatic (protan, deutan, tritan) thresholds and using scaled cone signals, we predict the unique hue changes with ageing. A dependency on age for unique red and unique yellow for predicted hue angle is found. We conclude that the chromatic sensitivity deteriorates significantly with age, whereas the appearance of unique hues is much less affected, remaining almost constant despite the known changes in the ocular media.%@@ Clromatic sensitivity along the protan, deutan, and tritan lines and the loci of the unique hues (red, green,yellow, blue) for a very large sample (n = 185) of colour-normal observers ranging from 18 to 75 years of age are assessed.Visual judgments are obtained under normal viewing conditions using colour patches on self-luminous display under controlled adaptation conditions.Trivector discrimination thresholds show an increase as a function of age along the protan, deutan, and tritan axes, with the largest increase present along the tritan line, less pronounced shifts in unique hue settings are also observed.

  5. UNIQUENESS ON ZERO PRESSURE GAS DYNAMICS

    Institute of Scientific and Technical Information of China (English)

    黄飞敏; 王振

    2001-01-01

    By introducing a new idea, the authors prove the uniqueness of weak solution of pressureless gases with the large initial data. In particular, uniqueness theorem is obtained in the same functional space as the existence theorem.

  6. On the uniqueness of supersymmetric attractors

    Directory of Open Access Journals (Sweden)

    Taniya Mandal

    2015-10-01

    Full Text Available In this paper we discuss the uniqueness of supersymmetric attractors in four-dimensional N=2 supergravity theories coupled to n vector multiplets. We prove that for a given charge configuration the supersymmetry preserving axion free attractors are unique. We generalise the analysis to axionic attractors and state the conditions for uniqueness explicitly. We consider the example of a two-parameter model and find all solutions to the supersymmetric attractor equations and discuss their uniqueness.

  7. 77 FR 69393 - Unique Device Identification System

    Science.gov (United States)

    2012-11-19

    ... HUMAN SERVICES Food and Drug Administration 21 CFR Part 801 RIN 0910-AG31 Unique Device Identification... unique device identification system as required by recent amendments to the Federal Food, Drug, and..., FDA published a proposed rule to establish a unique device identification system, as required by...

  8. On chromatic and flow polynomial unique graphs

    National Research Council Canada - National Science Library

    Duan, Yinghua; Wu, Haidong; Yu, Qinglin

    2008-01-01

    ... research on graphs uniquely determined by their chromatic polynomials and more recently on their Tutte polynomials, but rather spotty research on graphs uniquely determined by their flow polynomials or the combination of both chromatic and flow polynomials. This article is an initiation of investigation on graphs uniquely determin...

  9. Aespoe HRL - Geoscientific evaluation 1997/3. Results from pre-investigation and detailed site characterization. Comparison of predictions and observations. Geology and mechanical stability

    Energy Technology Data Exchange (ETDEWEB)

    Stanfors, R. [RS Consulting, Lund (Sweden); Olsson, Paer [Skanska AB Stockholm (Sweden); Stille, H. [Royal Inst. of Tech., Stockholm (Sweden)

    1997-05-01

    Prior to excavation of the laboratory in 1990 predictions were made for the excavation phase. The predictions concern five key issues: Geology, groundwater flow, groundwater chemistry, transport of solutes, and mechanical stability. Comparisons between predictions and observations were made during excavation in order to verify the reliability of the pre-investigations. This report presents a comparison between the geological and mechanical stability predictions and observations and an evaluation of data and investigation methods used for the 700-2874 m section of the tunnel. The report is specially highlighting the following conclusions: It is possible to localize major fracture zones during the pre-investigation at shallow (<200 m) depths; A number of minor fracture zones striking NNW-NNE were predicted to be hydraulically important and penetrate the southern area. A number of narrow fracture zone indications - 0.1-1 m wide - striking WNW-NE were mapped in the tunnel and pre-grouted sections confirm hydraulic conductors; It has not been possible to confirm the gently dipping zone EW-5, which was predicted as `possible`, with data from the tunnel; Predictions of the amount of different rock types were generally reliable as regards the major rocks, but the prediction of the distribution in space were poor as regards the minor rock types; The prediction of rock stress orientation corresponds well to the outcome; The prediction of rock quality for the tunnel, while applying the RMR-system, shows good correspondence to the observations made in the tunnel. 59 refs, 51 figs, 21 tabs.

  10. A spatial individual-based model predicting a great impact of copious sugar sources and resting sites on survival of Anopheles gambiae and malaria parasite transmission

    Science.gov (United States)

    Zhu, Lin; Qualls, Whitney A.; Marshall, John M; Arheart, Kris L.; DeAngelis, Don; McManus, John W.; Traore, Sekou F.; Doumbia, Seydou; Schlein, Yosef; Muller, Gunter C.; Beier, John C.

    2015-01-01

    BackgroundAgent-based modelling (ABM) has been used to simulate mosquito life cycles and to evaluate vector control applications. However, most models lack sugar-feeding and resting behaviours or are based on mathematical equations lacking individual level randomness and spatial components of mosquito life. Here, a spatial individual-based model (IBM) incorporating sugar-feeding and resting behaviours of the malaria vector Anopheles gambiae was developed to estimate the impact of environmental sugar sources and resting sites on survival and biting behaviour.MethodsA spatial IBM containing An. gambiae mosquitoes and humans, as well as the village environment of houses, sugar sources, resting sites and larval habitat sites was developed. Anopheles gambiae behaviour rules were attributed at each step of the IBM: resting, host seeking, sugar feeding and breeding. Each step represented one second of time, and each simulation was set to run for 60 days and repeated 50 times. Scenarios of different densities and spatial distributions of sugar sources and outdoor resting sites were simulated and compared.ResultsWhen the number of natural sugar sources was increased from 0 to 100 while the number of resting sites was held constant, mean daily survival rate increased from 2.5% to 85.1% for males and from 2.5% to 94.5% for females, mean human biting rate increased from 0 to 0.94 bites per human per day, and mean daily abundance increased from 1 to 477 for males and from 1 to 1,428 for females. When the number of outdoor resting sites was increased from 0 to 50 while the number of sugar sources was held constant, mean daily survival rate increased from 77.3% to 84.3% for males and from 86.7% to 93.9% for females, mean human biting rate increased from 0 to 0.52 bites per human per day, and mean daily abundance increased from 62 to 349 for males and from 257 to 1120 for females. All increases were significant (P < 0.01). Survival was greater when sugar sources were randomly

  11. Concentration and mindfulness meditations: unique forms of consciousness?

    Science.gov (United States)

    Dunn, B R; Hartigan, J A; Mikulas, W L

    1999-09-01

    Electroencephalographic (EEG) recordings from 19 scalp recording sites were used to differentiate among two posited unique forms of mediation, concentration and mindfulness, and a normal relaxation control condition. Analyzes of all traditional frequency bandwidth data (i.e., delta 1-3 Hz; theta, 4-7 Hz; alpha, 8-12 Hz; beta 1, 13-25 Hz; beta 2, 26-32 Hz) showed strong mean amplitude frequency differences between the two meditation conditions and relaxation over numerous cortical sites. Furthermore, significant differences were obtained between concentration and mindfulness states at all bandwidths. Taken together, our results suggest that concentration and mindfulness "meditations" may be unique forms of consciousness and are not merely degrees of a state of relaxation.

  12. Key role of water in proton transfer at the Q(o)-site of the cytochrome bc(1) complex predicted by atomistic molecular dynamics simulations

    DEFF Research Database (Denmark)

    Postila, P. A.; Kaszuba, K.; Sarewicz, M.

    2013-01-01

    on the simulations we are able to show the atom-level binding modes of two substrate forms: quinol (QH(2)) and quinone (Q). The QH(2) binding at the Q(o)-site involves a coordinated water arrangement that produces an exceptionally close and stable interaction between the cyt b and iron sulfur protein subunits....... In this arrangement water molecules are positioned suitably in relation to the hydroxyls of the QH(2) ring to act as the primary acceptors of protons detaching from the oxidized substrate. In contrast, water does not have a similar role in the Q binding at the Q(o)-site. Moreover, the coordinated water molecule...

  13. A multivariate linear regression model for predicting children's blood lead levels based on soil lead levels: A study at four Superfund sites

    Energy Technology Data Exchange (ETDEWEB)

    Lewin, M.D.; Sarasua, S.; Jones, P.A. (Agency for Toxic Substances and Disease Registry, Atlanta, GA (United States). Div. of Health Studies)

    1999-07-01

    For the purpose of examining the association between blood lead levels and household-specific soil lead levels, the authors used a multivariate linear regression model to find a slope factor relating soil lead levels to blood lead levels. They used previously collected data from the Agency for Toxic Substances and Disease Registry's (ATSDR's) multisite lead and cadmium study. The data included in the blood lead measurements of 1,015 children aged 6--71 months, and corresponding household-specific environmental samples. The environmental samples included lead in soil, house dust, interior paint, and tap water. After adjusting for income, education or the parents, presence of a smoker in the household, sex, and dust lead, and using a double log transformation, they found a slope factor of 0.1388 with a 95% confidence interval of 0.09--0.19 for the dose-response relationship between the natural log of the soil lead level and the natural log of the blood lead level. The predicted blood lead level corresponding to a soil lead level of 500 mg/kg was 5.99 [micro]g/kg with a 95% prediction interval of 2.08--17.29. Predicted values and their corresponding prediction intervals varied by covariate level. The model shows that increased soil lead level is associated with elevated blood leads in children, but that predictions based on this regression model are subject to high levels of uncertainty and variability.

  14. Prediction and evaluation of nonlinear site response with potentially liquefiable layers in the area of Nafplion (Peloponnesus, Greece for a repeat of historical earthquakes

    Directory of Open Access Journals (Sweden)

    V. K. Karastathis

    2010-11-01

    Full Text Available We examine the possible non-linear behaviour of potentially liquefiable layers at selected sites located within the expansion area of the town of Nafplion, East Peloponnese, Greece. Input motion is computed for three scenario earthquakes, selected on the basis of historical seismicity data, using a stochastic strong ground motion simulation technique, which takes into account the finite dimensions of the earthquake sources. Site-specific ground acceleration synthetics and soil profiles are then used to evaluate the liquefaction potential at the sites of interest. The activation scenario of the Iria fault, which is the closest one to Nafplion (M=6.4, is found to be the most hazardous in terms of liquefaction initiation. In this scenario almost all the examined sites exhibit liquefaction features at depths of 6–12 m. For scenario earthquakes at two more distant seismic sources (Epidaurus fault – M6.3; Xylokastro fault – M6.7 strong ground motion amplification phenomena by the shallow soft soil layer are expected to be observed.

  15. Ventricular catheter entry site and not catheter tip location predicts shunt survival: a secondary analysis of 3 large pediatric hydrocephalus studies.

    Science.gov (United States)

    Whitehead, William E; Riva-Cambrin, Jay; Kulkarni, Abhaya V; Wellons, John C; Rozzelle, Curtis J; Tamber, Mandeep S; Limbrick, David D; Browd, Samuel R; Naftel, Robert P; Shannon, Chevis N; Simon, Tamara D; Holubkov, Richard; Illner, Anna; Cochrane, D Douglas; Drake, James M; Luerssen, Thomas G; Oakes, W Jerry; Kestle, John R W

    2017-02-01

    OBJECTIVE Accurate placement of ventricular catheters may result in prolonged shunt survival, but the best target for the hole-bearing segment of the catheter has not been rigorously defined. The goal of the study was to define a target within the ventricle with the lowest risk of shunt failure. METHODS Five catheter placement variables (ventricular catheter tip location, ventricular catheter tip environment, relationship to choroid plexus, catheter tip holes within ventricle, and crosses midline) were defined, assessed for interobserver agreement, and evaluated for their effect on shunt survival in univariate and multivariate analyses. De-identified subjects from the Shunt Design Trial, the Endoscopic Shunt Insertion Trial, and a Hydrocephalus Clinical Research Network study on ultrasound-guided catheter placement were combined (n = 858 subjects, all first-time shunt insertions, all patients 0.60). In the univariate survival analysis, however, only ventricular catheter tip location was useful in distinguishing a target within the ventricle with a survival advantage (frontal horn; log-rank, p = 0.0015). None of the other catheter placement variables yielded a significant survival advantage unless they were compared with catheter tips completely not in the ventricle. Cox regression analysis was performed, examining ventricular catheter tip location with age, etiology, surgeon, decade of surgery, and catheter entry site (anterior vs posterior). Only age (p < 0.001) and entry site (p = 0.005) were associated with shunt survival; ventricular catheter tip location was not (p = 0.37). Anterior entry site lowered the risk of shunt failure compared with posterior entry site by approximately one-third (HR 0.65, 95% CI 0.51-0.83). CONCLUSIONS This analysis failed to identify an ideal target within the ventricle for the ventricular catheter tip. Unexpectedly, the choice of an anterior versus posterior catheter entry site was more important in determining shunt survival than

  16. Unique Physician Identification Number (UPIN) Directory

    Data.gov (United States)

    U.S. Department of Health & Human Services — The Unique Physician Identification Number (UPIN) Directory contains selected information on physicians, doctors of Osteopathy, limited licensed practitioners and...

  17. Factors predicting crisis counselor referrals to other crisis counseling, disaster relief, and psychological services: a cross-site analysis of post-Katrina programs.

    Science.gov (United States)

    Rosen, Craig S; Matthieu, Monica M; Norris, Fran H

    2009-05-01

    An important aspect of crisis counseling is linking survivors with services for their unmet needs. We examined determinants of referrals for disaster relief, additional crisis counseling, and psychological services in 703,000 crisis counseling encounters 3-18 months after Hurricane Katrina. Referrals for disaster relief were predicted by clients' losses, age (adults rather than children), and urbanicity. Referrals for additional counseling and psychological services were predicted by urbanicity, losses and trauma exposure, prior trauma, and preexisting mental health problems. Counseling and psychological referrals declined over time despite continuing mental health needs. Results confirm large urban-rural disparities in access to services.

  18. Neural network-based crop growth model to predict processing tomato yield on a site-specific basis using remotely sensed data

    Science.gov (United States)

    Koller, Michal

    Remote sensing is one of the major data acquisition tools available to rapidly acquire soil and plant related information over a wide area for use in precision agriculture. Green canopy has very specific reflectance characteristics distinguishing it from other materials such as soil and dry vegetative matter. Reflectance values in red (R) and near infra-red (NIR) spectral bands have been widely used for calculating normalized difference vegetation index (NDVI). Many researchers have related NDVI values to plant vigor, water stress, leaf area index (LAI) and/or yield. However, vegetative indices such as NDVI are usually sensitive to background reflectance characteristics. Often soil adjusted vegetation indices (SAVI) are used to minimize the background effect. In this study we have developed a relationship between the processing tomato yield and SAVI based on the R and NIR reflectance. Eight three band (R, NIR and green) aerial images were obtained at approximately two-week intervals during the 2000 processing tomato growing season. These images were analyzed to obtain SAVI values which were in turn related to LAI using regression techniques. A tuned neural network was developed to predict daily LAI values based on the biweekly experimental LAI values derived from aerial images. The coefficients of multiple determination between the actual LAI and neural network predicted LAI values were greater than 0.96 for all 56 grid points. The LAI values were numerically integrated over the whole growing season to obtain cumulative leaf area index days (CLAID). The CLAID values predicted from the neural network correlated very well with experimentally derived CLAID values (coefficient of determination, r2 = 0.83) indicating that the neural network model simulated processing tomato growth well. A crop growth model that was capable of predicting crop yield based on neural network predicted LAI values and CIMIS weather data was developed. Although predicted yield tended to be low

  19. Unique properties of Plasmodium falciparum porphobilinogen deaminase.

    Science.gov (United States)

    Nagaraj, Viswanathan Arun; Arumugam, Rajavel; Gopalakrishnan, Bulusu; Jyothsna, Yeleswarapu Sri; Rangarajan, Pundi N; Padmanaban, Govindarajan

    2008-01-04

    The hybrid pathway for heme biosynthesis in the malarial parasite proposes the involvement of parasite genome-coded enzymes of the pathway localized in different compartments such as apicoplast, mitochondria, and cytosol. However, knowledge on the functionality and localization of many of these enzymes is not available. In this study, we demonstrate that porphobilinogen deaminase encoded by the Plasmodium falciparum genome (PfPBGD) has several unique biochemical properties. Studies carried out with PfPBGD partially purified from parasite membrane fraction, as well as recombinant PfPBGD lacking N-terminal 64 amino acids expressed and purified from Escherichia coli cells (DeltaPfPBGD), indicate that both the proteins are catalytically active. Surprisingly, PfPBGD catalyzes the conversion of porphobilinogen to uroporphyrinogen III (UROGEN III), indicating that it also possesses uroporphyrinogen III synthase (UROS) activity, catalyzing the next step. This obviates the necessity to have a separate gene for UROS that has not been so far annotated in the parasite genome. Interestingly, DeltaPfP-BGD gives rise to UROGEN III even after heat treatment, although UROS from other sources is known to be heat-sensitive. Based on the analysis of active site residues, a DeltaPfPBGDL116K mutant enzyme was created and the specific activity of this recombinant mutant enzyme is 5-fold higher than DeltaPfPBGD. More interestingly, DeltaPfPBGDL116K catalyzes the formation of uroporphyrinogen I (UROGEN I) in addition to UROGEN III, indicating that with increased PBGD activity the UROS activity of PBGD may perhaps become rate-limiting, thus leading to non-enzymatic cyclization of preuroporphyrinogen to UROGEN I. PfPBGD is localized to the apicoplast and is catalytically very inefficient compared with the host red cell enzyme.

  20. Modeling of Carbon Tetrachloride Flow and Transport in the Subsurface of the 200 West Disposal Sites: Large-Scale Model Configuration and Prediction of Future Carbon Tetrachloride Distribution Beneath the 216-Z-9 Disposal Site

    Energy Technology Data Exchange (ETDEWEB)

    Oostrom, Mart; Thorne, Paul D.; Zhang, Z. F.; Last, George V.; Truex, Michael J.

    2008-12-17

    Three-dimensional simulations considered migration of dense, nonaqueous phase liquid (DNAPL) consisting of CT and co disposed organics in the subsurface as a function of the properties and distribution of subsurface sediments and of the properties and disposal history of the waste. Simulations of CT migration were conducted using the Water-Oil-Air mode of Subsurface Transport Over Multiple Phases (STOMP) simulator. A large-scale model was configured to model CT and waste water discharge from the major CT and waste-water disposal sites.

  1. An improved method for TAL effectors DNA-binding sites prediction reveals functional convergence in TAL repertoires of Xanthomonas oryzae strains.

    Directory of Open Access Journals (Sweden)

    Alvaro L Pérez-Quintero

    Full Text Available Transcription Activators-Like Effectors (TALEs belong to a family of virulence proteins from the Xanthomonas genus of bacterial plant pathogens that are translocated into the plant cell. In the nucleus, TALEs act as transcription factors inducing the expression of susceptibility genes. A code for TALE-DNA binding specificity and high-resolution three-dimensional structures of TALE-DNA complexes were recently reported. Accurate prediction of TAL Effector Binding Elements (EBEs is essential to elucidate the biological functions of the many sequenced TALEs as well as for robust design of artificial TALE DNA-binding domains in biotechnological applications. In this work a program with improved EBE prediction performances was developed using an updated specificity matrix and a position weight correction function to account for the matching pattern observed in a validation set of TALE-DNA interactions. To gain a systems perspective on the large TALE repertoires from X. oryzae strains, this program was used to predict rice gene targets for 99 sequenced family members. Integrating predictions and available expression data in a TALE-gene network revealed multiple candidate transcriptional targets for many TALEs as well as several possible instances of functional convergence among TALEs.

  2. Prediction of brain target site concentrations on the basis of CSF PK : impact of mechanisms of blood-to-brain transport and within brain distribution

    NARCIS (Netherlands)

    Westerhout, J.

    2014-01-01

    In the development of drugs for the treatment of central nervous system (CNS) disorders, the prediction of human CNS drug action is a big challenge. Direct measurement of brain extracellular fluid (brainECF) concentrations is highly restricted in human. Therefore, unbound drug concentrations in huma

  3. Confounding factors to predict the awakening effect-site concentration of propofol in target-controlled infusion based on propofol and fentanyl anesthesia.

    Science.gov (United States)

    Chan, Shun-Ming; Lee, Meei-Shyuan; Lu, Chueng-He; Cherng, Chen-Hwan; Huang, Yuan-Shiou; Yeh, Chun-Chang; Kuo, Chan-Yang; Wu, Zhi-Fu

    2015-01-01

    We conducted a large retrospective study to investigate the confounding factors that predict Ce ROC under propofol-based TIVA with TCI. We recorded sex, age, height, weight, Ce LOC, Ce ROC, total propofol and fentanyl consumption dose, and anesthetic time. Simple linear regression models were used to identify potential predictors of Ce ROC, and multiple linear regression models were used to identify the confounding predictors of Ce ROC. We found that Ce ROC correlated with age, sex, Ce LOC, and both total fentanyl and propofol consumption dose. The prediction formula was: Ce ROC = 0.87 - 0.06 × age + 0.18 × Ce LOC + 0.04 (if fentanyl consumption > 150 μg; if not, ignore this value) + 0.07 × (1 or 2, according to the total propofol consumption dose, 1 for a propofol amount 1000-2000 mg and 2 for a propofol amount > 2000 mg). We simplified the formula further as Ce ROC = 0.87 - 0.06 × age + 0.18 × Ce LOC. In conclusion, Ce ROC can be predicted under TCI with propofol- and fentanyl-based TIVA. The confounding factors that predicted propofol Ce ROC are age, sex, Ce LOC, and total consumption dose of propofol and fentanyl.

  4. Prediction of brain target site concentrations on the basis of CSF PK : impact of mechanisms of blood-to-brain transport and within brain distribution

    NARCIS (Netherlands)

    Westerhout, J.

    2014-01-01

    In the development of drugs for the treatment of central nervous system (CNS) disorders, the prediction of human CNS drug action is a big challenge. Direct measurement of brain extracellular fluid (brainECF) concentrations is highly restricted in human. Therefore, unbound drug concentrations in

  5. A multivariate linear regression model for predicting children's blood lead levels based on soil lead levels: A study at four superfund sites.

    Science.gov (United States)

    Lewin, M D; Sarasua, S; Jones, P A

    1999-07-01

    For the purpose of examining the association between blood lead levels and household-specific soil lead levels, we used a multivariate linear regression model to find a slope factor relating soil lead levels to blood lead levels. We used previously collected data from the Agency for Toxic Substances and Disease Registry's (ATSDR's) multisite lead and cadmium study. The data included the blood lead measurements (0.5 to 40.2 microg/dL) of 1015 children aged 6-71 months, and corresponding household-specific environmental samples. The environmental samples included lead in soil (18.1-9980 mg/kg), house dust (5.2-71,000 mg/kg), interior paint (0-16.5 mg/cm2), and tap water (0.3-103 microg/L). After adjusting for income, education of the parents, presence of a smoker in the household, sex, and dust lead, and using a double log transformation, we found a slope factor of 0.1388 with a 95% confidence interval of 0.09-0.19 for the dose-response relationship between the natural log of the soil lead level and the natural log of the blood lead level. The predicted blood lead level corresponding to a soil lead level of 500 mg/kg was 5.99 microg/kg with a 95% prediction interval of 2. 08-17.29. Predicted values and their corresponding prediction intervals varied by covariate level. The model shows that increased soil lead level is associated with elevated blood leads in children, but that predictions based on this regression model are subject to high levels of uncertainty and variability.

  6. Uniqueness of time-independent electromagnetic fields

    DEFF Research Database (Denmark)

    Karlsson, Per W.

    1974-01-01

    As a comment on a recent paper by Steele, a more general uniqueness theorem for time-independent fields is mentioned. ©1974 American Institute of Physics......As a comment on a recent paper by Steele, a more general uniqueness theorem for time-independent fields is mentioned. ©1974 American Institute of Physics...

  7. Some Graphs Containing Unique Hamiltonian Cycles

    Science.gov (United States)

    Lynch, Mark A. M.

    2002-01-01

    In this paper, two classes of graphs of arbitrary order are described which contain unique Hamiltonian cycles. All the graphs have mean vertex degree greater than one quarter the order of the graph. The Hamiltonian cycles are detailed, their uniqueness proved and simple rules for the construction of the adjacency matrix of the graphs are given.…

  8. Constructing Dense Graphs with Unique Hamiltonian Cycles

    Science.gov (United States)

    Lynch, Mark A. M.

    2012-01-01

    It is not difficult to construct dense graphs containing Hamiltonian cycles, but it is difficult to generate dense graphs that are guaranteed to contain a unique Hamiltonian cycle. This article presents an algorithm for generating arbitrarily large simple graphs containing "unique" Hamiltonian cycles. These graphs can be turned into dense graphs…

  9. 78 FR 58785 - Unique Device Identification System

    Science.gov (United States)

    2013-09-24

    ... 16, 801, 803, et al. Unique Device Identification System; Final Rule #0;#0;Federal Register / Vol. 78... 0910-AG31 Unique Device Identification System AGENCY: Food and Drug Administration, HHS. ACTION: Final... will substantially reduce existing obstacles to the adequate identification of medical devices used in...

  10. A note on uniquely (nil clean ring

    Directory of Open Access Journals (Sweden)

    Shervin Sahebi

    2014-05-01

    Full Text Available A ring $R$ is uniquely (nil clean in case for any $a\\in R$‎ ‎there exists a uniquely idempotent $e\\in R$ such that $a-e$ is‎ ‎invertible (nilpotent‎. ‎Let‎ ‎$C=\\small\\left(‎‎\\begin{array}{cc}‎‎A & V \\\\‎ ‎W & B‎‎\\end{array}‎‎\\right$‎ ‎be the Morita Context ring‎. ‎We determine conditions under which the rings $A‎, ‎B$‎ ‎are uniquely (nil clean‎. ‎Moreover we show that the center of a uniquely (nil‎‎clean ring is uniquely (nil clean.

  11. Predicting gene expression from sequence: a reexamination.

    Directory of Open Access Journals (Sweden)

    Yuan Yuan

    2007-11-01

    Full Text Available Although much of the information regarding genes' expressions is encoded in the genome, deciphering such information has been very challenging. We reexamined Beer and Tavazoie's (BT approach to predict mRNA expression patterns of 2,587 genes in Saccharomyces cerevisiae from the information in their respective promoter sequences. Instead of fitting complex Bayesian network models, we trained naïve Bayes classifiers using only the sequence-motif matching scores provided by BT. Our simple models correctly predict expression patterns for 79% of the genes, based on the same criterion and the same cross-validation (CV procedure as BT, which compares favorably to the 73% accuracy of BT. The fact that our approach did not use position and orientation information of the predicted binding sites but achieved a higher prediction accuracy, motivated us to investigate a few biological predictions made by BT. We found that some of their predictions, especially those related to motif orientations and positions, are at best circumstantial. For example, the combinatorial rules suggested by BT for the PAC and RRPE motifs are not unique to the cluster of genes from which the predictive model was inferred, and there are simpler rules that are statistically more significant than BT's ones. We also show that CV procedure used by BT to estimate their method's prediction accuracy is inappropriate and may have overestimated the prediction accuracy by about 10%.

  12. Two Predicted Transmembrane Domains Exclude Very Long Chain Fatty acyl-CoAs from the Active Site of Mouse Wax Synthase.

    Directory of Open Access Journals (Sweden)

    Steffen Kawelke

    Full Text Available Wax esters are used as coatings or storage lipids in all kingdoms of life. They are synthesized from a fatty alcohol and an acyl-CoA by wax synthases. In order to get insights into the structure-function relationships of a wax synthase from Mus musculus, a domain swap experiment between the mouse acyl-CoA:wax alcohol acyltransferase (AWAT2 and the homologous mouse acyl-CoA:diacylglycerol O-acyltransferase 2 (DGAT2 was performed. This showed that the substrate specificity of AWAT2 is partially determined by two predicted transmembrane domains near the amino terminus of AWAT2. Upon exchange of the two domains for the respective part of DGAT2, the resulting chimeric enzyme was capable of incorporating up to 20% of very long acyl chains in the wax esters upon expression in S. cerevisiae strain H1246. The amount of very long acyl chains in wax esters synthesized by wild type AWAT2 was negligible. The effect was narrowed down to a single amino acid position within one of the predicted membrane domains, the AWAT2 N36R variant. Taken together, we provide first evidence that two predicted transmembrane domains in AWAT2 are involved in determining its acyl chain length specificity.

  13. 运用GMS模型对某垃圾场地下水污染的研究%GMS Model for Assessment and Prediction of Groundwater Pollution of a Garbage Dumpling Site in Luoyang

    Institute of Scientific and Technical Information of China (English)

    仝晓霞; 宁立波; 董少刚

    2012-01-01

    通过对洛阳市某垃圾场的环境地质条件调查和地下水污染监测,用综合污染指数和内梅罗污染指数法,评价了垃圾场对地下水的污染情况;运用GMS模型选择垃圾场的特征污染物对垃圾场周围土壤及地下水的污染现状进行了影响评价;并通过数值模拟计算进行污染预测,为垃圾场水土污染的防治提供了基础资料和科学依据.%Based on surveying and monitoring of environmental and geological conditions of groundwater in a garbage dumpling site at Luoyang, Henan Province, integrating pollution index and Gianni Merlo pollution index were used to assess the influence of the site pollution on groundwater. GMS model was used to select the characteristics pollutants for the assessment of soil and groundwater pollution status around the dumpling site, as well as the prediction by numerical simulation, which would provide scientific basis for prevention and control of water and soil pollution of dumping site.