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IEEE International Conference on bioinformatics and Biomedicine (BIBM)

作者： Vinhthuy Phan Sudip Saha Ashutosh Pandey Wong Tit-Yee Department of Computer Science The Bioinformatics Program University of Memphis USA Department of Computer Science University of Memphis USA The Bioinformatics Program University of Memphis USA Department of Biology University of Memphis USA

Hidden stop codons are nucleotide triples TAA, TAG, and TGA that appear in the second and third reading frames of a protein coding gene. Recent studies reported biological evidence suggesting that hidden stop codons are important in preventing misread of mRNA, which is often detrimental to the cell. We study the problem of designing protein-encoding genes with large number of hidden stop codons under biological constraints including GC content and codon usage of individual organism. In simpler models, we obtained provably optimal results. In more complex models, the designed genes have many more hidden stop codons than wild-type genes do, as observed in an experiment with 8 genomes with a wide range of GC content and codon usage.

关键词： Proteins bioinformatics Organisms Amino acids Genetics Technical Activities Guide -TAG Genomics Computer science Biological system modeling Synthetic biology

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Comparative analysis of different approaches for dealing with candidate regions in the context of a genome-wide association study

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BMC proceedings 2009年第7期3 Suppl 7卷 S93页

作者： Francesca Lantieri Min A Jhun Jungsun Park Taesung Park Marcella Devoto The Children's Hospital of Philadelphia 3615 Civic Center Boulevard Philadelphia Pennsylvania 19104 USA. Dipartimento di Scienze della Salute sezione di Biostatistica Universita' degli Studi di Genova via Pastore 1 16132 Genoa Italy. Interdisciplinary Program in Bioinformatics Seoul National University Seoul 56-1 Shillim-Dong Kwanak-Gu Seoul 151-742 Korea. Department of Statistics Seoul National University Seoul 56-1 Shillim-Dong Kwanak-Gu 151-747 Korea. Department of Pediatrics and CCEB University of Pennsylvania 3615 Civic Center Boulevard Philadelphia Pennsylvania 19104 USA. Dipartimento di Medicina Sperimentale Universita' La Sapienza Viale Regina Elena 324 00161 Roma Italy.

Genome-wide association studies (GWAS) test hundreds of thousands of single-nucleotide polymorphisms (SNPs) for association to a trait, treating each marker equally and ignoring prior evidence of association to specific regions. Typically, promising regions are selected for further investigation based on p-values obtained from simple tests of association. However, loci that exert only a weak, low-penetrant role on the trait, producing modest evidence of association, are not detectable in the context of a GWAS. Implementing prior knowledge of association in GWAS could increase power, help distinguish between false and true positives, and identify better sets of SNPs for follow-up *** we performed a GWAS on rheumatoid arthritis (RA) patients and controls (Problem 1, Genetic Analysis Workshop 16). In order to include prior information in the analysis, we applied four methods that distinctively deal with markers in candidate genes in the context of GWAS. SNPs were divided into a random and a candidate subset, then we applied empirical correction by permutation, false-discovery rate, false-positive report probability, and posterior odds of association using different prior probabilities. We repeated the same analyses on two different sets of candidate markers defined on the basis of previously reported association to RA following two different approaches. The four methods showed similar relative behavior when applied to the two sets, with the proportion of candidate SNPs ranked among the top 2,000 varying from 0 to 100%. The use of different prior probabilities changed the stringency of the methods, but not their relative performance.

关键词： Rheumatoid Arthritis Prior Probability Candidate Marker Candidate SNPs Genetic Analysis Workshop

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Large-scale analysis of human heavy chain V(D)J recombination patterns

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Immunome Research 2008年第1期4卷 1-10页

作者： Volpe, Joseph M Kepler, Thomas B Center for Computational Immunology Duke University Durham NC United States Department of Immunology Duke Univeristy Medical Center Durham NC United States Department of Biostatistics and Bioinformatics Duke Univeristy Medical Center Durham NC United States Institute of Statistics and Decision Sciences Duke Univeristy Durham NC United States Computational Biology and Bioinformatics Graduate Program Institute for Genome Sciences and Policy Duke Univeristy Durham NC United States

Background. The processes involved in the somatic assembly of antigen receptor genes are unique to the immune system and are driven largely by random events. Subtle biases, however, may exist and provide clues to the molecular mechanisms involved in their assembly and selection. Large-scale efforts to provide baseline data about the genetic characteristics of immunoglobulin (Ig) genes and the mechanisms involved in their assembly have recently become possible due to the rapid growth of genetic databases. Results. We gathered and analyzed nearly 6,500 productive human Ig heavy chain genes and compared them with 325 non-productive Ig genes that were originally rearranged out of frame and therefore incapable of being biased by selection. We found evidence for differences in n-nucleotide tract length distributions which have interesting interpretations for the mechanisms involved in n-nucleotide polymerization. Additionally, we found striking statistical evidence for pairing preferences among D and J segments. We present a statistical model to support our hypothesis that these pairing biases are due to multiple sequential D-to-J rearrangements. Conclusion. We present here the most precise estimates of gene segment usage frequencies currently available along with analyses regarding n-nucleotide distributions and D-J segment pair preferences. Additionally, we provide the first statistical evidence that sequential D-J recombinations occur at the human heavy chain locus during B-cell ontogeny with an approximate frequency of 20%.

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Condition specific subnetwork identification using an optimization model

Condition specific subnetwork identification using an optimi...

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第二届最优化与系统生物学国际研讨会

作者： Yong Wang Yu Xia Bioinformatics Program Department of Chemistry Boston University Academy of Mathematics and Systems Science Chinese Academy of Sciences

Subnetworks can reveal the complex patterns of the whole-genome network by extracting the interactions that depend on temporal, spatial, or condition specific context. In this paper we present an optimization framework to identify condition specific subnetworks. This framework allows us to identify the most coherent subnetwork by integrating the information from both nodes and edges in the graph. Importantly we design an algorithm to solve the optimization problem efficiently. It is very fast and can extract subnetworks from large-scale network with about 10000 nodes. As a pilot study we apply our method to identify type 2 diabetes related subnetworks in the human protein-protein interaction network.

关键词： Condition specific subnetwork Optimization model and algorithm Diabetes

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Analysis of insertional sites of the SIRE1 retroelement family from Glycine Max using GenBank BAC-end sequences

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In Silico Biology 2008年第5-6期8卷 531-543页

作者： Flasch, Diane A. Rebman, Ellen K. Olfson, Emily H. Nguyen, Khanh K. Geirut, Lucasz E. Garland, Megan C. Lindorfer, Christi M. Laten, Howard M. Department of Biology Loyola University Chicago Chicago IL 60626 6525 N. Sheridan Rd. United States Program in Bioinformatics Loyola University Chicago Chicago IL United States Department of Biology Oberlin College Oberlin OH United States

SIRE1 is a 2,000-copy member of the Ty1/copia retroelement family found in the soybean genome and is closely related to sireviruses found in the genomes of other legumes. Although these elements closely resemble typical plant members of the Ty1/copia family, they are unusual in that they possess an envelope-like coding region immediately downstream of the reverse transcriptase gene. Despite its copy number, very few members of the SIRE1 family are currently present in publicly available genomic assemblies or draft contigs. However, fragments of family members are well-represented as BAC-ends in the GenBank Genome Survey Sequence database. This database was queried using the 5′ and 3′ ends of SIRE1 in order to catalog sequences into which SIRE1 members have integrated. Seven hundred and eighty-one unique SIRE1 insertions were identified and the majority of insertion sites constituted other repetitive elements, including Class I and Class II transposable elements and satellite DNAs. Ninety-four insertions were in single- or low-copy number sequences and three of these were homologous to characterized protein-coding genes. Examination of the ten bases flanking either side of SIRE1 revealed no clear consensus sequence, but the the distributions of A, C, G, and T at most of the positions were biased with strong statistical significance. © 2008 IOS Press. All rights reserved.

关键词： Endogenous retrovirus Integration LTR Repetitive DNA Retrotransposon Sirevirus Soybean Target site

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Volumetric, cortical thickness and grey matter density changes on MRI over 12 months: Relationship to conversion status in the ADNI cohort

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Alzheimer's & Dementia 2009年第4期5卷 P200-P200页

作者： Shannon L. Risacher Andrew J. Saykin Li Shen John D. West Sungeun Kim Brenna C. McDonald Center for Neuroimaging Division of Imaging Sciences Department of Radiology Indiana University School of Medicine Indianapolis IN USA Medical Neuroscience Program Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN USA Indiana Alzheimer Disease Center Indianapolis IN USA Center for Computational Biology and Bioinformatics Indiana University School of Medicine Indianapolis IN USA

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Information visualization services in a library? A public health case study

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Bulletin of the Association for Information Science and Technology 2009年第5期35卷

作者： Barrie Hayes Hong Yi Andrés Villaveces Bioinformatics librarian and Collaboration Center manager in the Biomedical Informatics Research Support and Training Program of the Health Sciences Library at the University of North Carolina at Chapel Hill Sernior research software developer Renaissance Computing Institute University of North Carolina at Chapel Hill Research assistant professor Department of Epidemiology and the Injury Prevention Research Center at the University of North Carolina at Chapel Hill

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A new approach to predict interactions between integral membrane proteins in yeast

A new approach to predict interactions between integral memb...

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Congress on Evolutionary Computation

作者： Kelvin Xi Zhang B.F. Francis Ouellette Ontario Institute for Cancer Research Toronto ONT Canada Graduate Program in Bioinformatics University of British Columbia BC Canada

Protein-protein interactions (PPIs) play an extremely important role in performing a variety of biological functions. The interactomes of several model organisms including budding yeast Saccharomyces cerevisiae have recently been studied using experimental techniques such as the yeast two-hybrid assay. However, these techniques are generally biased against integral membrane proteins due to their intrinsic limitations. Given the fact that the interactions between integral membrane proteins cover a large fraction of the whole interactome, we report a study of predicting interactions between integral membrane proteins in yeast by a quantitative model We integrate protein-protein interaction and domain-domain interaction (DDI) data from disparate sources and apply a log likelihood scoring method on all putative integral membrane proteins in yeast to predict their interactions based on a cut-off threshold. We show that our approach improves on other predictive approaches when tested on a ldquogold-standardrdquo data set and achieves 74.6% true positive rate at the expense of 0.43% false positive rate. Furthermore, we find that two integral membrane proteins are more likely to interact with each other if they share more common interaction partners. This study allows us to reach a more extensive understanding of the yeast integral membrane proteins from a network view, which also complements the previous prediction approaches based on the genomic context.

关键词： Evolutionary computation

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It takes glue to tango: MeDICi integration framework's data-intensive computing pipeline

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Scientific Computing 2008年第7期25卷 16-19页

作者： Gorton, Ian Oehmen, Christopher S. McDermott, Hason E. PNNL's Data Intensive Computing Program United States Laboratory's Bioinformatics and Computational Biology Group Fundamental and Computational Sciences Directorate United States

Researchers at the Department of Energy's (DOE) Pacific Northwest National Laboratory (PNNL) in Richland, WA, are creating computing environments for biologists that seamlessly integrate collections of data and computational resources. MeDICi is an evolving middleware platform for building complex, high-performance analytical applications. MIF components are constructed using Java programming interfaces that support inter-component communication using asynchronous messaging. Local components execute inside the MIF container. Remote components create distributed solutions and integrate with non-Java code. Mule provides the MIF container environment. MIF extends the Mule interface to make component and pipeline construction easier and to create an encapsulation device for component creation. The MIF interface is agnostic of the underlying Java messaging platform. This allows deployments to configure MIF applications using technologies that meet individual quality-of-service requirements.

关键词： Containers

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Knowledge-based versus experimentally acquired distance and angle constraints for NMR structure refinement

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Journal of bioinformatics and Computational Biology 2008年第2期6卷 283-300页

作者： Cui, Feng Jernigan, Robert Wu, Zhijun Laboratory of Cell Biology National Cancer Institute National Institutes of Health Bethesda MD 20892 United States Program on Bioinformatics and Computational Biology Iowa State University Ames IA 50011 United States Department of Biochemistry Biophysics and Molecular Biology Iowa State University Ames IA 50011 United States Department of Mathematics Iowa State University Ames IA 50011 United States

Nuclear Overhauser effects (NOE) distance constraints and torsion angle constraints are major conformational constraints for nuclear magnetic resonance (NMR) structure refinement. In particular, the number of NOE constraints has been considered as an important determinant for the quality of NMR structures. Of course, the availability of torsion angle constraints is also critical for the formation of correct local conformations. In our recent work, we have shown how a set of knowledge-based short-range distance constraints can also be utilized for NMR structure refinement, as a complementary set of conformational constraints to the NOE and torsion angle constraints. In this paper, we show the results from a series of structure refinement experiments by using different types of conformational constraints - NOE, torsion angle, or knowledge-based constraints - or their combinations, and make a quantitative assessment on how the experimentally acquired constraints contribute to the quality of structural models and whether or not they can be combined with or substituted by the knowledge-based constraints. We have carried out the experiments on a small set of NMR structures. Our preliminary calculations have revealed that the torsion angle constraints contribute substantially to the quality of the structures, but require to be combined with the NOE constraints to be fully effective. The knowledge-based constraints can be functionally as crucial as the torsion angle constraints, although they are statistical constraints after all and are not meant to be able to replace the latter. © 2008 Imperial College Press.

关键词： Knowledge-based distance constraints NMR structure refinement NOE distance constraints Precision and accuracy of NMR structures Torsion angle constraints

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