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10th International Conference on The Semantic Web: Semantics and Big Data, ESWC 2013

作者： Kuhn, Tobias Barbano, Paolo Emilio Nagy, Mate Levente Krauthammer, Michael Department of Pathology Yale University New Haven United States Department of Sociology Particular of Modeling and Simulation ETH Zurich Switzerland Department of Mathematics Yale University United States Program for Computational Biology and Bioinformatics Yale University United States

ISBN: (纸本)9783642382871

In this paper, we present an approach for extending the existing concept of nanopublications-tiny entities of scientific results in RDF representation-to broaden their application range. The proposed extension uses English sentences to represent informal and underspecified scientific claims. These sentences follow a syntactic and semantic scheme that we call AIDA (Atomic, Independent, Declarative, Absolute), which provides a uniform and succinct representation of scientific assertions. Such AIDA nanopublications are compatible with the existing nanopublication concept and enjoy most of its advantages such as information sharing, interlinking of scientific findings, and detailed attribution, while being more flexible and applicable to a much wider range of scientific results. We show that users are able to create AIDA sentences for given scientific results quickly and at high quality, and that it is feasible to automatically extract and interlink AIDA nanopublications from existing unstructured data sources. To demonstrate our approach, a web-based interface is introduced, which also exemplifies the use of nanopublications for non-scientific content, including meta-nanopublications that describe other nanopublications. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Semantics

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Structural characterization of RNA-binding sites of proteins: Preliminary results

Structural characterization of RNA-binding sites of proteins...

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IEEE International Conference on bioinformatics and Biomedicine Workshops (BIBMW)

作者： Fadi Towfic David C. Gemperline Cornelia Caragea Feihong Wu Drena Dobbs Vasant Honavar Bioinformatics and Computational Biology Graduate Program Iowa State University Ames IA USA Department of Biology Department of Chemistry Carthage College Kenosha WI USA Department of Computer Science Iowa State University Ames IA USA Department of Genetics Development and Cell Biology Bioinformatics and Computational Biology Graduate Program Iowa State University Ames IA USA Department of Computer Science Bioinformatics and Computational Biology Graduate Program Iowa State University Ames IA USA

We explore whether protein-RNA interfaces differ from non-interfaces in terms of their structural features and whether structural features vary according to the type of the bound RNA (e.g., mRNA, siRNA...etc), using a non-redundant dataset of 147 protein chains extracted from protein-RNA complexes in the protein data bank. Our analysis of surface roughness, solid angle and CX value of amino acid residues for each of the protein chains in the dataset shows that: The protein-RNA interface residues tend to be protruding compared to non-interface residues and tend to have higher surface roughness and exhibit moderately convex or concave solid angles. Furthermore, the protein chains in protein-RNA interfaces that contain Viral RNA and rRNA significantly differ from those that contain dsRNA, mRNA siRNA, snRNA, SRP RNA and tRNA with respect to their CX values. The results of this analysis sug gests the possibility of using such structural features to reliably identify protein-RNA interface residues when the structure of the protein is available but the structures of complexes formed by the protein with RNA are not.

关键词： RNA Protein engineering biology computing Amino acids bioinformatics Computer interfaces Rough surfaces Surface roughness Solids Machine learning

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Meeting report on RECOMB 2013 （the 17th Annual International Conference on Research in computational Molecular biology）

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Frontiers of Electrical and Electronic Engineering in China 2013年第2期8卷 175-181页

作者： Xuegong Zhang Fengzhu Sun MOE Key Laboratory of Bioinformatics and Bioinformatics Division/Center for Synthetic and Systems Biology TNLIST and Department of Automation Tsinghua University Beijing 100084 China Molecular and Computational Biology Program University of Southern California Los Angeles CA 90089 USA

RECOMB 2013 was successfully held in Tsinghua University, Beijing, China on April 7-10, 2013, hosted by the bioinformatics Division and Center for Synthetic and Systems biology, Tsinghua National Laboratory for Information Science and Technology （TNLIST）. A total of about 500 professionals from both academia and industry from 29 countries and regions attended the conference and its RECOMB-Seq satellite workshop after the main conference.

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Invited: Reverse engineering whole-genome networks

Invited: Reverse engineering whole-genome networks

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IEEE International Conference on computational Advances in Bio and Medical Sciences (ICCABS)

作者： Srinivas Aluru Department of Electrical and Computer Engineering Bioinformatics and Computational Biology Program Iowa State University Ames IA USA

A research on the development of parallel methods to eliminate piecemeal approach on building whole-genome networks and facilitate genome-scale network inference, are discussed. A parallel mutual information based method is developed, which can scale up to an arbitrary number of genes and gene expression measurements on sufficiently large parallel computers and clusters. A novel technique to carry out permutation testing for assessing the statistical significance of predicted gene-gene interactions is used to construct a whole genome network of the model plant Arabidopsis thaliana in 9 minutes on a 1024 core cluster. The paper also studied the construction of the whole genome network using mutual information, sample small subgraphs from the network, and refine these local networks through parallel Bayesian inference; and heuristic algorithms for large scale Bayesian inference.

关键词： Bayesian methods bioinformatics Genomics Mutual information Gene expression Genetic communication

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P.R.E.S.S. — An R-package for exploring residual-level protein structural statistics

P.R.E.S.S. — An R-package for exploring residual-level prot...

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IEEE International Conference on bioinformatics and Biomedicine Workshops (BIBMW)

作者： Yuanyuan Huang Steve Bonett Andrzej Kloczkowski Robert Jernigan Zhijun Wu Program on Bioinformatics and Computational Biology Department of Mathematics Iowa State University Ames IA USA Summer REU Program on Computational Systems Biology Iowa State University Ames IA USA Department of Biochemistry Biophysics and Molecular Biology Iowa State University Ames IA USA Program on Bioinformatics and Computational Biology Department of Biochemistry Biophysics and Molecular Biology Iowa State University Ames IA USA

P.R.E.S.S. is an R package developed to allow researchers to get access to and manipulate on a large set of statistical data on protein residue-level structural properties such as residue-level virtual bond lengths, virtual bond angles, and virtual torsion angles. A large set of high-resolution protein structures are downloaded and surveyed. Their residue-level structural properties are calculated and documented. The statistical distributions and correlations of these properties can be queried and displayed. Tools are also provided for modeling and analyzing a given structure in terms of its residue-level structural properties. In particular, new tools for computing residue-level statistical potentials and displaying residue-level Ramachandran-like plots are developed for structural analysis and refinement. P.R.E.S.S. will be released in R as an open source software package, with a user-friendly GUI, accessible and executable by a public user in any R environment.

关键词： Correlation Proteins Graphical user interfaces Potential energy Protein engineering Software Graphics

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Pitfalls of restriction enzyme analysis in identifying, characterizing,typing, and naming viral pathogens in the era of whole genome data, as illustrated by HAdV type 55

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Virologica Sinica 2016年第5期31卷 448-453页

作者： Qiwei Zhang Shoaleh Dehghan Donald Seto Biosafety Level-3 Laboratory School of Public HealthSouthern Medical University(Guangdong Provincial Key Laboratory of Tropical Disease Research) Chemistry Department American University Bioinformatics and Computational Biology Program School of Systems BiologyGeorge Mason University

Restriction endonuclease analysis(REA),or restriction fragment length polymorphism(RFLP),was useful for identifying and determining the relatedness and putative identities of microbial strains(Tang et al.,1997)and for... 详细信息

关键词： and naming viral pathogens in the era of whole genome data DLL QS characterizing,typing Pitfalls of restriction enzyme analysis in identifying REA type

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Leap forward with insect genomics

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Insect Science 2016年第3期23卷 332-334页

作者： Bin Chen Xian-Hui Wang Zhijian Tu Yong-Ping Huang Institute of Entomology and Molecular Biology Chongqing Normal University Chongqing China State Key Laboratory of IntegratedManagement of Pest Insects & Rodents Institute of Zoology Chinese Academy of Sciences Beijing China Department of Biochemistry Fralin Life Science Institute and Program in Genetics Bioinformatics and Computational Biology Virginia Tech Blacksburg Virginia USAand Key Laboratory of Insect Development and Evolutionary Biology Institute of Plant Physiology and Ecology Shanghai Institutes forBiological Sciences Chinese Academy of Sciences Shanghal China

Insects comprise the largest animal group in the world. More than a million insect species have been identified, leaving possibly two to three times more to be discovered. Systematic understanding of the genetic content of an insect species began more than 15 years ago when the genome sequence of the fruit fly, Drosophila melanogaster was reported （Adams et al., 2000）. For the first time, scientists were able to glean unprecedented insights into the genetic blueprint of a model insect, presenting its 13 600 protein coding genes. Such fundamental information opened a floodgate for comparative and functional analysis of these genes and enabled systems approaches to comparative, evolutionary and population genomic studies. In recent years, next-generation and third-generation sequencing platforms brought genome sequencing to more than a hundred insect species, reach- ing far beyond the few well-studied model organisms. The international consortium for insect genomes is work- ing toward an ambitious goal to sequence 5000 species of insects.

关键词： Drosophila melanogaster Insect genetics DNA sequencing Genetic code Insect evolution Insect population genetics

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The role of heritability in mapping expression quantitative trait loci

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BMC proceedings 2007年第1-Sup期1 Suppl 1卷 S86页

作者： Song Huang David Ballard Hongyu Zhao Program of Computational Biology and Bioinformatics Yale University New Haven Connecticut 06520 USA. song.huang@yale.edu

Gene expression, as a heritable complex trait, has recently been used in many genome-wide linkage studies. The estimated overall heritability of each trait may be considered as evidence of a genetic contribution to the total phenotypic variation, which implies the possibility of mapping genome regions responsible for the gene expression variation via linkage analysis. However, heritability has been found to be an inconsistent predictor of significant linkage signals. To investigate this issue in human studies, we performed genome-wide linkage analysis on the 3554 gene expression traits of 194 Centre d'Etude du Polymorphisme Humain individuals provided by Genetic Analysis Workshop 15. Out of the 422 expression traits with significant linkage signals identified (LOD > 5.3), 89 traits have low estimated heritability (h2 < 10%), among which 23 traits have an estimated heritability equal to 0. The linkage analysis on individual pedigree shows that the overall LOD scores may result from a few pedigrees with strong linkage signals. Screening gene expressions before linkage analysis using a relatively low heritability (h2 < 20%) may result in a loss of significant linkage signals, especially for trans-acting expression quantitative trait loci (49%).

关键词： Linkage Analysis Heritability Estimate Expression Trait Genetic Analysis Workshop Select Gene Expression

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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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Prediction of mitochondrial proteins of malaria parasite using improved hybrid method and reduced amino acid alphabet

Prediction of mitochondrial proteins of malaria parasite usi...

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2011 4th International Conference on Biomedical Engineering and Informatics, BMEI 2011

作者： Chen, Ying-Li Li, Qian-Zhong Zhang, Li-Qing Laboratory of Theoretical Biophysics School of Physical Science and Technology Inner Mongolia University Hohhot China Department of Computer Science Virginia Tech Blacksburg VA United States Program in Genetics Bioinformatics and Computational Biology Virginia Tech Blacksburg VA United States

ISBN: (纸本)9781424493524

The rate of human death and morbidity due to malaria is increasing in many parts of the developing countries. Thus, there is a great need to understand the critical pathways in malaria parasite in order to develop effective drugs and vaccines. In this work, based on the measure of diversity definition, we introduce the increment of diversity fusion (IDF), an improved hybrid method to predict mitochondrial proteins of malaria parasite. We conduct our experiment on an expanded protein dataset where we require the pairwise identity between two proteins is less than 25%. By choosing amino acids composition as the only input vector, we are able to achieve 65.4% accuracy with 0.32 Mathew's correlation coefficient (MCC) for the jackknife test. Further, incorporting the compositions of the N-terminal and C-terminal regions into the input vector, we show that the prediction results are improved to 82.0% accuracy with 0.64 MCC in the jackknife test. In addition, by combining with the several reduced amino acid alphabet and the hydropathy distribution along protein sequence, we achieve maximum 83.4% accuracy with 0.67 MCC in the jackknife test by using the 64 dipeptide compositions of the reduced amino acid alphabet obtained from Protein Blocks method. © 2011 IEEE.

关键词： Proteins

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