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CoreGenes3.5: A webserver for the determination of core genes from sets of viral and small bacterial genomes

BMC Research Notes 2013年第1期6卷 1-4页

作者： Turner, Dann Reynolds, Darren Seto, Donald Mahadevan, Padmanabhan Centre for Research in Biosciences Faculty of Applied Sciences University of the West of England Bristol BS16 1QY United Kingdom Bioinformatics and Computational Biology Program School of Systems Biology George Mason University Manassas VA 20110 United States Department of Biology University of Tampa Tampa FL 33606 United States

Background: CoreGenes3.5 is a webserver that determines sets of core genes from viral and small bacterial genomes as an automated batch process. Previous versions of CoreGenes have been used to classify bacteriophage genomes and mine data from pathogen genomes. Findings. CoreGenes3.5 accepts as input GenBank accession numbers of genomes and performs iterative BLASTP analyses to output a set of core genes. After completion of the program run, the results can be either displayed in a new window for one pair of reference and query genomes or emailed to the user for multiple pairs of small genomes in tabular format. Conclusions: With the number of genomes sequenced increasing daily and interest in determining phylogenetic relationships, CoreGenes3.5 provides a user-friendly web interface for wet-bench biologists to process multiple small genomes for core gene determinations. CoreGenes3.5 is available at. © 2013 Turner et al.;licensee BioMed Central Ltd.

关键词： Bacteriophage Core genes Data mining Taxonomy Viral genomics

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Manifold learning-based methods for analyzing single-cell RNA-sequencing data

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Current Opinion in Systems biology 2018年 7卷 36-46页

作者： Moon, Kevin R. Stanley, Jay S. Burkhardt, Daniel van Dijk, David Wolf, Guy Krishnaswamy, Smita Department of Genetics Yale University New Haven CT United States Applied Mathematics Program Yale University New Haven CT United States Computational Biology and Bioinformatics Program Yale University New Haven CT United States Department of Computer Science Yale University New Haven CT United States

Recent advances in single-cell RNA sequencing technologies enable deep insights into cellular development, gene regulation, and phenotypic diversity by measuring gene expression for thousands of cells in a single experiment. While these technologies hold great potential for improving our understanding of cellular states and progression, they also pose new challenges and require advanced mathematical and algorithmic tools to extract underlying biological signals. In this review, we cover one of the most promising avenues of research into unlocking the potential of scRNA-seq data: the field of manifold learning, and the related manifold assumption in data analysis. Manifold learning provides a powerful structure for algorithmic approaches to process the data, extract its dynamics, and infer patterns in it. In particular, we cover manifold learning-based methods for denoising the data, revealing gene interactions, extracting pseudotime progressions with model fitting, visualizing the cellular state space via dimensionality reduction, and clustering the data. © 2017 Published by Elsevier Ltd.

关键词： Data mining Gene regulatory networks Imputation Manifold learning Pseudotime trends Single cell RNA sequencing

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Parsimonious reconstruction of network evolution

Parsimonious reconstruction of network evolution

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Lecture Notes in Computer Science

作者： Patro, Rob Sefer, Emre Malin, Justin Marçais, Guillaume Navlakha, Saket Kingsford, Carl Center for Bioinformatics and Computational Biology University of Maryland College Park MD 20742 United States Department of Computer Science University of Maryland College Park MD 20742 United States Computational Biology Bioinformatics and Genomics Concentration Biological Sciences Graduate Program University of Maryland College Park MD 20742 United States Program in Applied Mathematics Statistics and Scientific Computation University of Maryland College Park MD 20742 United States School of Computer Science Carnegie Mellon University Pittsburgh PA 15213 United States

ISBN: (纸本)9783642230370

We consider the problem of reconstructing a maximally parsimonious history of network evolution under models that support gene duplication and loss and independent interaction gain and loss. We introduce a combinatorial framework for encoding network histories, and we give a fast procedure that, given a set of duplication histories, in practice finds network histories with close to the minimum number of interaction gain or loss events. In contrast to previous studies, our method does not require knowing the relative ordering of unrelated duplication events. Results on simulated histories suggest that common ancestral networks can be accurately reconstructed using this parsimony approach. © 2011 Springer-Verlag.

关键词： Genes

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Conservation of ancient full-length open reading frames in vertebrate endogenous retroviruses

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Retrovirology 2011年第2期8卷 1-2页

作者： Hugo Martins Palle Villesen Bioinformatics Research Centre Aarhus University Denmark PhD Program in Computational Biology Instituto Gulbenkian de Ciências Oeiras Portugal

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Broadening the scope of nanopublications

Broadening the scope of nanopublications

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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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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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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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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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