Literature DB >> 15972284

BiNGO: a Cytoscape plugin to assess overrepresentation of gene ontology categories in biological networks.

Steven Maere1, Karel Heymans, Martin Kuiper.   

Abstract

The Biological Networks Gene Ontology tool (BiNGO) is an open-source Java tool to determine which Gene Ontology (GO) terms are significantly overrepresented in a set of genes. BiNGO can be used either on a list of genes, pasted as text, or interactively on subgraphs of biological networks visualized in Cytoscape. BiNGO maps the predominant functional themes of the tested gene set on the GO hierarchy, and takes advantage of Cytoscape's versatile visualization environment to produce an intuitive and customizable visual representation of the results.

Mesh：

Year:  2005        PMID： 15972284     DOI： 10.1093/bioinformatics/bti551

Source DB:  PubMed          Journal:  Bioinformatics        ISSN： 1367-4803            Impact factor:   6.937


  1830 in total

1.  Evaluation of the cell viability of human Wharton's jelly stem cells for use in cell therapy.

Authors:  Ingrid Garzón; Barbara Pérez-Köhler; Juan Garrido-Gómez; Victor Carriel; Renato Nieto-Aguilar; Miguel Angel Martín-Piedra; Natalio García-Honduvilla; Julia Buján; Antonio Campos; Miguel Alaminos
Journal:  Tissue Eng Part C Methods       Date:  2012-01-26       Impact factor: 3.056

Review 2.  Tools for protein-protein interaction network analysis in cancer research.

Authors:  Rebeca Sanz-Pamplona; Antoni Berenguer; Xavier Sole; David Cordero; Marta Crous-Bou; Jordi Serra-Musach; Elisabet Guinó; Miguel Ángel Pujana; Víctor Moreno
Journal:  Clin Transl Oncol       Date:  2012-01       Impact factor: 3.405

3.  ApoptoProteomics, an integrated database for analysis of proteomics data obtained from apoptotic cells.

Authors:  Magnus Ø Arntzen; Bernd Thiede
Journal:  Mol Cell Proteomics       Date:  2011-11-08       Impact factor: 5.911

4.  Large-scale phosphotyrosine proteomic profiling of rat renal collecting duct epithelium reveals predominance of proteins involved in cell polarity determination.

Authors:  Boyang Zhao; Mark A Knepper; Chung-Lin Chou; Trairak Pisitkun
Journal:  Am J Physiol Cell Physiol       Date:  2011-09-21       Impact factor: 4.249

5.  Generation and comprehensive analysis of an influenza virus polymerase cellular interaction network.

Authors:  Lionel Tafforeau; Thibault Chantier; Fabrine Pradezynski; Johann Pellet; Philippe E Mangeot; Pierre-Olivier Vidalain; Patrice Andre; Chantal Rabourdin-Combe; Vincent Lotteau
Journal:  J Virol       Date:  2011-10-12       Impact factor: 5.103

6.  Network analysis of pseudogene-gene relationships: from pseudogene evolution to their functional potentials.

Authors:  Travis S Johnson; Sihong Li; Jonathan R Kho; Kun Huang; Yan Zhang
Journal:  Pac Symp Biocomput       Date:  2018

7.  Transcriptome-wide effect of DE-ETIOLATED1 (DET1) suppression in embryogenic callus of Carica papaya.

Authors:  Nur Diyana Jamaluddin; Emelda Rosseleena Rohani; Normah Mohd Noor; Hoe-Han Goh
Journal:  J Plant Res       Date:  2019-01-16       Impact factor: 2.629

8.  Systems-level analysis of proteolytic events in increased vascular permeability and complement activation in skin inflammation.

Authors:  Ulrich auf dem Keller; Anna Prudova; Ulrich Eckhard; Barbara Fingleton; Christopher M Overall
Journal:  Sci Signal       Date:  2013-01-15       Impact factor: 8.192

9.  Machine learning-based differential network analysis: a study of stress-responsive transcriptomes in Arabidopsis.

Authors:  Chuang Ma; Mingming Xin; Kenneth A Feldmann; Xiangfeng Wang
Journal:  Plant Cell       Date:  2014-02-11       Impact factor: 11.277

10.  Comparative analysis of RNAi screening technologies at genome-scale reveals an inherent processing inefficiency of the plasmid-based shRNA hairpin.

Authors:  Bhavneet Bhinder; David Shum; Hakim Djaballah
Journal:  Comb Chem High Throughput Screen       Date:  2014-02       Impact factor: 1.339
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