Literature DB >> 17720984

Tools for visually exploring biological networks.

Matthew Suderman1, Michael Hallett.   

Abstract

UNLABELLED: Many tools exist for visually exploring biological networks including well-known examples such as Cytoscape, VisANT, Pathway Studio and Patika. These systems play a key role in the development of integrative biology, systems biology and integrative bioinformatics. The trend in the development of these tools is to go beyond 'static' representations of cellular state, towards a more dynamic model of cellular processes through the incorporation of gene expression data, subcellular localization information and time-dependent behavior. We provide a comprehensive review of the relative advantages and disadvantages of existing systems with two goals in mind: to aid researchers in efficiently identifying the appropriate existing tools for data visualization; to describe the necessary and realistic goals for the next generation of visualization tools. In view of the first goal, we provide in the Supplementary Material a systematic comparison of more than 35 existing tools in terms of over 25 different features. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Mesh:

Substances:

Year:  2007        PMID: 17720984     DOI: 10.1093/bioinformatics/btm401

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


  74 in total

1.  gViz, a novel tool for the visualization of co-expression networks.

Authors:  Raphaël Helaers; Eric Bareke; Bertrand De Meulder; Michael Pierre; Sophie Depiereux; Naji Habra; Eric Depiereux
Journal:  BMC Res Notes       Date:  2011-10-27

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.  Creating interactive, web-based and data-enriched maps with the Systems Biology Graphical Notation.

Authors:  Astrid Junker; Hendrik Rohn; Tobias Czauderna; Christian Klukas; Anja Hartmann; Falk Schreiber
Journal:  Nat Protoc       Date:  2012-03-01       Impact factor: 13.491

4.  Topological analysis and interactive visualization of biological networks and protein structures.

Authors:  Nadezhda T Doncheva; Yassen Assenov; Francisco S Domingues; Mario Albrecht
Journal:  Nat Protoc       Date:  2012-03-15       Impact factor: 13.491

5.  Detection of locally over-represented GO terms in protein-protein interaction networks.

Authors:  Mathieu Lavallée-Adam; Benoit Coulombe; Mathieu Blanchette
Journal:  J Comput Biol       Date:  2010-03       Impact factor: 1.479

6.  Mapping plant interactomes using literature curated and predicted protein-protein interaction data sets.

Authors:  KiYoung Lee; David Thorneycroft; Premanand Achuthan; Henning Hermjakob; Trey Ideker
Journal:  Plant Cell       Date:  2010-04-06       Impact factor: 11.277

7.  EINVis: a visualization tool for analyzing and exploring genetic interactions in large-scale association studies.

Authors:  Yubao Wu; Xiaofeng Zhu; Jian Chen; Xiang Zhang
Journal:  Genet Epidemiol       Date:  2013-08-11       Impact factor: 2.135

8.  Arabidopsis reactome: a foundation knowledgebase for plant systems biology.

Authors:  Nicolas Tsesmetzis; Matthew Couchman; Janet Higgins; Alison Smith; John H Doonan; Georg J Seifert; Esther E Schmidt; Imre Vastrik; Ewan Birney; Guanming Wu; Peter D'Eustachio; Lincoln D Stein; Richard J Morris; Michael W Bevan; Sean V Walsh
Journal:  Plant Cell       Date:  2008-06-30       Impact factor: 11.277

9.  VisANT: an integrative framework for networks in systems biology.

Authors:  Zhenjun Hu; Evan S Snitkin; Charles DeLisi
Journal:  Brief Bioinform       Date:  2008-05-07       Impact factor: 11.622

10.  Graphle: Interactive exploration of large, dense graphs.

Authors:  Curtis Huttenhower; Sajid O Mehmood; Olga G Troyanskaya
Journal:  BMC Bioinformatics       Date:  2009-12-14       Impact factor: 3.169

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