Literature DB >> 16473872

CFinder: locating cliques and overlapping modules in biological networks.

Balázs Adamcsek1, Gergely Palla, Illés J Farkas, Imre Derényi, Tamás Vicsek.   

Abstract

UNLABELLED: Most cellular tasks are performed not by individual proteins, but by groups of functionally associated proteins, often referred to as modules. In a protein association network modules appear as groups of densely interconnected nodes, also called communities or clusters. These modules often overlap with each other and form a network of their own, in which nodes (links) represent the modules (overlaps). We introduce CFinder, a fast program locating and visualizing overlapping, densely interconnected groups of nodes in undirected graphs, and allowing the user to easily navigate between the original graph and the web of these groups. We show that in gene (protein) association networks CFinder can be used to predict the function(s) of a single protein and to discover novel modules. CFinder is also very efficient for locating the cliques of large sparse graphs. AVAILABILITY: CFinder (for Windows, Linux and Macintosh) and its manual can be downloaded from http://angel.elte.hu/clustering. SUPPLEMENTARY INFORMATION: Supplementary data are available on Bioinformatics online.

Mesh:

Substances:

Year:  2006        PMID: 16473872     DOI: 10.1093/bioinformatics/btl039

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


  220 in total

Review 1.  Profiling of protein interaction networks of protein complexes using affinity purification and quantitative mass spectrometry.

Authors:  Robyn M Kaake; Xiaorong Wang; Lan Huang
Journal:  Mol Cell Proteomics       Date:  2010-05-05       Impact factor: 5.911

2.  MIPCE: an MI-based protein complex extraction technique.

Authors:  Priyakshi Mahanta; Dhruba Kr Bhattacharyya; Ashish Ghosh
Journal:  J Biosci       Date:  2015-10       Impact factor: 1.826

3.  An automated approach to network features of protein structure ensembles.

Authors:  Moitrayee Bhattacharyya; Chanda R Bhat; Saraswathi Vishveshwara
Journal:  Protein Sci       Date:  2013-10       Impact factor: 6.725

4.  Understanding protein structure from a percolation perspective.

Authors:  Dhruba Deb; Saraswathi Vishveshwara; Smitha Vishveshwara
Journal:  Biophys J       Date:  2009-09-16       Impact factor: 4.033

5.  PLW: Probabilistic Local Walks for detecting protein complexes from protein interaction networks.

Authors:  Daniel Wong; Xiao-Li Li; Min Wu; Jie Zheng; See-Kiong Ng
Journal:  BMC Genomics       Date:  2013-10-16       Impact factor: 3.969

6.  Dancing through Life: Molecular Dynamics Simulations and Network-Centric Modeling of Allosteric Mechanisms in Hsp70 and Hsp110 Chaperone Proteins.

Authors:  Gabrielle Stetz; Gennady M Verkhivker
Journal:  PLoS One       Date:  2015-11-30       Impact factor: 3.240

7.  Cohesive versus flexible evolution of functional modules in eukaryotes.

Authors:  Like Fokkens; Berend Snel
Journal:  PLoS Comput Biol       Date:  2009-01-30       Impact factor: 4.475

8.  RRW: repeated random walks on genome-scale protein networks for local cluster discovery.

Authors:  Kathy Macropol; Tolga Can; Ambuj K Singh
Journal:  BMC Bioinformatics       Date:  2009-09-09       Impact factor: 3.169

9.  Network-assisted protein identification and data interpretation in shotgun proteomics.

Authors:  Jing Li; Lisa J Zimmerman; Byung-Hoon Park; David L Tabb; Daniel C Liebler; Bing Zhang
Journal:  Mol Syst Biol       Date:  2009-08-18       Impact factor: 11.429

10.  Protein complex identification by supervised graph local clustering.

Authors:  Yanjun Qi; Fernanda Balem; Christos Faloutsos; Judith Klein-Seetharaman; Ziv Bar-Joseph
Journal:  Bioinformatics       Date:  2008-07-01       Impact factor: 6.937

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.