Literature DB >> 18802442

Network Analysis Tools: from biological networks to clusters and pathways.

Sylvain Brohée1, Karoline Faust, Gipsi Lima-Mendez, Gilles Vanderstocken, Jacques van Helden.   

Abstract

Network Analysis Tools (NeAT) is a suite of computer tools that integrate various algorithms for the analysis of biological networks: comparison between graphs, between clusters, or between graphs and clusters; network randomization; analysis of degree distribution; network-based clustering and path finding. The tools are interconnected to enable a stepwise analysis of the network through a complete analytical workflow. In this protocol, we present a typical case of utilization, where the tasks above are combined to decipher a protein-protein interaction network retrieved from the STRING database. The results returned by NeAT are typically subnetworks, networks enriched with additional information (i.e., clusters or paths) or tables displaying statistics. Typical networks comprising several thousands of nodes and arcs can be analyzed within a few minutes. The complete protocol can be read and executed in approximately 1 h.

Mesh:

Year:  2008        PMID: 18802442     DOI: 10.1038/nprot.2008.100

Source DB:  PubMed          Journal:  Nat Protoc        ISSN: 1750-2799            Impact factor:   13.491


  41 in total

1.  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

2.  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

3.  Rapid immunoprecipitation mass spectrometry of endogenous proteins (RIME) for analysis of chromatin complexes.

Authors:  Hisham Mohammed; Christopher Taylor; Gordon D Brown; Evaggelia K Papachristou; Jason S Carroll; Clive S D'Santos
Journal:  Nat Protoc       Date:  2016-01-21       Impact factor: 13.491

Review 4.  Structure and dynamics of molecular networks: a novel paradigm of drug discovery: a comprehensive review.

Authors:  Peter Csermely; Tamás Korcsmáros; Huba J M Kiss; Gábor London; Ruth Nussinov
Journal:  Pharmacol Ther       Date:  2013-02-04       Impact factor: 12.310

5.  Reprogramming of miRNA networks in cancer and leukemia.

Authors:  Stefano Volinia; Marco Galasso; Stefan Costinean; Luca Tagliavini; Giacomo Gamberoni; Alessandra Drusco; Jlenia Marchesini; Nicoletta Mascellani; Maria Elena Sana; Ramzey Abu Jarour; Caroline Desponts; Michael Teitell; Raffaele Baffa; Rami Aqeilan; Marilena V Iorio; Cristian Taccioli; Ramiro Garzon; Gianpiero Di Leva; Muller Fabbri; Marco Catozzi; Maurizio Previati; Stefan Ambs; Tiziana Palumbo; Michela Garofalo; Angelo Veronese; Arianna Bottoni; Pierluigi Gasparini; Curtis C Harris; Rosa Visone; Yuri Pekarsky; Albert de la Chapelle; Mark Bloomston; Mary Dillhoff; Laura Z Rassenti; Thomas J Kipps; Kay Huebner; Flavia Pichiorri; Dido Lenze; Stefano Cairo; Marie-Annick Buendia; Pascal Pineau; Anne Dejean; Nicola Zanesi; Simona Rossi; George A Calin; Chang-Gong Liu; Jeff Palatini; Massimo Negrini; Andrea Vecchione; Anne Rosenberg; Carlo M Croce
Journal:  Genome Res       Date:  2010-05       Impact factor: 9.043

6.  NetComm: a network analysis tool based on communicability.

Authors:  Ian M Campbell; Regis A James; Edward S Chen; Chad A Shaw
Journal:  Bioinformatics       Date:  2014-08-13       Impact factor: 6.937

7.  Metabolome and fecal microbiota in monozygotic twin pairs discordant for weight: a Big Mac challenge.

Authors:  Isabel Bondia-Pons; Johanna Maukonen; Ismo Mattila; Aila Rissanen; Maria Saarela; Jaakko Kaprio; Antti Hakkarainen; Jesper Lundbom; Nina Lundbom; Tuulia Hyötyläinen; Kirsi H Pietiläinen; Matej Orešič
Journal:  FASEB J       Date:  2014-05-20       Impact factor: 5.191

Review 8.  Disruption of small molecule transporter systems by Transporter-Interfering Chemicals (TICs).

Authors:  Sascha C T Nicklisch; Amro Hamdoun
Journal:  FEBS Lett       Date:  2020-12-09       Impact factor: 4.124

9.  Protein network prediction and topological analysis in Leishmania major as a tool for drug target selection.

Authors:  Andrés F Flórez; Daeui Park; Jong Bhak; Byoung-Chul Kim; Allan Kuchinsky; John H Morris; Jairo Espinosa; Carlos Muskus
Journal:  BMC Bioinformatics       Date:  2010-09-27       Impact factor: 3.169

10.  Identification of microRNA activity by Targets' Reverse EXpression.

Authors:  Stefano Volinia; Rosa Visone; Marco Galasso; Elda Rossi; Carlo M Croce
Journal:  Bioinformatics       Date:  2009-11-06       Impact factor: 6.937

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