Literature DB >> 15998662

Local modeling of global interactome networks.

Denise Scholtens1, Marc Vidal, Robert Gentleman.   

Abstract

MOTIVATION: Systems biology requires accurate models of protein complexes, including physical interactions that assemble and regulate these molecular machines. Yeast two-hybrid (Y2H) and affinity-purification/mass-spectrometry (AP-MS) technologies measure different protein-protein relationships, and issues of completeness, sensitivity and specificity fuel debate over which is best for high-throughput 'interactome' data collection. Static graphs currently used to model Y2H and AP-MS data neglect dynamic and spatial aspects of macromolecular complexes and pleiotropic protein function.
RESULTS: We apply the local modeling methodology proposed by Scholtens and Gentleman (2004) to two publicly available datasets and demonstrate its uses, interpretation and limitations. Specifically, we use this technology to address four major issues pertaining to protein-protein networks. (1) We motivate the need to move from static global interactome graphs to local protein complex models. (2) We formally show that accurate local interactome models require both Y2H and AP-MS data, even in idealized situations. (3) We briefly discuss experimental design issues and how bait selection affects interpretability of results. (4) We point to the implications of local modeling for systems biology including functional annotation, new complex prediction, pathway interactivity and coordination with gene-expression data. AVAILABILITY: The local modeling algorithm and all protein complex estimates reported here can be found in the R package apComplex, available at http://www.bioconductor.org CONTACT: dscholtens@northwestern.edu SUPPLEMENTARY INFORMATION: http://daisy.prevmed.northwestern.edu/~denise/pubs/LocalModeling

Mesh:

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Year:  2005        PMID: 15998662     DOI: 10.1093/bioinformatics/bti567

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


  24 in total

1.  A general pipeline for quality and statistical assessment of protein interaction data using R and Bioconductor.

Authors:  Tony Chiang; Denise Scholtens
Journal:  Nat Protoc       Date:  2009-03-26       Impact factor: 13.491

2.  Discovery of protein complexes with core-attachment structures from Tandem Affinity Purification (TAP) data.

Authors:  Min Wu; Xiao-Li Li; Chee-Keong Kwoh; See-Kiong Ng; Limsoon Wong
Journal:  J Comput Biol       Date:  2011-07-21       Impact factor: 1.479

3.  Charting the landscape of tandem BRCT domain-mediated protein interactions.

Authors:  Nicholas T Woods; Rafael D Mesquita; Michael Sweet; Marcelo A Carvalho; Xueli Li; Yun Liu; Huey Nguyen; C Eric Thomas; Edwin S Iversen; Sylvia Marsillac; Rachel Karchin; John Koomen; Alvaro N A Monteiro
Journal:  Sci Signal       Date:  2012-09-18       Impact factor: 8.192

Review 4.  Algorithmic and analytical methods in network biology.

Authors:  Mehmet Koyutürk
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2010 May-Jun

5.  Comparative analysis of Saccharomyces cerevisiae WW domains and their interacting proteins.

Authors:  Jay R Hesselberth; John P Miller; Anna Golob; Jason E Stajich; Gregory A Michaud; Stanley Fields
Journal:  Genome Biol       Date:  2006-04-10       Impact factor: 13.583

6.  Mapping the NPHP-JBTS-MKS protein network reveals ciliopathy disease genes and pathways.

Authors:  Liyun Sang; Julie J Miller; Kevin C Corbit; Rachel H Giles; Matthew J Brauer; Edgar A Otto; Lisa M Baye; Xiaohui Wen; Suzie J Scales; Mandy Kwong; Erik G Huntzicker; Mindan K Sfakianos; Wendy Sandoval; J Fernando Bazan; Priya Kulkarni; Francesc R Garcia-Gonzalo; Allen D Seol; John F O'Toole; Susanne Held; Heiko M Reutter; William S Lane; Muhammad Arshad Rafiq; Abdul Noor; Muhammad Ansar; Akella Radha Rama Devi; Val C Sheffield; Diane C Slusarski; John B Vincent; Daniel A Doherty; Friedhelm Hildebrandt; Jeremy F Reiter; Peter K Jackson
Journal:  Cell       Date:  2011-05-13       Impact factor: 41.582

7.  High-quality binary protein interaction map of the yeast interactome network.

Authors:  Haiyuan Yu; Pascal Braun; Muhammed A Yildirim; Irma Lemmens; Kavitha Venkatesan; Julie Sahalie; Tomoko Hirozane-Kishikawa; Fana Gebreab; Na Li; Nicolas Simonis; Tong Hao; Jean-François Rual; Amélie Dricot; Alexei Vazquez; Ryan R Murray; Christophe Simon; Leah Tardivo; Stanley Tam; Nenad Svrzikapa; Changyu Fan; Anne-Sophie de Smet; Adriana Motyl; Michael E Hudson; Juyong Park; Xiaofeng Xin; Michael E Cusick; Troy Moore; Charlie Boone; Michael Snyder; Frederick P Roth; Albert-László Barabási; Jan Tavernier; David E Hill; Marc Vidal
Journal:  Science       Date:  2008-08-21       Impact factor: 47.728

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.  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

10.  Identifying the topology of protein complexes from affinity purification assays.

Authors:  Caroline C Friedel; Ralf Zimmer
Journal:  Bioinformatics       Date:  2009-06-08       Impact factor: 6.937

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