Literature DB >> 16108720

Identification of protein complexes by comparative analysis of yeast and bacterial protein interaction data.

Roded Sharan1, Trey Ideker, Brian Kelley, Ron Shamir, Richard M Karp.   

Abstract

Mounting evidence shows that many protein complexes are conserved in evolution. Here we use conservation to find complexes that are common to the yeast S. cerevisiae and the bacteria H. pylori. Our analysis combines protein interaction data that are available for each of the two species and orthology information based on protein sequence comparison. We develop a detailed probabilistic model for protein complexes in a single species and a model for the conservation of complexes between two species. Using these models, one can recast the question of finding conserved complexes as a problem of searching for heavy subgraphs in an edge- and node-weighted graph, whose nodes are orthologous protein pairs. We tested this approach on the data currently available for yeast and bacteria and detected 11 significantly conserved complexes. Several of these complexes match very well with prior experimental knowledge on complexes in yeast only and serve for validation of our methodology. The complexes suggest new functions for a variety of uncharacterized proteins. By identifying a conserved complex whose yeast proteins function predominantly in the nuclear pore complex, we propose that the corresponding bacterial proteins function as a coherent cellular membrane transport system. We also compare our results to two alternative methods for detecting complexes and demonstrate that our methodology obtains a much higher specificity.

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Year:  2005        PMID: 16108720     DOI: 10.1089/cmb.2005.12.835

Source DB:  PubMed          Journal:  J Comput Biol        ISSN: 1066-5277            Impact factor:   1.479


  44 in total

1.  Graemlin: general and robust alignment of multiple large interaction networks.

Authors:  Jason Flannick; Antal Novak; Balaji S Srinivasan; Harley H McAdams; Serafim Batzoglou
Journal:  Genome Res       Date:  2006-08-09       Impact factor: 9.043

2.  Cross-species analysis of biological networks by Bayesian alignment.

Authors:  Johannes Berg; Michael Lässig
Journal:  Proc Natl Acad Sci U S A       Date:  2006-07-11       Impact factor: 11.205

3.  A probabilistic model of neutral and selective dynamics of protein network evolution.

Authors:  Janusz Dutkowski; Jerzy Tiuryn
Journal:  J Comput Biol       Date:  2013-08-09       Impact factor: 1.479

4.  Automatic parameter learning for multiple local network alignment.

Authors:  Jason Flannick; Antal Novak; Chuong B Do; Balaji S Srinivasan; Serafim Batzoglou
Journal:  J Comput Biol       Date:  2009-08       Impact factor: 1.479

Review 5.  Integrative approaches for finding modular structure in biological networks.

Authors:  Koyel Mitra; Anne-Ruxandra Carvunis; Sanath Kumar Ramesh; Trey Ideker
Journal:  Nat Rev Genet       Date:  2013-10       Impact factor: 53.242

6.  Inferring protein function by domain context similarities in protein-protein interaction networks.

Authors:  Song Zhang; Hu Chen; Ke Liu; Zhirong Sun
Journal:  BMC Bioinformatics       Date:  2009-12-02       Impact factor: 3.169

7.  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

8.  A genome-wide screen for essential yeast genes that affect telomere length maintenance.

Authors:  Lior Ungar; Nir Yosef; Yael Sela; Roded Sharan; Eytan Ruppin; Martin Kupiec
Journal:  Nucleic Acids Res       Date:  2009-04-22       Impact factor: 16.971

9.  Associating genes and protein complexes with disease via network propagation.

Authors:  Oron Vanunu; Oded Magger; Eytan Ruppin; Tomer Shlomi; Roded Sharan
Journal:  PLoS Comput Biol       Date:  2010-01-15       Impact factor: 4.475

10.  Local network topology in human protein interaction data predicts functional association.

Authors:  Hua Li; Shoudan Liang
Journal:  PLoS One       Date:  2009-07-29       Impact factor: 3.240

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