ProRank: a method for detecting protein complexes

Detecting protein complexes from protein-protein interaction (PPI) network is becoming a difficult challenge in computational biology. Observations show that genes causing the same or similar diseases tend to lie close to one another in a network of protein-protein or functional interactions. This paper introduces a novel method for detecting protein-complexes from PPI by using a protein ranking algorithm (ProRank) and incorporating an evolutionary relationships between proteins in the network. The method successfully predicted 57 out of 81 benchmarked protein complexes created from the Munich Information Center for Protein Sequence (MIPS). The level of the accuracy achieved using ProRank in comparison to other recent methods for detecting protein complexes is a strong argument in favor of our proposed method. Datasets, programs and results are available at http://faculty.uaeu.ac.ae/nzaki/ProRank.htm.

[1]  Jacques van Helden,et al.  Evaluation of clustering algorithms for protein-protein interaction networks , 2006, BMC Bioinformatics.

[2]  Sean R. Collins,et al.  Global landscape of protein complexes in the yeast Saccharomyces cerevisiae , 2006, Nature.

[3]  Limsoon Wong,et al.  Using Indirect protein-protein Interactions for protein Complex Prediction , 2008, J. Bioinform. Comput. Biol..

[4]  Guimei Liu,et al.  Complex discovery from weighted PPI networks , 2009, Bioinform..

[5]  James R. Knight,et al.  A comprehensive analysis of protein–protein interactions in Saccharomyces cerevisiae , 2000, Nature.

[6]  Illés J. Farkas,et al.  CFinder: locating cliques and overlapping modules in biological networks , 2006, Bioinform..

[7]  Ba Di Ya,et al.  Matrix Analysis , 2011 .

[8]  P. Bork,et al.  Proteome survey reveals modularity of the yeast cell machinery , 2006, Nature.

[9]  Nazar Zaki,et al.  Protein-protein interaction based on pairwise similarity , 2009, BMC Bioinformatics.

[10]  D. Lipman,et al.  Improved tools for biological sequence comparison. , 1988, Proceedings of the National Academy of Sciences of the United States of America.

[11]  Gary D Bader,et al.  Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry , 2002, Nature.

[12]  Jason Weston,et al.  Motif-based protein ranking by network propagation , 2005, Bioinform..

[13]  Igor Jurisica,et al.  Protein complex prediction via cost-based clustering , 2004, Bioinform..

[14]  Siu-Ming Yiu,et al.  Predicting Protein Complexes from PPI Data: A Core-Attachment Approach , 2009, J. Comput. Biol..

[15]  Limsoon Wong,et al.  Exploiting indirect neighbours and topological weight to predict protein function from protein--protein interactions , 2006 .

[16]  Charles R. Johnson,et al.  Matrix analysis , 1985, Statistical Inference for Engineers and Data Scientists.

[17]  Sergey Brin,et al.  The Anatomy of a Large-Scale Hypertextual Web Search Engine , 1998, Comput. Networks.

[18]  S. Dongen Graph clustering by flow simulation , 2000 .

[19]  Dmitrij Frishman,et al.  MIPS: analysis and annotation of proteins from whole genomes in 2005 , 2006, Nucleic Acids Res..

[20]  Kurt Bryan,et al.  The $25,000,000,000 Eigenvector: The Linear Algebra behind Google , 2006, SIAM Rev..

[21]  R. Ozawa,et al.  A comprehensive two-hybrid analysis to explore the yeast protein interactome , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[22]  Dmitrij Frishman,et al.  MIPS: analysis and annotation of proteins from whole genomes in 2005 , 2005, Nucleic Acids Res..

[23]  Roberto Tempo,et al.  A distributed randomized approach for the PageRank computation: Part 1 , 2008, 2008 47th IEEE Conference on Decision and Control.

[24]  Tatsuya Akutsu,et al.  Protein homology detection using string alignment kernels , 2004, Bioinform..

[25]  Gary D. Bader,et al.  An automated method for finding molecular complexes in large protein interaction networks , 2003, BMC Bioinformatics.

[26]  Chee Keong Kwoh,et al.  Construction of co-complex score matrix for protein complex prediction from AP-MS data , 2011, Bioinform..

[27]  Nazar Zaki,et al.  Conotoxin protein classification using free scores of words and support vector machines , 2011, BMC Bioinformatics.

[28]  Dmitrij Frishman,et al.  MIPS: a database for genomes and protein sequences , 1999, Nucleic Acids Res..

[29]  M S Waterman,et al.  Identification of common molecular subsequences. , 1981, Journal of molecular biology.

[30]  P. Bork,et al.  Functional organization of the yeast proteome by systematic analysis of protein complexes , 2002, Nature.

[31]  Roded Sharan,et al.  Identification of protein complexes from co-immunoprecipitation data , 2011, Bioinform..

[32]  Igor Jurisica,et al.  Functional topology in a network of protein interactions , 2004, Bioinform..

[33]  David Martin,et al.  Functional classification of proteins for the prediction of cellular function from a protein-protein interaction network , 2003, Genome Biology.

[34]  R. Rosenfeld Nature , 2009, Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery.