Global Alignment of Pairwise Protein Interaction Networks for Maximal Common Conserved Patterns
Abstract
A number of tools for the alignment of protein-protein interaction (PPI) networks have laid the foundation for PPI network analysis. Most of alignment tools focus on finding conserved interaction regions across the PPI networks through either local or global mapping of similar sequences. Researchers are still trying to improve the speed, scalability, and accuracy of network alignment. In view of this, we introduce a connected-components based fast algorithm, HopeMap, for network alignment. Observing that the size of true orthologs across species is small comparing to the total number of proteins in all species, we take a different approach based on a precompiled list of homologs identified by KO terms. Applying this approach to S. cerevisiae (yeast) and D. melanogaster (fly), E. coli K12 and S. typhimurium , E. coli K12 and C. crescenttus , we analyze all clusters identified in the alignment. The results are evaluated through up-to-date known gene annotations, gene ontology (GO), and KEGG ortholog groups (KO). Comparing to existing tools, our approach is fast with linear computational cost, highly accurate in terms of KO and GO terms specificity and sensitivity, and can be extended to multiple alignments easily.
- Authors:
-
[1];
- School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
- Department of Computer and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA, Computer Science Department, North Carolina State University, Raleigh, NC 27696, USA
- Publication Date:
- Research Org.:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Biological and Environmental Research (BER). Biological Systems Science Division
- OSTI Identifier:
- 1227737
- Alternate Identifier(s):
- OSTI ID: 1626213
- Grant/Contract Number:
- DEAC05-00OR22725; AC05-00OR22725
- Resource Type:
- Published Article
- Journal Name:
- International Journal of Genomics
- Additional Journal Information:
- Journal Name: International Journal of Genomics Journal Volume: 2013; Journal ID: ISSN 2314-436X
- Publisher:
- Hindawi Publishing Corporation
- Country of Publication:
- Egypt
- Language:
- English
- Subject:
- 59 BASIC BIOLOGICAL SCIENCES; Biochemistry & Molecular Biology; Biotechnology & Applied Microbiology; Genetics & Heredity
Citation Formats
Tian, Wenhong, and Samatova, Nagiza F. Global Alignment of Pairwise Protein Interaction Networks for Maximal Common Conserved Patterns. Egypt: N. p., 2013.
Web. doi:10.1155/2013/670623.
Tian, Wenhong, & Samatova, Nagiza F. Global Alignment of Pairwise Protein Interaction Networks for Maximal Common Conserved Patterns. Egypt. https://doi.org/10.1155/2013/670623
Tian, Wenhong, and Samatova, Nagiza F. Tue .
"Global Alignment of Pairwise Protein Interaction Networks for Maximal Common Conserved Patterns". Egypt. https://doi.org/10.1155/2013/670623.
@article{osti_1227737,
title = {Global Alignment of Pairwise Protein Interaction Networks for Maximal Common Conserved Patterns},
author = {Tian, Wenhong and Samatova, Nagiza F.},
abstractNote = {A number of tools for the alignment of protein-protein interaction (PPI) networks have laid the foundation for PPI network analysis. Most of alignment tools focus on finding conserved interaction regions across the PPI networks through either local or global mapping of similar sequences. Researchers are still trying to improve the speed, scalability, and accuracy of network alignment. In view of this, we introduce a connected-components based fast algorithm, HopeMap, for network alignment. Observing that the size of true orthologs across species is small comparing to the total number of proteins in all species, we take a different approach based on a precompiled list of homologs identified by KO terms. Applying this approach to S. cerevisiae (yeast) and D. melanogaster (fly), E. coli K12 and S. typhimurium , E. coli K12 and C. crescenttus , we analyze all clusters identified in the alignment. The results are evaluated through up-to-date known gene annotations, gene ontology (GO), and KEGG ortholog groups (KO). Comparing to existing tools, our approach is fast with linear computational cost, highly accurate in terms of KO and GO terms specificity and sensitivity, and can be extended to multiple alignments easily.},
doi = {10.1155/2013/670623},
journal = {International Journal of Genomics},
number = ,
volume = 2013,
place = {Egypt},
year = {Tue Jan 01 00:00:00 EST 2013},
month = {Tue Jan 01 00:00:00 EST 2013}
}
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https://doi.org/10.1155/2013/670623
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Works referenced in this record:
Conserved patterns of protein interaction in multiple species
journal, February 2005
- Sharan, R.; Suthram, S.; Kelley, R. M.
- Proceedings of the National Academy of Sciences, Vol. 102, Issue 6
The FunCat, a functional annotation scheme for systematic classification of proteins from whole genomes
journal, October 2004
- Ruepp, A.
- Nucleic Acids Research, Vol. 32, Issue 18
Fast and Accurate Alignment of Multiple Protein Networks
journal, August 2009
- Kalaev, Maxim; Bafna, Vineet; Sharan, Roded
- Journal of Computational Biology, Vol. 16, Issue 8
Systematic identification of functional orthologs based on protein network comparison
journal, January 2006
- Bandyopadhyay, S.
- Genome Research, Vol. 16, Issue 3
The Yeast Protein Interaction Network Evolves Rapidly and Contains Few Redundant Duplicate Genes
journal, July 2001
- Wagner, Andreas
- Molecular Biology and Evolution, Vol. 18, Issue 7
Gene Ontology: tool for the unification of biology
journal, May 2000
- Ashburner, Michael; Ball, Catherine A.; Blake, Judith A.
- Nature Genetics, Vol. 25, Issue 1
Modeling cellular machinery through biological network comparison
journal, April 2006
- Sharan, Roded; Ideker, Trey
- Nature Biotechnology, Vol. 24, Issue 4
Automatic Parameter Learning for Multiple Local Network Alignment
journal, August 2009
- Flannick, Jason; Novak, Antal; Do, Chuong B.
- Journal of Computational Biology, Vol. 16, Issue 8
In silico Discovery of Enzyme–Substrate Specificity-determining Residue Clusters
journal, October 2005
- Yu, Gong-Xin; Park, Byung-Hoon; Chandramohan, Praveen
- Journal of Molecular Biology, Vol. 352, Issue 5
Conserved pathways within bacteria and yeast as revealed by global protein network alignment
journal, September 2003
- Kelley, B. P.; Sharan, R.; Karp, R. M.
- Proceedings of the National Academy of Sciences, Vol. 100, Issue 20
Specificity and Stability in Topology of Protein Networks
journal, May 2002
- Maslov, S.
- Science, Vol. 296, Issue 5569
A Note on the Calculation of Empirical P Values from Monte Carlo Procedures
journal, August 2002
- North, B. V.; Curtis, D.; Sham, P. C.
- The American Journal of Human Genetics, Vol. 71, Issue 2
From pull-down data to protein interaction networks and complexes with biological relevance
journal, February 2008
- Zhang, B.; Park, B. -H.; Karpinets, T.
- Bioinformatics, Vol. 24, Issue 7
KEGG: Kyoto Encyclopedia of Genes and Genomes
journal, January 2000
- Kanehisa, Minoru; Goto, Susumu
- Nucleic Acids Research, Vol. 28, Issue 1, p. 27-30
MIPS: analysis and annotation of proteins from whole genomes
journal, January 2004
- Mewes, H. W.
- Nucleic Acids Research, Vol. 32, Issue 90001
Graemlin: General and robust alignment of multiple large interaction networks
journal, August 2006
- Flannick, J.
- Genome Research, Vol. 16, Issue 9
Automatic clustering of orthologs and in-paralogs from pairwise species comparisons
journal, December 2001
- Remm, Maido; Storm, Christian E. V.; Sonnhammer, Erik L. L.
- Journal of Molecular Biology, Vol. 314, Issue 5