Exploiting amino acid composition for predicting protein-protein interactions

PLoS ONE

Volumn 4, Issue 11, 2009, Pages

  Roy, Sushmita ^a   Martinez, Diego ^b   Platero, Harriett ^b   Lane, Terran ^b   Werner Washburne, Margaret ^b  

^a MSC01 1070   (United States)

^b UNIVERSITY OF NEW MEXICO   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACTIN; PROTEOME; AMINO ACID; FUNGAL PROTEIN; PROTEIN;

AMINO ACID COMPOSITION; ARTICLE; CELL BUDDING; CONTROLLED STUDY; DIMERIZATION; NONHUMAN; PROTEIN ANALYSIS; PROTEIN ASSEMBLY; PROTEIN DATABASE; PROTEIN DOMAIN; PROTEIN FUNCTION; PROTEIN LOCALIZATION; PROTEIN PROTEIN INTERACTION; ALGORITHM; ANIMAL; BIOLOGY; CAENORHABDITIS ELEGANS; CHEMISTRY; DROSOPHILA; METHODOLOGY; MOLECULAR EVOLUTION; OPEN READING FRAME; PROBABILITY; PROTEOMICS;

ALGORITHMS; AMINO ACIDS; ANIMALS; CAENORHABDITIS ELEGANS; COMPUTATIONAL BIOLOGY; DIMERIZATION; DROSOPHILA; EVOLUTION, MOLECULAR; FUNGAL PROTEINS; OPEN READING FRAMES; PROBABILITY; PROTEIN INTERACTION MAPPING; PROTEINS; PROTEOME; PROTEOMICS;

EID: 70949106297     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0007813     Document Type: Article

References (38)

1. Ito T, Tashiro K, Muta S, Ozawa R, Chiba T, et al. (2000) Toward a protein-protein interaction map of the budding yeast: A comprehensive system to examine two-hybrid interactions in all possible combinations between the yeast proteins. Proc Natl Acad Sci USA, 97;3.
2. Uetz P, Giot L, Cagney G, Mansfield TA, Judson RS, et al. (2000) A comprehensive analysis of protein-protein interactions in saccharomyces cerevisiae. Nature 403.
3. Krogan NJ, Cagney G, Yu H, Zhong G, Guo X, et al. (2006) Global landscape of protein complexes in the yeast saccharomyces cerevisiae. Nature 440.
4. Li S, Armstrong CM, Bertin N, Ge H, Milstein S, et al. (2004) A Map of the Interactome Network of the Metazoan C. elegans. Science 303: 540-543.
5. Yu H, Braun P, Yildirim MA, Lemmens I, Venkatesan K, et al. (2008) High-quality binary protein interaction map of the yeast interactome network. Science. pp 1158684+.
6. Simonis N, Rual JF, Carvunis AR, Tasan M, Lemmens I, et al. (2008) Empirically controlled mapping of the caenorhabditis elegans protein-protein interactome network. Nat Meth 6: 47-54.
7. Huang H, Bader JS (2009) Precision and recall estimates for two-hybrid screens. Bioinformatics (Oxford, England) 25: 372-378.
8. Shoemaker BA, Panchenko AR (2007) Deciphering protein-protein interactions. part i. experimental techniques and databases. PLOS Comput Biol 3;3.
9. Shoemaker BA, Panchenko AR (2007) Deciphering protein-protein interactions. part ii. computational methods to predict protein and domain interaction partners. PLOS Computat Biol 3;4.
10. Gomez SM, Noble WS, Rzhetsky A (2003) Learning to predict protein-protein interactions from protein sequences. Bioinformatics 19;15.
11. Sprinzak E, Margalit H (2001) Correlated sequence-signatures as markers of protein-protein interaction. J of Mol Biol 311(4).
12. Liu Y, Liu N, Zhao H (2005) Inferring protein-protein interactions through high-throughput interaction data from diverse organisms. Bioinformatics 21(5): 3279-3285.
13. Kann MG, Jothi R, Cherukuri PF, Przytycka TM (2007) Predicting protein domain interactions from coevolution of conserved regions. Proteins 67: 811-820.
14. Martin S, Roe D, Falon JL (2005) Predicting protein-protein interations using signature products. Bioinformatics 21(2): 218-226.
15. Sun J, Xu J, Liu Z, Liu Q, Zhao A, et al. (2005) Refined phylogenetic profiles method for predicting protein-protein interactions. Bioinformatics 21;16.
16. Jothi R, Przytycka TM, Aravind L (2007) Discovering functional linkages and uncharacterized cellular pathways using phylogenetic profile comparisons: a comprehensive assessment. BMC bioinformatics 8: 173+.
17. Jansen R, Yu H, Greenbaum D, Kluger Y, Krogan NJ, et al. (2003) A bayesian networks approach for predicting protein-protein interactions from genomic data. Science 302;449.
18. Jaimovich A, Elidan G, Margalit H, Friedman N (2006) Towards an integrated protein-protein interaction network: a relational markov network approach. J Comput Biol 13(2): 145-164.
19. Qiu J, Noble WS (2008) Predicting co-complexed protein pairs from heterogeneous data. PLoS computational biology 4.
20. Raghavachari B, Tasneem A, Przytycka TM, Jothi R (2008) Domine: a database of protein domain interactions. Nucleic acids research 36.
21. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, et al. (2000) Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 25: 25-29.
22. Gasch AP, Spellman PT, Kao CM, Carmel-Harel O, Eisen MB, et al. (2000) Genomic expression programs in the response of yeast cells to environmental changes. Mol Biol Cell. pp 4421-4257.
23. Werner-Washburne M, Wylie B, Boyack K, Fuge E, Galbraith J, et al. (2002) Comparative analysis of multiple genome-scale data sets. Genome Res 12: 1564-1573.
24. Mahdavi M, Lin YH (2007) False positive reduction in protein-protein interaction predictions using gene ontology annotations. BMC Bioinformatics 8: 262+.
25. Li R (1997) Bee1, a yeast protein with homology to wiscott-aldrich syndrome protein, is critical for the assembly of cortical actin cytoskeleton. J Cell Biol 136: 649-658.
26. Lee I, Lehner B, Crombie C, Wong W, Fraser A, et al. (2008) A single gene network accurately predicts phenotypic effects of gene perturbation in caenorhabditis elegans. Nature Genetics 40: 181-188.
27. Langley P, Iba W, Thompson K (1992) An analysis of bayesian classifiers. In: National Conference on Artificial Intelligence. pp. 223-228. URL citeseer. ist.psu.edu/langley92analysis.html.
28. Ofran Y, Rost B (2003) Analysing six types of protein-protein interfaces. J of Mol Biol 325; 2: 377-387.
29. Fong JH, Keating AE, Singh M (2004) Predicting specificity in bzip coiled-coil protein interactions. Genome Biol 5: R11.
30. Quevillon E, Silventoinen V, Pillai S, Harte N, Mulder N, et al. (2001) Interproscan: protein domains identifier. Nucleic Acids Res 33.
31. Nigam K, Lafferty J, McCallum A (1999) Using maximum entropy for text classification. In: IJCAI-99 Workshop on Machine Learning for Information Filtering. pp. 61-67. URL citeseer.ist.psu.edu/ nigam99using.html.
32. McCallum AK (2002) Mallet: A machine learning for language toolkit. Http://mallet.cs.umass.edu.
33. Witten IH, Frank E (2002) Data mining: practical machine learning tools and techniques with Java implementations. ACM SIGMOD Record 31: 76-77.
34. Joachims T (1999) Making large-scale support vector machine learning practical. In: Schölkopf B, Burges CJC, Smola AJ, editors, Advances in kernel methods: support vector learning, Cambridge, MA, USA: MIT Press. pp. 169-184.URL http://portal.acm.org/citation.cfm?id=299104.
35. Stark C, Breitkreutz BJ, Reguly T, Boucher L, Breitkreutz A, et al. (2006) Biogrid: a general repository for interaction datasets. Nucleic Acids Res 1;34.
36. Quevillon E, Silventoinen V, Pillai S, Harte N, Mulder N, et al. (2005) Interproscan: protein domains identifier. Nucl Acids Res 33: W116-120.
37. Ben-Hur A, Noble WS (2006) Choosing negative examples for the prediction of protein-protein interactions. BMC Bioinformatics 7.
38. Lasko TA, Bhagwat JG, Zou KH, Ohno-Machado L (2005) The use of receiver operating characteristic curves in biomedical informatics. J of Biomedical Informatics 38: 404-415.