Adv Biochem Eng Biotechnol. 2008;110:247-67.

Computational methods for predicting protein-protein interactions.

Pitre S, Alamgir M, Green JR, Dumontier M, Dehne F, Golshani A.

Source

School of Computer Science, Carleton University, 5304 Herzberg Building, 1125 Colonel By Drive, K1S 5B6, Ottawa, Ontario, Canada.

Abstract

Protein-protein interactions (PPIs) play a critical role in many cellular functions. A number of experimental techniques have been applied to discover PPIs; however, these techniques are expensive in terms of time, money, and expertise. There are also large discrepancies between the PPI data collected by the same or different techniques in the same organism. We therefore turn to computational techniques for the prediction of PPIs. Computational techniques have been applied to the collection, indexing, validation, analysis, and extrapolation of PPI data. This chapter will focus on computational prediction of PPI, reviewing a number of techniques including PIPE, developed in our own laboratory. For comparison, the conventional large-scale approaches to predict PPIs are also briefly discussed. The chapter concludes with a discussion of the limitations of both experimental and computational methods of determining PPIs.

PMID:: 18202838; [PubMed - indexed for MEDLINE]

Publication Types, MeSH Terms, Substances

Publication Types

Review

MeSH Terms

Substances

Proteome

LinkOut - more resources

Full Text Sources

Other Literature Sources

COS Scholar Universe

Supplemental Content

Save items

Related citations in PubMed

Review Using product kernels to predict protein interactions. [Adv Biochem Eng Biotechnol. 2008]
Review Using product kernels to predict protein interactions.
Martin S, Brown WM, Faulon JL. Adv Biochem Eng Biotechnol. 2008; 110:215-45.
Large-scale Protein-Protein Interaction prediction using novel kernel methods. [Int J Data Min Bioinform. 2008]
Large-scale Protein-Protein Interaction prediction using novel kernel methods.
Chen XW, Han B, Fang J, Haasl RJ. Int J Data Min Bioinform. 2008; 2(2):145-56.
Discovering functional interaction patterns in protein-protein interaction networks. [BMC Bioinformatics. 2008]
Discovering functional interaction patterns in protein-protein interaction networks.
Turanalp ME, Can T. BMC Bioinformatics. 2008 Jun 11; 9:276. Epub 2008 Jun 11.
Improving protein protein interaction prediction based on phylogenetic information using a least-squares support vector machine. [Ann N Y Acad Sci. 2007]
Improving protein protein interaction prediction based on phylogenetic information using a least-squares support vector machine.
Craig RA, Liao L. Ann N Y Acad Sci. 2007 Dec; 1115:154-67. Epub 2007 Oct 9.
Review Prediction of protein-protein interaction networks. [Curr Protoc Bioinformatics. 2008]
Review Prediction of protein-protein interaction networks.
Gomez SM, Choi K, Wu Y. Curr Protoc Bioinformatics. 2008 Jun; Chapter 8:Unit 8.2.

See reviews... See all...

Cited by 4 PubMed Central articles

Recent advances in clustering methods for protein interaction networks. [BMC Genomics. 2010]
Recent advances in clustering methods for protein interaction networks.
Wang J, Li M, Deng Y, Pan Y. BMC Genomics. 2010 Dec 1; 11 Suppl 3:S10. Epub 2010 Dec 1.
Open source tool for prediction of genome wide protein-protein interaction network based on ortholog information. [Source Code Biol Med. 2010]
Open source tool for prediction of genome wide protein-protein interaction network based on ortholog information.
Pedamallu CS, Posfai J. Source Code Biol Med. 2010 Aug 4; 5:8. Epub 2010 Aug 4.
Functional classification of proteins based on projection of amino acid sequences: application for prediction of protein kinase substrates. [BMC Bioinformatics. 2010]
Functional classification of proteins based on projection of amino acid sequences: application for prediction of protein kinase substrates.
Sobolev B, Filimonov D, Lagunin A, Zakharov A, Koborova O, Kel A, Poroikov V. BMC Bioinformatics. 2010 Jun 10; 11:313. Epub 2010 Jun 10.

See all...

Related information

Related Citations
Calculated set of PubMed citations closely related to the selected article(s) retrieved using a word weight algorithm. Related articles are displayed in ranked order from most to least relevant, with the “linked from” citation displayed first.
Cited in PMC
Full-text articles in the PubMed Central Database that cite the current articles.

Recent activity

Clear Turn Off Turn On

Computational methods for predicting protein-protein interactions.
Computational methods for predicting protein-protein interactions.
Adv Biochem Eng Biotechnol. 2008 ;110:247-67.

PubMed
The proteasome subunit PSMA7 located on the 20q13 amplicon is overexpressed and ...
The proteasome subunit PSMA7 located on the 20q13 amplicon is overexpressed and associated with liver metastasis in colorectal cancer.
Oncol Rep. 2008 Feb ;19(2):441-6.

PubMed
Down-regulation of androgen-receptor and PSA by phytochemicals.
Down-regulation of androgen-receptor and PSA by phytochemicals.
Int J Oncol. 2008 Feb ;32(2):405-11.

PubMed
The Genetic Activity Profile database.
The Genetic Activity Profile database.
Environ Health Perspect. 1991 Dec ;96:41-5.

PubMed
Overexpression of ABCA1 reduces amyloid deposition in the PDAPP mouse model of A...
Overexpression of ABCA1 reduces amyloid deposition in the PDAPP mouse model of Alzheimer disease.
J Clin Invest. 2008 Feb ;118(2):671-82.

PubMed

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

PubMed

Result Filters

Display Settings:

Send to: