Computational Methods for Prediction of Protein-Protein Interactions: PPI Prediction Methods

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Author(s): Sneha Rai (Netaji Subhas Institute of Technology, India)and Sonika Bhatnagar (Netaji Subhas Institute of Technology, India)
Copyright: 2016
Pages: 32
Source title: Handbook of Research on Computational Intelligence Applications in Bioinformatics
Source Author(s)/Editor(s): Sujata Dash (North Orissa University, India)and Bidyadhar Subudhi (National Institute of Technology, India)
DOI: 10.4018/978-1-5225-0427-6.ch010

Keywords: Artificial Intelligence / Bioinformatics / Computer Science & IT / Medical Information Science Reference

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Abstract

The key signaling pathways in cellular processes involve protein-protein interactions (PPIs). A perturbation in the balance of PPIs occurs in various pathophysiological processes. There are a large numbers of experimental methods for detection of PPIs. However, experimental PPI determination is time consuming, expensive, error prone and does not effectively cover transient interactions. Therefore, overlaying and integration of predictive methods with experimental results provides statistical robustness and biological significance to the PPI data. In this chapter, the authors describe PPIs in terms of types, importance, and biological consequences. This chapter also provides a comprehensive description on various computational approaches for PPI prediction. Prediction of PPI can be done through: 1) Genomic information based methods 2) Structure based methods 3) Network topology based methods: 4) Literature and data mining based methods 5) Machine learning methods. For ease of use and convenience, a summary of various databases and software for PPI prediction has been provided.

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