PPI_SVM: prediction of protein-protein interactions using machine learning, domain-domain affinities and frequency tables.

ABSTRACT: Protein-protein interactions (PPI) control most of the biological processes in a living cell. In order to fully understand protein functions, a knowledge of protein-protein interactions is necessary. Prediction of PPI is challenging, especially when the three-dimensional structure of interacting partners is not known. Recently, a novel prediction method was proposed by exploiting physical interactions of constituent domains. We propose here a novel knowledge-based prediction method, namely PPI_SVM, which predicts interactions between two protein sequences by exploiting their domain information. We trained a two-class support vector machine on the benchmarking set of pairs of interacting proteins extracted from the Database of Interacting Proteins (DIP). The method considers all possible co

SUBMITTER: Chatterjee P 

PROVIDER: S-EPMC6275787 | biostudies-literature | 2011 Jun

REPOSITORIES: biostudies-literature