Supervised learning and prediction of physical interactions between human and HIV proteins.

ABSTRACT:

Background

Infectious diseases result in millions of deaths each year. Physical interactions between pathogen and host proteins often form the basis of such infections. While a number of methods have been proposed for predicting protein-protein interactions (PPIs), they have primarily focused on intra-species protein-protein interactions.

Methodology

We present an application of a supervised learning method for predicting physical interactions between host and pathogen proteins, using the human-HIV system. Using a Support Vector Machine with a linear kernel, we explore the use of a number of features including domain profiles, protein sequence k-mers, and properties of human proteins in a human PPI network. We achieve the best cross-validation performance when we use a combi

SUBMITTER: Dyer MD 

PROVIDER: S-EPMC3134873 | biostudies-literature | 2011 Jul

REPOSITORIES: biostudies-literature