Incorporating the type and direction information in predicting novel regulatory interactions between HIV-1 and human proteins using a biclustering approach.

ABSTRACT:

Background

Discovering novel interactions between HIV-1 and human proteins would greatly contribute to different areas of HIV research. Identification of such interactions leads to a greater insight into drug target prediction. Some recent studies have been conducted for computational prediction of new interactions based on the experimentally validated information stored in a HIV-1-human protein-protein interaction database. However, these techniques do not predict any regulatory mechanism between HIV-1 and human proteins by considering interaction types and direction of regulation of interactions.

Results

Here we present an association rule mining technique based on biclustering for discovering a set of rules among human and HIV-1 proteins using the publicly available HIV-1

SUBMITTER: Mukhopadhyay A 

PROVIDER: S-EPMC3922888 | biostudies-literature | 2014 Jan

REPOSITORIES: biostudies-literature