Inference of functional relations in predicted protein networks with a machine learning approach.

ABSTRACT:

Background

Molecular biology is currently facing the challenging task of functionally characterizing the proteome. The large number of possible protein-protein interactions and complexes, the variety of environmental conditions and cellular states in which these interactions can be reorganized, and the multiple ways in which a protein can influence the function of others, requires the development of experimental and computational approaches to analyze and predict functional associations between proteins as part of their activity in the interactome.

Methodology/principal findings

We have studied the possibility of constructing a classifier in order to combine the output of the several protein interaction prediction methods. The AODE (Averaged One-Dependence Estimators) machin

SUBMITTER: Garcia-Jimenez B 

PROVIDER: S-EPMC2848617 | biostudies-literature | 2010 Apr

REPOSITORIES: biostudies-literature