ESG: extended similarity group method for automated protein function prediction.

ABSTRACT:

Motivation

Importance of accurate automatic protein function prediction is ever increasing in the face of a large number of newly sequenced genomes and proteomics data that are awaiting biological interpretation. Conventional methods have focused on high sequence similarity-based annotation transfer which relies on the concept of homology. However, many cases have been reported that simple transfer of function from top hits of a homology search causes erroneous annotation. New methods are required to handle the sequence similarity in a more robust way to combine together signals from strongly and weakly similar proteins for effectively predicting function for unknown proteins with high reliability.

Results

We present the extended similarity group (ESG) method, which performs

SUBMITTER: Chitale M 

PROVIDER: S-EPMC2705228 | biostudies-literature | 2009 Jul

REPOSITORIES: biostudies-literature