Protein function prediction by massive integration of evolutionary analyses and multiple data sources.

ABSTRACT:

Background

Accurate protein function annotation is a severe bottleneck when utilizing the deluge of high-throughput, next generation sequencing data. Keeping database annotations up-to-date has become a major scientific challenge that requires the development of reliable automatic predictors of protein function. The CAFA experiment provided a unique opportunity to undertake comprehensive 'blind testing' of many diverse approaches for automated function prediction. We report on the methodology we used for this challenge and on the lessons we learnt.

Methods

Our method integrates into a single framework a wide variety of biological information sources, encompassing sequence, gene expression and protein-protein interaction data, as well as annotations in UniProt entries. The me

SUBMITTER: Cozzetto D 

PROVIDER: S-EPMC3584902 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature