Combining modularity, conservation, and interactions of proteins significantly increases precision and coverage of protein function prediction.

ABSTRACT:

Background

While the number of newly sequenced genomes and genes is constantly increasing, elucidation of their function still is a laborious and time-consuming task. This has led to the development of a wide range of methods for predicting protein functions in silico. We report on a new method that predicts function based on a combination of information about protein interactions, orthology, and the conservation of protein networks in different species.

Results

We show that aggregation of these independent sources of evidence leads to a drastic increase in number and quality of predictions when compared to baselines and other methods reported in the literature. For instance, our method generates more than 12,000 novel protein functions for human with an estimated precision

SUBMITTER: Jaeger S 

PROVIDER: S-EPMC3017542 | biostudies-literature | 2010 Dec

REPOSITORIES: biostudies-literature