Predicting protein function via downward random walks on a gene ontology.

ABSTRACT:

Background

High-throughput bio-techniques accumulate ever-increasing amount of genomic and proteomic data. These data are far from being functionally characterized, despite the advances in gene (or gene's product proteins) functional annotations. Due to experimental techniques and to the research bias in biology, the regularly updated functional annotation databases, i.e., the Gene Ontology (GO), are far from being complete. Given the importance of protein functions for biological studies and drug design, proteins should be more comprehensively and precisely annotated.

Results

We proposed downward Random Walks (dRW) to predict missing (or new) functions of partially annotated proteins. Particularly, we apply downward random walks with restart on the GO directed acyclic graph

SUBMITTER: Yu G 

PROVIDER: S-EPMC4551531 | biostudies-literature | 2015 Aug

REPOSITORIES: biostudies-literature