Automatic assignment of prokaryotic genes to functional categories using literature profiling.

ABSTRACT: In the last years, there was an exponential increase in the number of publicly available genomes. Once finished, most genome projects lack financial support to review annotations. A few of these gene annotations are based on a combination of bioinformatics evidence, however, in most cases, annotations are based solely on sequence similarity to a previously known gene, which was most probably annotated in the same way. As a result, a large number of predicted genes remain unassigned to any functional category despite the fact that there is enough evidence in the literature to predict their function. We developed a classifier trained with term-frequency vectors automatically disclosed from text corpora of an ensemble of genes representative of each functional category of the J. Craig Venter

SUBMITTER: Torrieri R 

PROVIDER: S-EPMC3471813 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature