Predicting pathway membership via domain signatures.

ABSTRACT:

Motivation

Functional characterization of genes is of great importance for the understanding of complex cellular processes. Valuable information for this purpose can be obtained from pathway databases, like KEGG. However, only a small fraction of genes is annotated with pathway information up to now. In contrast, information on contained protein domains can be obtained for a significantly higher number of genes, e.g. from the InterPro database.

Results

We present a classification model, which for a specific gene of interest can predict the mapping to a KEGG pathway, based on its domain signature. The classifier makes explicit use of the hierarchical organization of pathways in the KEGG database. Furthermore, we take into account that a specific gene can be mapped to differen

SUBMITTER: Frohlich H 

PROVIDER: S-EPMC2553439 | biostudies-literature | 2008 Oct

REPOSITORIES: biostudies-literature