Fitting hidden Markov models of protein domains to a target species: application to Plasmodium falciparum.

ABSTRACT:

Background

Hidden Markov Models (HMMs) are a powerful tool for protein domain identification. The Pfam database notably provides a large collection of HMMs which are widely used for the annotation of proteins in new sequenced organisms. In Pfam, each domain family is represented by a curated multiple sequence alignment from which a profile HMM is built. In spite of their high specificity, HMMs may lack sensitivity when searching for domains in divergent organisms. This is particularly the case for species with a biased amino-acid composition, such as P. falciparum, the main causal agent of human malaria. In this context, fitting HMMs to the specificities of the target proteome can help identify additional domains.

Results

Using P. falciparum as an example, we compare approac

SUBMITTER: Terrapon N 

PROVIDER: S-EPMC3434054 | biostudies-literature | 2012 May

REPOSITORIES: biostudies-literature