Automatic identification of highly conserved family regions and relationships in genome wide datasets including remote protein sequences.

ABSTRACT: Identifying shared sequence segments along amino acid sequences generally requires a collection of closely related proteins, most often curated manually from the sequence datasets to suit the purpose at hand. Currently developed statistical methods are strained, however, when the collection contains remote sequences with poor alignment to the rest, or sequences containing multiple domains. In this paper, we propose a completely unsupervised and automated method to identify the shared sequence segments observed in a diverse collection of protein sequences including those present in a smaller fraction of the sequences in the collection, using a combination of sequence alignment, residue conservation scoring and graph-theoretical approaches. Since shared sequence fragments often imply conserv

SUBMITTER: Dogan T 

PROVIDER: S-EPMC3771926 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature