Partitioning clustering algorithms for protein sequence data sets.

ABSTRACT:

Background

Genome-sequencing projects are currently producing an enormous amount of new sequences and cause the rapid increasing of protein sequence databases. The unsupervised classification of these data into functional groups or families, clustering, has become one of the principal research objectives in structural and functional genomics. Computer programs to automatically and accurately classify sequences into families become a necessity. A significant number of methods have addressed the clustering of protein sequences and most of them can be categorized in three major groups: hierarchical, graph-based and partitioning methods. Among the various sequence clustering methods in literature, hierarchical and graph-based approaches have been widely used. Although partitioning clus

SUBMITTER: Fayech S 

PROVIDER: S-EPMC2678123 | biostudies-literature | 2009 Apr

REPOSITORIES: biostudies-literature