Large scale hierarchical clustering of protein sequences.

ABSTRACT:

Background

Searching a biological sequence database with a query sequence looking for homologues has become a routine operation in computational biology. In spite of the high degree of sophistication of currently available search routines it is still virtually impossible to identify quickly and clearly a group of sequences that a given query sequence belongs to.

Results

We report on our developments in grouping all known protein sequences hierarchically into superfamily and family clusters. Our graph-based algorithms take into account the topology of the sequence space induced by the data itself to construct a biologically meaningful partitioning. We have applied our clustering procedures to a non-redundant set of about 1,000,000 sequences resulting in a hierarchical cluster

SUBMITTER: Krause A 

PROVIDER: S-EPMC547898 | biostudies-literature | 2005 Jan

REPOSITORIES: biostudies-literature