TY - JOUR A1 - Krause, Antje A1 - Stoye, Jens A1 - Vingron, Martin T1 - Large scale hierarchical clustering of protein sequences JF - BMC Bioinformatics N2 - 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 clustering which is being made available for querying and browsing at http://systers.molgen.mpg.de/. Conclusions: Comparisons with other widely used clustering methods on various data sets show the abilities and strengths of our clustering methods in producing a biologically meaningful grouping of protein sequences. KW - Protein KW - Sequenz KW - Clusteralgorithmus KW - Hierarchisches Clustern KW - Proteinfamilie KW - protein KW - sequence KW - cluster algorithm KW - hierarchical clustering KW - protein family Y1 - 2005 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:526-opus-153 SN - 1471-2105 PB - BioMed Central ER -