@article{KrauseStoyeVingron2005, author = {Krause, Antje and Stoye, Jens and Vingron, Martin}, title = {Large scale hierarchical clustering of protein sequences}, series = {BMC Bioinformatics}, journal = {BMC Bioinformatics}, publisher = {BioMed Central}, issn = {1471-2105}, doi = {10.15771/1471-2105_2005_6_15}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:526-opus-153}, year = {2005}, 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 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.}, language = {en} }