title: MotifCluster: an interactive online tool for clustering and visualizing sequences using shared motifs.
abstract: MotifCluster finds related motifs in a set of sequences, and clusters the sequences into families using the motifs they contain. MotifCluster, at http://bmf.colorado.edu/motifcluster, lets users test whether proteins are related, cluster sequences by shared conserved motifs, and visualize motifs mapped onto trees, sequences and three-dimensional structures. We demonstrate MotifCluster's accuracy using gold-standard protein superfamilies; using recommended settings, families were assigned to the correct superfamilies with 0.17% false positive and no false negative assignments.
authors.affiliation: Department of Computer Science, University of Colorado, Boulder, CO 80309, USA.
authors.forename: Micah
authors.initials: M
authors.lastname: Hamady
authors.forename: Jeremy
authors.initials: J
authors.lastname: Widmann
authors.forename: Shelley D
authors.initials: SD
authors.lastname: Copley
authors.forename: Rob
authors.initials: R
authors.lastname: Knight
mesh_terms: D019747:Aldose-Ketose Isomerases / Q000737:chemistry; D000465:Algorithms; D020816:Amino Acid Motifs; D016000:Cluster Analysis; D020407:Internet; D008969:Molecular Sequence Data; D010802:Phylogeny; D017434:Protein Structure, Tertiary; D016415:Sequence Alignment; D020539:Sequence Analysis, Protein / Q000379:methods*; D012984:Software
chemical_list: D019747:Aldose-Ketose Isomerases; C022548:ribosephosphate isomerase