SUPERFAMILY - Sophisticated comparative genomics, data mining, visualization and phylogeny

Derek Wilson, Ralph Pethica, Yiduo Zhou, Charles Talbot, Christine Vogel, Martin Madera, Cyrus Chothia, Julian Gough

Research output: Contribution to journalArticle

Abstract

SUPERFAMILY provides structural, functional and evolutionary information for proteins from all completely sequenced genomes, and large sequence collections such as UniProt. Protein domain assignments for over 900 genomes are included in the database, which can be accessed at http://supfam.org/. Hidden Markov models based on Structural Classification of Proteins (SCOP) domain definitions at the superfamily level are used to provide structural annotation. We recently produced a new model library based on SCOP 1.73. Family level assignments are also available. From the web site users can submit sequences for SCOP domain classification; search for keywords such as superfamilies, families, organism names, models and sequence identifiers; find over- and underrepresented families or superfamilies within a genome relative to other genomes or groups of genomes; compare domain architectures across selections of genomes and finally build multiple sequence alignments between Protein Data Bank (PDB), genomic and custom sequences. Recent extensions to the database include InterPro abstracts and Gene Ontology terms for superfamiles, taxonomic visualization of the distribution of families across the tree of life, searches for functionally similar domain architectures and phylogenetic trees. The database, models and associated scripts are available for download from the ftp site.

Original languageEnglish (US)
Pages (from-to)D380-D386
JournalNucleic acids research
Volume37
Issue numberSUPPL. 1
DOIs
StatePublished - Jan 9 2009

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ASJC Scopus subject areas

  • Genetics

Cite this

Wilson, D., Pethica, R., Zhou, Y., Talbot, C., Vogel, C., Madera, M., Chothia, C., & Gough, J. (2009). SUPERFAMILY - Sophisticated comparative genomics, data mining, visualization and phylogeny. Nucleic acids research, 37(SUPPL. 1), D380-D386. https://doi.org/10.1093/nar/gkn762