Open AccessFISH--family identification of sequence homologues using structure anchored hidden Markov models
Author(s) -
Jeanette Tångrot,
Lei Wang,
Bo Kågström,
Uwe H. Sauer
Publication year - 2006
Publication title -
nucleic acids research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.008
H-Index - 537
eISSN - 1362-4954
pISSN - 0305-1048
DOI - 10.1093/nar/gkl330
Subject(s) - biology , sequence (biology) , sequence database , fish <actinopterygii> , computational biology , upload , multiple sequence alignment , protein family , identification (biology) , alignment free sequence analysis , function (biology) , sequence alignment , genetics , hidden markov model , peptide sequence , computer science , gene , artificial intelligence , fishery , ecology , operating system
The FISH server is highly accurate in identifying the family membership of domains in a query protein sequence, even in the case of very low sequence identities to known homologues. A performance test using SCOP sequences and an E-value cut-off of 0.1 showed that 99.3% of the top hits are to the correct family saHMM. Matches to a query sequence provide the user not only with an annotation of the identified domains and hence a hint to their function, but also with probable 2D and 3D structures, as well as with pairwise and multiple sequence alignments to homologues with low sequence identity. In addition, the FISH server allows users to upload and search their own protein sequence collection or to quarry public protein sequence data bases with individual saHMMs. The FISH server can be accessed at http://babel.ucmp.umu.se/fish/.
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