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FISH—family identification of sequence homologues using structure anchored hidden Markov models
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 cor...
Autores principales: | , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2006
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1538871/ https://www.ncbi.nlm.nih.gov/pubmed/16844969 http://dx.doi.org/10.1093/nar/gkl330 |
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author | Tångrot, Jeanette Wang, Lixiao Kågström, Bo Sauer, Uwe H. |
author_facet | Tångrot, Jeanette Wang, Lixiao Kågström, Bo Sauer, Uwe H. |
author_sort | Tångrot, Jeanette |
collection | PubMed |
description | 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 . |
format | Text |
id | pubmed-1538871 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2006 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-15388712006-08-18 FISH—family identification of sequence homologues using structure anchored hidden Markov models Tångrot, Jeanette Wang, Lixiao Kågström, Bo Sauer, Uwe H. Nucleic Acids Res Article 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 . Oxford University Press 2006-07-01 2006-07-14 /pmc/articles/PMC1538871/ /pubmed/16844969 http://dx.doi.org/10.1093/nar/gkl330 Text en © The Author 2006. Published by Oxford University Press. All rights reserved |
spellingShingle | Article Tångrot, Jeanette Wang, Lixiao Kågström, Bo Sauer, Uwe H. FISH—family identification of sequence homologues using structure anchored hidden Markov models |
title | FISH—family identification of sequence homologues using structure anchored hidden Markov models |
title_full | FISH—family identification of sequence homologues using structure anchored hidden Markov models |
title_fullStr | FISH—family identification of sequence homologues using structure anchored hidden Markov models |
title_full_unstemmed | FISH—family identification of sequence homologues using structure anchored hidden Markov models |
title_short | FISH—family identification of sequence homologues using structure anchored hidden Markov models |
title_sort | fish—family identification of sequence homologues using structure anchored hidden markov models |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1538871/ https://www.ncbi.nlm.nih.gov/pubmed/16844969 http://dx.doi.org/10.1093/nar/gkl330 |
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