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The SeqFEATURE library of 3D functional site models: comparison to existing methods and applications to protein function annotation
Structural genomics efforts have led to increasing numbers of novel, uncharacterized protein structures with low sequence identity to known proteins, resulting in a growing need for structure-based function recognition tools. Our method, SeqFEATURE, robustly models protein functions described by seq...
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2008
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2395245/ https://www.ncbi.nlm.nih.gov/pubmed/18197987 http://dx.doi.org/10.1186/gb-2008-9-1-r8 |
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author | Wu, Shirley Liang, Mike P Altman, Russ B |
author_facet | Wu, Shirley Liang, Mike P Altman, Russ B |
author_sort | Wu, Shirley |
collection | PubMed |
description | Structural genomics efforts have led to increasing numbers of novel, uncharacterized protein structures with low sequence identity to known proteins, resulting in a growing need for structure-based function recognition tools. Our method, SeqFEATURE, robustly models protein functions described by sequence motifs using a structural representation. We built a library of models that shows good performance compared to other methods. In particular, SeqFEATURE demonstrates significant improvement over other methods when sequence and structural similarity are low. |
format | Text |
id | pubmed-2395245 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-23952452008-05-29 The SeqFEATURE library of 3D functional site models: comparison to existing methods and applications to protein function annotation Wu, Shirley Liang, Mike P Altman, Russ B Genome Biol Method Structural genomics efforts have led to increasing numbers of novel, uncharacterized protein structures with low sequence identity to known proteins, resulting in a growing need for structure-based function recognition tools. Our method, SeqFEATURE, robustly models protein functions described by sequence motifs using a structural representation. We built a library of models that shows good performance compared to other methods. In particular, SeqFEATURE demonstrates significant improvement over other methods when sequence and structural similarity are low. BioMed Central 2008-01-16 /pmc/articles/PMC2395245/ /pubmed/18197987 http://dx.doi.org/10.1186/gb-2008-9-1-r8 Text en Copyright © 2008 Wu et al.; licensee BioMed Central Ltd. https://creativecommons.org/licenses/by/2.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0 (https://creativecommons.org/licenses/by/2.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Method Wu, Shirley Liang, Mike P Altman, Russ B The SeqFEATURE library of 3D functional site models: comparison to existing methods and applications to protein function annotation |
title | The SeqFEATURE library of 3D functional site models: comparison to existing methods and applications to protein function annotation |
title_full | The SeqFEATURE library of 3D functional site models: comparison to existing methods and applications to protein function annotation |
title_fullStr | The SeqFEATURE library of 3D functional site models: comparison to existing methods and applications to protein function annotation |
title_full_unstemmed | The SeqFEATURE library of 3D functional site models: comparison to existing methods and applications to protein function annotation |
title_short | The SeqFEATURE library of 3D functional site models: comparison to existing methods and applications to protein function annotation |
title_sort | seqfeature library of 3d functional site models: comparison to existing methods and applications to protein function annotation |
topic | Method |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2395245/ https://www.ncbi.nlm.nih.gov/pubmed/18197987 http://dx.doi.org/10.1186/gb-2008-9-1-r8 |
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