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HangOut: generating clean PSI-BLAST profiles for domains with long insertions
Summary: Profile-based similarity search is an essential step in structure-function studies of proteins. However, inclusion of non-homologous sequence segments into a profile causes its corruption and results in false positives. Profile corruption is common in multidomain proteins, and single domain...
Autores principales: | , , |
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Formato: | Texto |
Lenguaje: | English |
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Oxford University Press
2010
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2881392/ https://www.ncbi.nlm.nih.gov/pubmed/20413635 http://dx.doi.org/10.1093/bioinformatics/btq208 |
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author | Kim, Bong-Hyun Cong, Qian Grishin, Nick V. |
author_facet | Kim, Bong-Hyun Cong, Qian Grishin, Nick V. |
author_sort | Kim, Bong-Hyun |
collection | PubMed |
description | Summary: Profile-based similarity search is an essential step in structure-function studies of proteins. However, inclusion of non-homologous sequence segments into a profile causes its corruption and results in false positives. Profile corruption is common in multidomain proteins, and single domains with long insertions are a significant source of errors. We developed a procedure (HangOut) that, for a single domain with specified insertion position, cleans erroneously extended PSI-BLAST alignments to generate better profiles. Availability: HangOut is implemented in Python 2.3 and runs on all Unix-compatible platforms. The source code is available under the GNU GPL license at http://prodata.swmed.edu/HangOut/ Contact: kim@chop.swmed.edu; grishin@chop.swmed.edu Supplementary information: Supplementary data are available at Bioinformatics online. |
format | Text |
id | pubmed-2881392 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-28813922010-06-08 HangOut: generating clean PSI-BLAST profiles for domains with long insertions Kim, Bong-Hyun Cong, Qian Grishin, Nick V. Bioinformatics Applications Note Summary: Profile-based similarity search is an essential step in structure-function studies of proteins. However, inclusion of non-homologous sequence segments into a profile causes its corruption and results in false positives. Profile corruption is common in multidomain proteins, and single domains with long insertions are a significant source of errors. We developed a procedure (HangOut) that, for a single domain with specified insertion position, cleans erroneously extended PSI-BLAST alignments to generate better profiles. Availability: HangOut is implemented in Python 2.3 and runs on all Unix-compatible platforms. The source code is available under the GNU GPL license at http://prodata.swmed.edu/HangOut/ Contact: kim@chop.swmed.edu; grishin@chop.swmed.edu Supplementary information: Supplementary data are available at Bioinformatics online. Oxford University Press 2010-06-15 2010-04-22 /pmc/articles/PMC2881392/ /pubmed/20413635 http://dx.doi.org/10.1093/bioinformatics/btq208 Text en © The Author 2010. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Note Kim, Bong-Hyun Cong, Qian Grishin, Nick V. HangOut: generating clean PSI-BLAST profiles for domains with long insertions |
title | HangOut: generating clean PSI-BLAST profiles for domains with long insertions |
title_full | HangOut: generating clean PSI-BLAST profiles for domains with long insertions |
title_fullStr | HangOut: generating clean PSI-BLAST profiles for domains with long insertions |
title_full_unstemmed | HangOut: generating clean PSI-BLAST profiles for domains with long insertions |
title_short | HangOut: generating clean PSI-BLAST profiles for domains with long insertions |
title_sort | hangout: generating clean psi-blast profiles for domains with long insertions |
topic | Applications Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2881392/ https://www.ncbi.nlm.nih.gov/pubmed/20413635 http://dx.doi.org/10.1093/bioinformatics/btq208 |
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