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PepBank - a database of peptides based on sequence text mining and public peptide data sources

BACKGROUND: Peptides are important molecules with diverse biological functions and biomedical uses. To date, there does not exist a single, searchable archive for peptide sequences or associated biological data. Rather, peptide sequences still have to be mined from abstracts and full-length articles...

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Detalles Bibliográficos
Autores principales: Shtatland, Timur, Guettler, Daniel, Kossodo, Misha, Pivovarov, Misha, Weissleder, Ralph
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1976427/
https://www.ncbi.nlm.nih.gov/pubmed/17678535
http://dx.doi.org/10.1186/1471-2105-8-280
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author Shtatland, Timur
Guettler, Daniel
Kossodo, Misha
Pivovarov, Misha
Weissleder, Ralph
author_facet Shtatland, Timur
Guettler, Daniel
Kossodo, Misha
Pivovarov, Misha
Weissleder, Ralph
author_sort Shtatland, Timur
collection PubMed
description BACKGROUND: Peptides are important molecules with diverse biological functions and biomedical uses. To date, there does not exist a single, searchable archive for peptide sequences or associated biological data. Rather, peptide sequences still have to be mined from abstracts and full-length articles, and/or obtained from the fragmented public sources. DESCRIPTION: We have constructed a new database (PepBank), which at the time of writing contains a total of 19,792 individual peptide entries. The database has a web-based user interface with a simple, Google-like search function, advanced text search, and BLAST and Smith-Waterman search capabilities. The major source of peptide sequence data comes from text mining of MEDLINE abstracts. Another component of the database is the peptide sequence data from public sources (ASPD and UniProt). An additional, smaller part of the database is manually curated from sets of full text articles and text mining results. We show the utility of the database in different examples of affinity ligand discovery. CONCLUSION: We have created and maintain a database of peptide sequences. The database has biological and medical applications, for example, to predict the binding partners of biologically interesting peptides, to develop peptide based therapeutic or diagnostic agents, or to predict molecular targets or binding specificities of peptides resulting from phage display selection. The database is freely available on , and the text mining source code (Peptide::Pubmed) is freely available above as well as on CPAN ().
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spelling pubmed-19764272007-09-14 PepBank - a database of peptides based on sequence text mining and public peptide data sources Shtatland, Timur Guettler, Daniel Kossodo, Misha Pivovarov, Misha Weissleder, Ralph BMC Bioinformatics Database BACKGROUND: Peptides are important molecules with diverse biological functions and biomedical uses. To date, there does not exist a single, searchable archive for peptide sequences or associated biological data. Rather, peptide sequences still have to be mined from abstracts and full-length articles, and/or obtained from the fragmented public sources. DESCRIPTION: We have constructed a new database (PepBank), which at the time of writing contains a total of 19,792 individual peptide entries. The database has a web-based user interface with a simple, Google-like search function, advanced text search, and BLAST and Smith-Waterman search capabilities. The major source of peptide sequence data comes from text mining of MEDLINE abstracts. Another component of the database is the peptide sequence data from public sources (ASPD and UniProt). An additional, smaller part of the database is manually curated from sets of full text articles and text mining results. We show the utility of the database in different examples of affinity ligand discovery. CONCLUSION: We have created and maintain a database of peptide sequences. The database has biological and medical applications, for example, to predict the binding partners of biologically interesting peptides, to develop peptide based therapeutic or diagnostic agents, or to predict molecular targets or binding specificities of peptides resulting from phage display selection. The database is freely available on , and the text mining source code (Peptide::Pubmed) is freely available above as well as on CPAN (). BioMed Central 2007-08-01 /pmc/articles/PMC1976427/ /pubmed/17678535 http://dx.doi.org/10.1186/1471-2105-8-280 Text en Copyright © 2007 Shtatland et al; licensee BioMed Central Ltd. http://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) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Database
Shtatland, Timur
Guettler, Daniel
Kossodo, Misha
Pivovarov, Misha
Weissleder, Ralph
PepBank - a database of peptides based on sequence text mining and public peptide data sources
title PepBank - a database of peptides based on sequence text mining and public peptide data sources
title_full PepBank - a database of peptides based on sequence text mining and public peptide data sources
title_fullStr PepBank - a database of peptides based on sequence text mining and public peptide data sources
title_full_unstemmed PepBank - a database of peptides based on sequence text mining and public peptide data sources
title_short PepBank - a database of peptides based on sequence text mining and public peptide data sources
title_sort pepbank - a database of peptides based on sequence text mining and public peptide data sources
topic Database
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1976427/
https://www.ncbi.nlm.nih.gov/pubmed/17678535
http://dx.doi.org/10.1186/1471-2105-8-280
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