PepBank - a database of peptides based on sequence text mining and public peptide data sources
<p>Abstract</p> <p>Background</p> <p>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 h...
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| Format: | Article |
| Language: | English |
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BMC
2007-08-01
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| Series: | BMC Bioinformatics |
| Online Access: | http://www.biomedcentral.com/1471-2105/8/280 |
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| author | Pivovarov Misha Kossodo Misha Guettler Daniel Shtatland Timur Weissleder Ralph |
| author_facet | Pivovarov Misha Kossodo Misha Guettler Daniel Shtatland Timur Weissleder Ralph |
| author_sort | Pivovarov Misha |
| collection | DOAJ |
| description | <p>Abstract</p> <p>Background</p> <p>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.</p> <p>Description</p> <p>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.</p> <p>Conclusion</p> <p>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 <url>http://pepbank.mgh.harvard.edu/</url>, and the text mining source code (Peptide::Pubmed) is freely available above as well as on CPAN (<url>http://www.cpan.org/</url>).</p> |
| first_indexed | 2024-12-11T10:54:06Z |
| format | Article |
| id | doaj.art-84a4d6dde07142c0b0e8e8a18ff2de98 |
| institution | Directory Open Access Journal |
| issn | 1471-2105 |
| language | English |
| last_indexed | 2024-12-11T10:54:06Z |
| publishDate | 2007-08-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Bioinformatics |
| spelling | doaj.art-84a4d6dde07142c0b0e8e8a18ff2de982022-12-22T01:10:10ZengBMCBMC Bioinformatics1471-21052007-08-018128010.1186/1471-2105-8-280PepBank - a database of peptides based on sequence text mining and public peptide data sourcesPivovarov MishaKossodo MishaGuettler DanielShtatland TimurWeissleder Ralph<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Description</p> <p>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.</p> <p>Conclusion</p> <p>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 <url>http://pepbank.mgh.harvard.edu/</url>, and the text mining source code (Peptide::Pubmed) is freely available above as well as on CPAN (<url>http://www.cpan.org/</url>).</p>http://www.biomedcentral.com/1471-2105/8/280 |
| spellingShingle | Pivovarov Misha Kossodo Misha Guettler Daniel Shtatland Timur Weissleder Ralph PepBank - a database of peptides based on sequence text mining and public peptide data sources BMC Bioinformatics |
| 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 |
| url | http://www.biomedcentral.com/1471-2105/8/280 |
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