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Querying the public databases for sequences using complex keywords contained in the feature lines

BACKGROUND: High throughput technologies often require the retrieval of large data sets of sequences. Retrieval of EMBL or GenBank entries using keywords is easy using tools such as ACNUC, Entrez or SRS, but has some limitations, in particular when querying with complex keywords. RESULTS: We show th...

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Detalles Bibliográficos
Autores principales: Croce, Olivier, Lamarre, Michaël, Christen, Richard
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2006
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1403806/
https://www.ncbi.nlm.nih.gov/pubmed/16441875
http://dx.doi.org/10.1186/1471-2105-7-45
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author Croce, Olivier
Lamarre, Michaël
Christen, Richard
author_facet Croce, Olivier
Lamarre, Michaël
Christen, Richard
author_sort Croce, Olivier
collection PubMed
description BACKGROUND: High throughput technologies often require the retrieval of large data sets of sequences. Retrieval of EMBL or GenBank entries using keywords is easy using tools such as ACNUC, Entrez or SRS, but has some limitations, in particular when querying with complex keywords. RESULTS: We show that Entrez has severe limitations with respect to retrieving subsequences. SRS works well with simple keywords but not with keywords composed of several terms, and has problems with complex queries. ACNUC works well, but does not allow precise queries in the Feature qualifiers. We developed specific Perl scripts to precisely retrieve subsequences as defined by complex descriptors in the Features qualifiers of the EMBL entries. We improved parts of the bioPerl library to allow parsing of large data files, and we embedded these scripts in a user friendly interface (OS independent) for easy use. CONCLUSION: Although not as fast as the public tools that use prebuilt indexes, parsing the complete entries using a script is often necessary in order to retrieve the exact data searched for. Embedding in a user friendly interface allows biologists to use the scripts, which can easily be modified, if necessary, by bioinformaticians for unforeseen needs.
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spelling pubmed-14038062006-03-18 Querying the public databases for sequences using complex keywords contained in the feature lines Croce, Olivier Lamarre, Michaël Christen, Richard BMC Bioinformatics Software BACKGROUND: High throughput technologies often require the retrieval of large data sets of sequences. Retrieval of EMBL or GenBank entries using keywords is easy using tools such as ACNUC, Entrez or SRS, but has some limitations, in particular when querying with complex keywords. RESULTS: We show that Entrez has severe limitations with respect to retrieving subsequences. SRS works well with simple keywords but not with keywords composed of several terms, and has problems with complex queries. ACNUC works well, but does not allow precise queries in the Feature qualifiers. We developed specific Perl scripts to precisely retrieve subsequences as defined by complex descriptors in the Features qualifiers of the EMBL entries. We improved parts of the bioPerl library to allow parsing of large data files, and we embedded these scripts in a user friendly interface (OS independent) for easy use. CONCLUSION: Although not as fast as the public tools that use prebuilt indexes, parsing the complete entries using a script is often necessary in order to retrieve the exact data searched for. Embedding in a user friendly interface allows biologists to use the scripts, which can easily be modified, if necessary, by bioinformaticians for unforeseen needs. BioMed Central 2006-01-27 /pmc/articles/PMC1403806/ /pubmed/16441875 http://dx.doi.org/10.1186/1471-2105-7-45 Text en Copyright © 2006 Croce 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 Software
Croce, Olivier
Lamarre, Michaël
Christen, Richard
Querying the public databases for sequences using complex keywords contained in the feature lines
title Querying the public databases for sequences using complex keywords contained in the feature lines
title_full Querying the public databases for sequences using complex keywords contained in the feature lines
title_fullStr Querying the public databases for sequences using complex keywords contained in the feature lines
title_full_unstemmed Querying the public databases for sequences using complex keywords contained in the feature lines
title_short Querying the public databases for sequences using complex keywords contained in the feature lines
title_sort querying the public databases for sequences using complex keywords contained in the feature lines
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1403806/
https://www.ncbi.nlm.nih.gov/pubmed/16441875
http://dx.doi.org/10.1186/1471-2105-7-45
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