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RegExpBlasting (REB), a Regular Expression Blasting algorithm based on multiply aligned sequences

BACKGROUND: One of the most frequent uses of bioinformatics tools concerns functional characterization of a newly produced nucleotide sequence (a query sequence) by applying Blast or FASTA against a set of sequences (the subject sequences). However, in some specific contexts, it is useful to compare...

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Detalles Bibliográficos
Autores principales: Rubino, Francesco, Attimonelli, Marcella
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2697652/
https://www.ncbi.nlm.nih.gov/pubmed/19534754
http://dx.doi.org/10.1186/1471-2105-10-S6-S5
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author Rubino, Francesco
Attimonelli, Marcella
author_facet Rubino, Francesco
Attimonelli, Marcella
author_sort Rubino, Francesco
collection PubMed
description BACKGROUND: One of the most frequent uses of bioinformatics tools concerns functional characterization of a newly produced nucleotide sequence (a query sequence) by applying Blast or FASTA against a set of sequences (the subject sequences). However, in some specific contexts, it is useful to compare the query sequence against a cluster such as a MultiAlignment (MA). We present here the RegExpBlasting (REB) algorithm, which compares an unclassified sequence with a dataset of patterns defined by application of Regular Expression rules to a given-as-input MA datasets. The REB algorithm workflow consists in i. the definition of a dataset of multialignments ii. the association of each MA to a pattern, defined by application of regular expression rules; iii. automatic characterization of a submitted biosequence according to the function of the sequences described by the pattern best matching the query sequence. RESULTS: An application of this algorithm is used in the "characterize your sequence" tool available in the PPNEMA resource. PPNEMA is a resource of Ribosomal Cistron sequences from various species, grouped according to nematode genera. It allows the retrieval of plant nematode multialigned sequences or the classification of new nematode rDNA sequences by applying REB. The same algorithm also supports automatic updating of the PPNEMA database. The present paper gives examples of the use of REB within PPNEMA. CONCLUSION: The use of REB in PPNEMA updating, the PPNEMA "characterize your sequence" option clearly demonstrates the power of the method. Using REB can also rapidly solve any other bioinformatics problem, where the addition of a new sequence to a pre-existing cluster is required. The statistical tests carried out here show the powerful flexibility of the method.
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spelling pubmed-26976522009-06-16 RegExpBlasting (REB), a Regular Expression Blasting algorithm based on multiply aligned sequences Rubino, Francesco Attimonelli, Marcella BMC Bioinformatics Proceedings BACKGROUND: One of the most frequent uses of bioinformatics tools concerns functional characterization of a newly produced nucleotide sequence (a query sequence) by applying Blast or FASTA against a set of sequences (the subject sequences). However, in some specific contexts, it is useful to compare the query sequence against a cluster such as a MultiAlignment (MA). We present here the RegExpBlasting (REB) algorithm, which compares an unclassified sequence with a dataset of patterns defined by application of Regular Expression rules to a given-as-input MA datasets. The REB algorithm workflow consists in i. the definition of a dataset of multialignments ii. the association of each MA to a pattern, defined by application of regular expression rules; iii. automatic characterization of a submitted biosequence according to the function of the sequences described by the pattern best matching the query sequence. RESULTS: An application of this algorithm is used in the "characterize your sequence" tool available in the PPNEMA resource. PPNEMA is a resource of Ribosomal Cistron sequences from various species, grouped according to nematode genera. It allows the retrieval of plant nematode multialigned sequences or the classification of new nematode rDNA sequences by applying REB. The same algorithm also supports automatic updating of the PPNEMA database. The present paper gives examples of the use of REB within PPNEMA. CONCLUSION: The use of REB in PPNEMA updating, the PPNEMA "characterize your sequence" option clearly demonstrates the power of the method. Using REB can also rapidly solve any other bioinformatics problem, where the addition of a new sequence to a pre-existing cluster is required. The statistical tests carried out here show the powerful flexibility of the method. BioMed Central 2009-06-16 /pmc/articles/PMC2697652/ /pubmed/19534754 http://dx.doi.org/10.1186/1471-2105-10-S6-S5 Text en Copyright © 2009 Rubino and Attimonelli; 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 Proceedings
Rubino, Francesco
Attimonelli, Marcella
RegExpBlasting (REB), a Regular Expression Blasting algorithm based on multiply aligned sequences
title RegExpBlasting (REB), a Regular Expression Blasting algorithm based on multiply aligned sequences
title_full RegExpBlasting (REB), a Regular Expression Blasting algorithm based on multiply aligned sequences
title_fullStr RegExpBlasting (REB), a Regular Expression Blasting algorithm based on multiply aligned sequences
title_full_unstemmed RegExpBlasting (REB), a Regular Expression Blasting algorithm based on multiply aligned sequences
title_short RegExpBlasting (REB), a Regular Expression Blasting algorithm based on multiply aligned sequences
title_sort regexpblasting (reb), a regular expression blasting algorithm based on multiply aligned sequences
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2697652/
https://www.ncbi.nlm.nih.gov/pubmed/19534754
http://dx.doi.org/10.1186/1471-2105-10-S6-S5
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