A Bioinformatics Approach for Detecting Repetitive Nested Motifs using Pattern Matching

Autores
Romero, José Rodolfo; Carballido, Jessica Andrea; Garbus, Ingrid; Echenique, Carmen Viviana; Ponzoni, Ignacio
Año de publicación
2016
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The identification of nested motifs in genomic sequences is a complex computational problem. The detection of these patterns is important to allow discovery of transposable element (TE) insertions, incomplete reverse transcripts, deletions, and/or mutations. Here, we designed a de novo strategy for detecting patterns that represent nested motifs based on exhaustive searches for pairs of motifs and combinatorial pattern analysis. These patterns can be grouped into three categories: motifs within other motifs, motifs flanked by other motifs, and motifs of large size. Our methodology, applied to genomic sequences from the plant species Aegilops tauschii and Oryza sativa, revealed that it is possible to find putative nested TEs by detecting these three types of patterns. The results were validated though BLAST alignments, which revealed the efficacy and usefulness of the new method, which we call Mamushka.
Fil: Romero, José Rodolfo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Centro de Recursos Naturales Renovables de la Zona Semiárida. Universidad Nacional del Sur. Centro de Recursos Naturales Renovables de la Zona Semiárida; Argentina
Fil: Carballido, Jessica Andrea. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Cs. E Ingeniería de la Computacion; Argentina
Fil: Garbus, Ingrid. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Centro de Recursos Naturales Renovables de la Zona Semiárida. Universidad Nacional del Sur. Centro de Recursos Naturales Renovables de la Zona Semiárida; Argentina
Fil: Echenique, Carmen Viviana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Centro de Recursos Naturales Renovables de la Zona Semiárida. Universidad Nacional del Sur. Centro de Recursos Naturales Renovables de la Zona Semiárida; Argentina
Fil: Ponzoni, Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Cs. E Ingeniería de la Computacion; Argentina
Materia
REPETITIVE MOTIFS
NESTED MOTIFS
EXACT SEQUENCE ANALYSIS
STRUCTURAL BIOINFORMATICS
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/25982
Acceder
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network_name_str CONICET Digital (CONICET)
spelling A Bioinformatics Approach for Detecting Repetitive Nested Motifs using Pattern MatchingRomero, José RodolfoCarballido, Jessica AndreaGarbus, IngridEchenique, Carmen VivianaPonzoni, IgnacioREPETITIVE MOTIFSNESTED MOTIFSEXACT SEQUENCE ANALYSISSTRUCTURAL BIOINFORMATICShttps://purl.org/becyt/ford/4.4https://purl.org/becyt/ford/4The identification of nested motifs in genomic sequences is a complex computational problem. The detection of these patterns is important to allow discovery of transposable element (TE) insertions, incomplete reverse transcripts, deletions, and/or mutations. Here, we designed a de novo strategy for detecting patterns that represent nested motifs based on exhaustive searches for pairs of motifs and combinatorial pattern analysis. These patterns can be grouped into three categories: motifs within other motifs, motifs flanked by other motifs, and motifs of large size. Our methodology, applied to genomic sequences from the plant species Aegilops tauschii and Oryza sativa, revealed that it is possible to find putative nested TEs by detecting these three types of patterns. The results were validated though BLAST alignments, which revealed the efficacy and usefulness of the new method, which we call Mamushka.Fil: Romero, José Rodolfo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Centro de Recursos Naturales Renovables de la Zona Semiárida. Universidad Nacional del Sur. Centro de Recursos Naturales Renovables de la Zona Semiárida; ArgentinaFil: Carballido, Jessica Andrea. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Cs. E Ingeniería de la Computacion; ArgentinaFil: Garbus, Ingrid. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Centro de Recursos Naturales Renovables de la Zona Semiárida. Universidad Nacional del Sur. Centro de Recursos Naturales Renovables de la Zona Semiárida; ArgentinaFil: Echenique, Carmen Viviana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Centro de Recursos Naturales Renovables de la Zona Semiárida. Universidad Nacional del Sur. Centro de Recursos Naturales Renovables de la Zona Semiárida; ArgentinaFil: Ponzoni, Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Cs. E Ingeniería de la Computacion; ArgentinaBioinformatics Inst2016-10-30info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/25982Romero, José Rodolfo; Carballido, Jessica Andrea; Garbus, Ingrid; Echenique, Carmen Viviana; Ponzoni, Ignacio; A Bioinformatics Approach for Detecting Repetitive Nested Motifs using Pattern Matching; Bioinformatics Inst; Evolutionary Bioinformatics; 12; 30-10-2016; 247-2511176-9343CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://insights.sagepub.com/a-bioinformatics-approach-for-detecting-repetitive-nested-motifs-using-article-a5992-abstract?article_id=5992info:eu-repo/semantics/altIdentifier/url/https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5089818/info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:52:08Zoai:ri.conicet.gov.ar:11336/25982instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:52:08.322CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A Bioinformatics Approach for Detecting Repetitive Nested Motifs using Pattern Matching
title A Bioinformatics Approach for Detecting Repetitive Nested Motifs using Pattern Matching
spellingShingle A Bioinformatics Approach for Detecting Repetitive Nested Motifs using Pattern Matching
Romero, José Rodolfo
REPETITIVE MOTIFS
NESTED MOTIFS
EXACT SEQUENCE ANALYSIS
STRUCTURAL BIOINFORMATICS
title_short A Bioinformatics Approach for Detecting Repetitive Nested Motifs using Pattern Matching
title_full A Bioinformatics Approach for Detecting Repetitive Nested Motifs using Pattern Matching
title_fullStr A Bioinformatics Approach for Detecting Repetitive Nested Motifs using Pattern Matching
title_full_unstemmed A Bioinformatics Approach for Detecting Repetitive Nested Motifs using Pattern Matching
title_sort A Bioinformatics Approach for Detecting Repetitive Nested Motifs using Pattern Matching
dc.creator.none.fl_str_mv Romero, José Rodolfo
Carballido, Jessica Andrea
Garbus, Ingrid
Echenique, Carmen Viviana
Ponzoni, Ignacio
author Romero, José Rodolfo
author_facet Romero, José Rodolfo
Carballido, Jessica Andrea
Garbus, Ingrid
Echenique, Carmen Viviana
Ponzoni, Ignacio
author_role author
author2 Carballido, Jessica Andrea
Garbus, Ingrid
Echenique, Carmen Viviana
Ponzoni, Ignacio
author2_role author
author
author
author
dc.subject.none.fl_str_mv REPETITIVE MOTIFS
NESTED MOTIFS
EXACT SEQUENCE ANALYSIS
STRUCTURAL BIOINFORMATICS
topic REPETITIVE MOTIFS
NESTED MOTIFS
EXACT SEQUENCE ANALYSIS
STRUCTURAL BIOINFORMATICS
purl_subject.fl_str_mv https://purl.org/becyt/ford/4.4
https://purl.org/becyt/ford/4
dc.description.none.fl_txt_mv The identification of nested motifs in genomic sequences is a complex computational problem. The detection of these patterns is important to allow discovery of transposable element (TE) insertions, incomplete reverse transcripts, deletions, and/or mutations. Here, we designed a de novo strategy for detecting patterns that represent nested motifs based on exhaustive searches for pairs of motifs and combinatorial pattern analysis. These patterns can be grouped into three categories: motifs within other motifs, motifs flanked by other motifs, and motifs of large size. Our methodology, applied to genomic sequences from the plant species Aegilops tauschii and Oryza sativa, revealed that it is possible to find putative nested TEs by detecting these three types of patterns. The results were validated though BLAST alignments, which revealed the efficacy and usefulness of the new method, which we call Mamushka.
Fil: Romero, José Rodolfo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Centro de Recursos Naturales Renovables de la Zona Semiárida. Universidad Nacional del Sur. Centro de Recursos Naturales Renovables de la Zona Semiárida; Argentina
Fil: Carballido, Jessica Andrea. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Cs. E Ingeniería de la Computacion; Argentina
Fil: Garbus, Ingrid. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Centro de Recursos Naturales Renovables de la Zona Semiárida. Universidad Nacional del Sur. Centro de Recursos Naturales Renovables de la Zona Semiárida; Argentina
Fil: Echenique, Carmen Viviana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Centro de Recursos Naturales Renovables de la Zona Semiárida. Universidad Nacional del Sur. Centro de Recursos Naturales Renovables de la Zona Semiárida; Argentina
Fil: Ponzoni, Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Cs. E Ingeniería de la Computacion; Argentina
description The identification of nested motifs in genomic sequences is a complex computational problem. The detection of these patterns is important to allow discovery of transposable element (TE) insertions, incomplete reverse transcripts, deletions, and/or mutations. Here, we designed a de novo strategy for detecting patterns that represent nested motifs based on exhaustive searches for pairs of motifs and combinatorial pattern analysis. These patterns can be grouped into three categories: motifs within other motifs, motifs flanked by other motifs, and motifs of large size. Our methodology, applied to genomic sequences from the plant species Aegilops tauschii and Oryza sativa, revealed that it is possible to find putative nested TEs by detecting these three types of patterns. The results were validated though BLAST alignments, which revealed the efficacy and usefulness of the new method, which we call Mamushka.
publishDate 2016
dc.date.none.fl_str_mv 2016-10-30
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/25982
Romero, José Rodolfo; Carballido, Jessica Andrea; Garbus, Ingrid; Echenique, Carmen Viviana; Ponzoni, Ignacio; A Bioinformatics Approach for Detecting Repetitive Nested Motifs using Pattern Matching; Bioinformatics Inst; Evolutionary Bioinformatics; 12; 30-10-2016; 247-251
1176-9343
CONICET Digital
CONICET
url http://hdl.handle.net/11336/25982
identifier_str_mv Romero, José Rodolfo; Carballido, Jessica Andrea; Garbus, Ingrid; Echenique, Carmen Viviana; Ponzoni, Ignacio; A Bioinformatics Approach for Detecting Repetitive Nested Motifs using Pattern Matching; Bioinformatics Inst; Evolutionary Bioinformatics; 12; 30-10-2016; 247-251
1176-9343
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://insights.sagepub.com/a-bioinformatics-approach-for-detecting-repetitive-nested-motifs-using-article-a5992-abstract?article_id=5992
info:eu-repo/semantics/altIdentifier/url/https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5089818/
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Bioinformatics Inst
publisher.none.fl_str_mv Bioinformatics Inst
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.070432

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