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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/25982
Ver los metadatos del registro completo
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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 Técnicas2025-09-03T09:53:15Zoai: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:34982025-09-03 09:53:15.32CONICET 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 |
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CONICET Digital (CONICET) |
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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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13.13397 |