ICIC   25583
INSTITUTO DE CIENCIAS E INGENIERIA DE LA COMPUTACION
Unidad Ejecutora - UE
artículos
Título:
A Bioinformatics Approach for Detecting Repetitive Nested Motifs using Pattern Matching
Autor/es:
CARBALLIDO J; PONZONI IGNACIO; GARBUS I; ROMERO J; ECHENIQUE V; GARBUS I; CARBALLIDO J; ROMERO J; PONZONI IGNACIO; ECHENIQUE V
Revista:
EVOLUTIONARY BIOINFORMATICS
Editorial:
BIOINFORMATICS INST
Referencias:
Lugar: Albany; Año: 2016 vol. 12 p. 247 - 251
ISSN:
1176-9343
Resumen:
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.