RNA motif search with data-driven element ordering.
BMC Bioinformatics
; 17(1): 216, 2016 May 18.
Article
en En
| MEDLINE
| ID: mdl-27188396
ABSTRACT
BACKGROUND:
In this paper, we study the problem of RNA motif search in long genomic sequences. This approach uses a combination of sequence and structure constraints to uncover new distant homologs of known functional RNAs. The problem is NP-hard and is traditionally solved by backtracking algorithms.RESULTS:
We have designed a new algorithm for RNA motif search and implemented a new motif search tool RNArobo. The tool enhances the RNAbob descriptor language, allowing insertions in helices, which enables better characterization of ribozymes and aptamers. A typical RNA motif consists of multiple elements and the running time of the algorithm is highly dependent on their ordering. By approaching the element ordering problem in a principled way, we demonstrate more than 100-fold speedup of the search for complex motifs compared to previously published tools.CONCLUSIONS:
We have developed a new method for RNA motif search that allows for a significant speedup of the search of complex motifs that include pseudoknots. Such speed improvements are crucial at a time when the rate of DNA sequencing outpaces growth in computing. RNArobo is available at http//compbio.fmph.uniba.sk/rnarobo .Palabras clave
Texto completo:
1
Bases de datos:
MEDLINE
Asunto principal:
ARN
/
Análisis de Secuencia de ARN
/
Motivos de Nucleótidos
Límite:
Humans
Idioma:
En
Revista:
BMC Bioinformatics
Asunto de la revista:
INFORMATICA MEDICA
Año:
2016
Tipo del documento:
Article
País de afiliación:
Canadá