Mining frequent stem patterns from unaligned RNA sequences

Motivation: In detection of non-coding RNAs, it is often necessary to identify the secondary structure motifs from a set of putative RNA sequences. Most of the existing algorithms aim to provide the best motif or few good motifs, but biologists often need to inspect all the possible motifs thoroughl...

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Veröffentlicht in:	Bioinformatics 2006-10, Vol.22 (20), p.2480-2487
Hauptverfasser:	Hamada, Michiaki, Tsuda, Koji, Kudo, Taku, Kin, Taishin, Asai, Kiyoshi
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Artificial Intelligence Base Sequence Biological and medical sciences Databases, Genetic Fundamental and applied biological sciences. Psychology General aspects Information Storage and Retrieval - methods Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects) Molecular Sequence Data Pattern Recognition, Automated RNA - chemistry RNA - genetics Sequence Alignment - methods Sequence Analysis, RNA - methods
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