Mining frequent stem patterns from unaligned RNA sequences | Zendy

Michiaki Hamada | Zendy; Koji Tsuda | Zendy; Taku Kudo | Zendy; Taishin Kin | Zendy; Kiyoshi Asai | Zendy

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Mining frequent stem patterns from unaligned RNA sequences

Author(s) -

Michiaki Hamada,

Koji Tsuda,

Taku Kudo,

Taishin Kin,

Kiyoshi Asai

Publication year - 2006

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btl431

Subject(s) - computer science , motif (music) , rna , software , coding (social sciences) , graph , web server , source code , computational biology , theoretical computer science , data mining , biology , the internet , genetics , world wide web , gene , mathematics , programming language , acoustics , statistics , physics

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 thoroughly.

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