Efficient combination of multiple word models for improved sequence comparison | Zendy

Xiaoqiu Huang | Zendy; Ye Liang | Zendy; Hui-Hsien Chou | Zendy; IHsuan Yang | Zendy; KunMao Chao | Zendy

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Efficient combination of multiple word models for improved sequence comparison

Author(s) -

Xiaoqiu Huang,

Ye Liang,

Hui-Hsien Chou,

IHsuan Yang,

KunMao Chao

Publication year - 2004

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/bth279

Subject(s) - word (group theory) , computer science , source code , similarity (geometry) , sequence (biology) , binary number , natural language processing , code (set theory) , sequence alignment , artificial intelligence , algorithm , computational biology , programming language , arithmetic , set (abstract data type) , biology , genetics , mathematics , peptide sequence , gene , geometry , image (mathematics)

Studies of efficient and sensitive sequence comparison methods are driven by a need to find homologous regions of weak similarity between large genomes.

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