Tree Gibbs Sampler: identifying conserved motifs without aligning orthologous sequences | Zendy

Xiaohui Cai | Zendy; Haiyan Hu | Zendy; Xiaoman Shawn Li | Zendy

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Tree Gibbs Sampler: identifying conserved motifs without aligning orthologous sequences

Author(s) -

Xiaohui Cai,

Haiyan Hu,

Xiaoman Shawn Li

Publication year - 2007

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/btm282

Subject(s) - tree (set theory) , computational biology , phylogenetic tree , gibbs sampling , conserved sequence , biology , phylogenetics , genetics , evolutionary biology , computer science , base sequence , combinatorics , artificial intelligence , bayesian probability , gene , mathematics

Tree Gibbs Sampler is a software for identifying motifs by simultaneously using the motif overrepresentation property and the motif evolutionary conservation property. It identifies motifs without depending on pre-aligned orthologous sequences, which makes it useful for the extraction of regulatory elements in multiple genomes of both closely related and distant species.

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