Set cover-based methods for motif selection | Zendy

Yichao Li | Zendy; Yating Liu | Zendy; David Juedes | Zendy; Frank A. Drews | Zendy; Rǎzvan Bunescu | Zendy; Lonnie R. Welch | Zendy

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Set cover-based methods for motif selection

Author(s) -

Yichao Li,

Yating Liu,

David Juedes,

Frank A. Drews,

Rǎzvan Bunescu,

Lonnie R. Welch

Publication year - 2019

Publication title -

bioinformatics

Language(s) - Uncategorized

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btz697

Subject(s) - motif (music) , sequence motif , computer science , encode , source code , data mining , computational biology , dna binding site , sequence alignment , algorithm , biology , genetics , peptide sequence , gene , promoter , gene expression , physics , acoustics , operating system

De novo motif discovery algorithms find statistically over-represented sequence motifs that may function as transcription factor binding sites. Current methods often report large numbers of motifs, making it difficult to perform further analyses and experimental validation. The motif selection problem seeks to identify a minimal set of putative regulatory motifs that characterize sequences of interest (e.g. ChIP-Seq binding regions).

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