Open AccessSiTaR: a novel tool for transcription factor binding site prediction
Author(s) -
Eugen Fazius,
Vladimir Shelest,
Ekaterina Shelest
Publication year - 2011
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/btr492
Subject(s) - randomness , computer science , false positive paradox , inference , data mining , motif (music) , dna binding site , sequence motif , artificial intelligence , mathematics , biology , promoter , statistics , genetics , gene , physics , gene expression , acoustics
Prediction of transcription factor binding sites (TFBSs) is crucial for promoter modeling and network inference. Quality of the predictions is spoiled by numerous false positives, which persist as the main problem for all presently available TFBS search methods.
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