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De novo motif discovery facilitates identification of interactions between transcription factors in Saccharomyces cerevisiae
Author(s) -
Mei-Ju May Chen,
Lih-Ching Chou,
Tsung-Ting Hsieh,
DingDar Lee,
Kaiwei Liu,
Chi-Yuan Yu,
YenJen Oyang,
HuaiKuang Tsai,
ChienYu Chen
Publication year - 2012
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/bts002
Subject(s) - cooperativity , computational biology , motif (music) , transcription factor , saccharomyces cerevisiae , computer science , gene , data mining , biology , genetics , physics , acoustics
Gene regulation involves complicated mechanisms such as cooperativity between a set of transcription factors (TFs). Previous studies have used target genes shared by two TFs as a clue to infer TF-TF interactions. However, this task remains challenging because the target genes with low binding affinity are frequently omitted by experimental data, especially when a single strict threshold is employed. This article aims at improving the accuracy of inferring TF-TF interactions by incorporating motif discovery as a fundamental step when detecting overlapping targets of TFs based on ChIP-chip data.

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