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Updated: Jun 19, 2026

Describing a Transcription Factor Dependent Regulation of the MicroRNA Transcriptome
Published on: June 15, 2016
Genomic promoter analysis predicts functional transcription factor binding
J Sunil Rao1, Suresh Karanam, Colleen D McCabe
1Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH 44106, USA.
Abstract:
Background. The computational identification of functional transcription factor binding sites (TFBSs) remains a major challenge of computational biology. Results. We have analyzed the conserved promoter sequences for the complete set of human RefSeq genes using our conserved transcription factor binding site (CONFAC) software. CONFAC identified 16296 human-mouse ortholog gene pairs, and of those pairs, 9107 genes contained conserved TFBS in the 3 kb proximal promoter and first intron. To attempt to predict in vivo occupancy of transcription factor binding sites, we developed a novel marginal effect isolator algorithm that builds upon Bayesian methods for multigroup TFBS filtering and predicted the in vivo occupancy of two transcription factors with an overall accuracy of 84%. Conclusion. Our analyses show that integration of chromatin immunoprecipitation data with conserved TFBS analysis can be used to generate accurate predictions of functional TFBS. They also show that TFBS cooccurrence can be used to predict transcription factor binding to promoters in vivo.
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