| Jun-Tao Guo, Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, Hosted by Jiancheng Jiang |
| Title: Structure-based prediction of transcription factor binding sites |
| Abstract: Transcription factors (TFs) regulate gene expression through binding to specific target DNA sites. Accurate annotation of transcription factor binding sites (TFBSs) at genome scale represents an essential step to our understanding of gene regulation networks. In this talk, I will present our recent work on structure-based prediction of TFBSs using an integrative energy function. The new energy function combines a multi-body statistical potential and two atomic energy terms, hydrogen bond energy and π-interaction energy. This energy function was tested on a set of homeodomains, the second largest transcription factor family in mammals, as well as a non-redundant dataset consisting of transcription factors from different families. Our results show that this integrative energy function improves the prediction accuracy over the knowledge-based, statistical potentials. |