报告题目：Deep Learning for Motif Mining in Biological Sequences and Beyond

主讲人：Prof. De-Shuang Huang, Tongji University, China

时间：2021年4月15日（星期四） 8:15—9:30

地点：海韵园行政楼A201会议室

摘要：Transcription factor (TF) plays a central role in gene regulation. Knowing the binding specificities of TFs is essential for developing models of the regulatory processes in biological systems and for deciphering the mechanism of gene expression. In this talk, we will introduce several novel computational models of TF binding data by combining various types of high-throughput data. Firstly, we will introduce a tensor decomposition model for collaborative prediction of ChIP-seq data, which could overcome its current limitation for integrative analysis. Secondly, we will present a de novo motif learning method based on the area under the receiver-operating characteristic curve (AUC) criterion, which has been widely used in the literature to evaluate the significance of extracted motifs. Finally, based on Fisher Exact Test score (FETS), we propose DirectFS, which is (to our best knowledge) the first FETS-based approach that allows direct learning of the motif parameters in continuous space. Experimental results based on real world high-throughput datasets illustrate that DirectFS outperforms competing methods for refining motifs found by de novo motif elicitation methods, while being one order of magnitude faster. In addition, we also present the possibility for using deep learning technique combining motif mining in biological sequences to address the medical image processing issue.

报告人简介： Prof. De-Shuang Huang, IAPR Fellow, IEEE Fellow, Institute of Machine Learning and Systems Biology, Tongji University, China.

De-Shuang Huang is a Professor in Department of Computer Science and Director of Institute of Machine Learning and Systems Biology at Tongji University, China. He is currently the Fellow of the International Association of Pattern Recognition (IAPR Fellow), Fellow of the IEEE (IEEE Fellow) and Senior Member of the INNS, Bioinformatics and Bioengineering Technical Committee Member of IEEE CIS, Neural Networks Technical Committee Member of IEEE CIS, the member of the INNS, Co-Chair of the Big Data Analytics section within INNS, and associated editors of IEEE/ACM Transactions on Computational Biology & Bioinformatics, and Neural Networks, etc. He founded the International Conference on Intelligent Computing (ICIC) in 2005. ICIC has since been successfully held annually with him serving as General or Steering Committee Chair. He also served as the 2015 International Joint Conference on Neural Networks (IJCNN 2015) General Chair, July 12-17, 2015, Killarney, Ireland, the 2014 11th IEEE Computational Intelligence in Bioinformatics and Computational Biology Conference (IEEE-CIBCBC) Program Committee Chair, May 21-24, 2014, Honolulu, USA. His main research interest includes neural networks, pattern recognition and bioinformatics.

邀请人：信息与通信工程系 王琳 教授