Abstract
Gene expressions are regulated by transcription factors binding to specific transcription factor binding sites or motifs in promoter regions. Therefore, recognition and discovery of binding sites are critical for understanding the mechanism of gene regulation. Experimental approaches for discovering and verifying motifs are quite time consuming and costly. To solve this problem, considerable attention has been paid to computational approaches for motif discovery in the past decade. Various algorithms and computational tools have been proposed and implemented for biologists. Existing algorithms employed some motif models and statistical measures to predict the locations of motifs in given DNA sequences. Due to uncertainties occurring in motif presentation and low signal-to-noise ratio, it becomes a challenging task to distinguish true motifs from false positives and accurately forecast the location of motifs in particular for the large scale of datasets.

This talk gives some ideas about how to use computing techniques to resolve a typical bio-data mining problem. Specifically, we will discuss three topics including motif modeling, filtering systems design, and understanding of motif instance location forecasting. Some data mining techniques and computational intelligence systems for potential applications will be presented with some supportive results.

Biography
Prof. Dianhui Wang received his PhD degree (supervised by Professor Tianyou Chai) in March 1995, from the School of Information Science and Engineering, Northeastern University, Shenyang, China. From September 1995 to August 1997, he worked as a Postdoctoral Fellow in the School of Electronic and Electrical Engineering, Nanyang Technological University, Singapore. He then worked as a Research Fellow for three years until June 2001 in the Department of Computing, The Hong Kong Polytechnic University, Hong Kong. Since July 2001, he has been with the Department of Computer Science and Computer Engineering at La Trobe University, Australia, and promoted as a Reader and Associate Professor in 2007. Dr Wang is an adjunct Professor at Key Laboratory of Integrated Automation for the Process Industry, Ministry of Education of China, Northeastern University, China

Dianhui has broad working areas and experienced various research topics in computational mathematics (computational fluid dynamics), applied mathematics (singular systems theory), computer sciences (image processing and bioinformatics) and control engineering (adaptive neural/fuzzy control systems design). His current research focuses on data mining and computational intelligence systems for Bioinformatics, Information Retrieval and Engineering Applications. He has published over 150 technical papers in journals and conference proceedings.

Dianhui is a Senior Member of IEEE, and serving as an Associate Editor for Information Sciences, Neurocomputing, International Journal of Applied Intelligence, International Journal of Modeling, Identification and Control, International Journal of Machine Learning and Cybernetics.