Description
The technologies in data mining have been applied to bioinformatics research in the past few years with success, but more research in this field is necessary. While tremendous progress has been made over the years, many of the fundamental challenges in bioinformatics are still open. Data mining plays a essential role in understanding the emerging problems in genomics, proteomics, and systems biology.
Advanced Data Mining Technologies in Bioinformatics covers important research topics of data mining on bioinformatics. Readers of this book will gain an understanding of the basics and problems of bioinformatics, as well as the applications of data mining technologies in tackling the problems and the essential research topics in the field. Advanced Data Mining Technologies in Bioinformatics is extremely useful for data mining researchers, molecular biologists, graduate students, and others interested in this topic.
Author's/Editor's Biography
Hui-Huang Hsu (Ed.)
Dr. Hui-Huang Hsu received the B.E. degree from Tamkang University, Taipei, Taiwan in 1987, and the M.S. and Ph.D. degrees from The University of Florida, Florida, USA in 1991 and 1994, respectively. All the degrees are in electrical engineering. He worked as a research assistant in the Department of Computer and Information Sciences at The University of Florida throughout his Ph.D. study and stayed there as a postdoctoral research fellow from January to May in 1995. From August 1995 to July 2003, he was with Chung Kuo Institute of Technology (1995 - 2000), Takming College (2000 - 2001), and Chinese Culture University (2001 - 2003) all located in Taipei, Taiwan. He joined the Department of Computer Science and Information Engineering, Tamkang University in August 2003, where he is now an associate professor. He has participated in the organization of several international conferences and workshops as the general chair, the program chair, the workshop chair, the financial chair, and the local arrangement chair. His current research interests are in the areas of bioinformatics, multimedia processing, data mining, machine learning, and e-learning.