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Tutorial
May 28, 2006, 13:30-15:30, Room C
Subtle Signal Discoveries in DNA and Protein Sequences
Using Neural Networks
| University of Illinois at Chicago, USA |
Abstract
In this tutorial, we introduce the problem of motif discoveries in unaligned DNA and protein sequences. The problem of motif identification in DNA and protein sequences has been studied for many years in the literature. Major hurdles at this point include computational complexity and reliability of the search algorithms. We discuss the use of a self-organizing neural network structure for solving the problem of motif identification in DNA and protein sequences. The network contains several layers with each layer performing classifications at different levels. The top layer divides the input space into a small number of regions and the bottom layer classifies all input patterns into motifs and non-motif patterns. Depending on the number of input patterns to be classified, several layers between the top layer and the bottom layer are needed to perform intermediate classifications. We maintain a low computational complexity through the use of the layered structure so that each pattern's classification is performed with respect to a small subspace of the whole input space. Our self-organizing neural network will grow as needed (e.g., when more motif patterns are classified). It will give the same amount of attention to each input pattern and it will not omit any potential motif patterns. Finally, simulation results show that our algorithm outperforms existing algorithms in certain aspects. In particular, simulation results show that our algorithm can identify motifs with more mutations than existing algorithms and our algorithm works well for long DNA sequences as well.
Biosketch
Derong Liu received the Ph.D. degree in electrical engineering from the University of Notre Dame, Notre Dame, Indiana, in 1994; the M.S. degree in electrical engineering from the Institute of Automation, Chinese Academy of Sciences, Beijing, China, in 1987; and the B.S. degree in mechanical engineering from the East China Institute of Technology (now Nanjing University of Science and Technology), Nanjing, China, in 1982. From 1982 to 1984, he was a product design engineer at China North Industries Corporation, Jilin, China. From 1987 to 1990, he was an instructor at the Graduate School of the Chinese Academy of Sciences, Beijing, China. From 1993 to 1995, he was a staff fellow at General Motors Research and Development Center, Warren, Michigan. From 1995 to 1999, he was an Assistant Professor in the Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, New Jersey. He joined the University of Illinois at Chicago in 1999 where he is now an Associate Professor of Electrical and Computer Engineering, of Bioengineering, and of Computer Science. Since 2005, he serves as the Director of Graduate Studies in the Department of Electrical and Computer Engineering at the University of Illinois at Chicago. He is coauthor (with A. N. Michel) of the books Dynamical Systems with Saturation Nonlinearities: Analysis and Design (New York: Springer-Verlag, 1994) and Qualitative Analysis and Synthesis of Recurrent Neural Networks ( New York: Marcel Dekker, 2002). He is coeditor (with P. J. Antsaklis) of the book Stability and Control of Dynamical Systems with Applications ( Boston, MA: Birkhauser, 2003).
Dr. Liu was a member of the Conference Editorial Board of the IEEE Control Systems Society (1995-2000); and served as an Associate Editor of the IEEE Transactions on Circuits and Systems-I: Fundamental Theory and Applications (1997-1999), the IEEE Transactions on Signal Processing (2001-2003), and the IEEE Transactions on Neural Networks (2004-2006). Since 2004, he has been the Editor of the IEEE Computational Intelligence Society's Electronic Letter; and since 2006, he has been the Letter Editor of the IEEE Transactions on Neural Networks, an Associate Editor of the IEEE Computational Intelligence Magazine, and an Associate Editor of the Automatica. He is the Program Chair for the following three conferences: the 2007 IEEE International Symposium on Approximate Dynamic Programming and Reinforcement Learning; the 21st IEEE International Symposium on Intelligent Control (2006); and the 2006 International Conference on Networking, Sensing and Control. He has served and is serving as a member of the organizing committee and the program committee of several international conferences. He is an elected AdCom member of the IEEE Computational Intelligence Society (2006-2009) and he is the Chair of the Chicago Chapter of the IEEE Computational Intelligence Society. He was recipient of the Michael J. Birck Fellowship from the University of Notre Dame (1990), the Harvey N. Davis Distinguished Teaching Award from Stevens Institute of Technology (1997), and the Faculty Early Career Development (CAREER) award from the National Science Foundation (1999). He is a Fellow of the IEEE and a member of Eta Kappa Nu.
