This special focus is jointly sponsored by the Center for Discrete Mathematics and Theoretical Computer Science (DIMACS), the Biological, Mathematical, and Physical Sciences Interfaces Institute for Quantitative Biology (BioMaPS), and the Rutgers Center for Molecular Biophysics and Biophysical Chemistry (MB Center).
Tuesday, July 11, 2006 8:15 - 9:15 Breakfast and Registration 9:15 - 9:30 Welcome and Opening Remarks Mel Janowitz, DIMACS Associate Director 9:30 - 10:15 Predicting Protein Structure Flexibility from Sequence Philip E. Bourne, University of California San Diego 10:15 - 11:00 Break 11:00 - 11:45 Cancer Tissue Classification with Data-dependent Kernels Anne Zhang, The University of Kansas 12:00 - 1:30 Lunch 1:30 - 2:15 Modular Organization of Protein Interaction Network Feng Luo, Clemson University 2:15 - 3:00 Comparing the Performance of Several Popular Machine Learning Algorithms on Classifying TATA-box from putative TATA boxes Raja Loganantharaj, University of Louisiana at Lafayette 3:00 - 3:30 Break 3:30 - 4:15 Simple decision rules for classifying human cancers from gene expression profiles Aik Choon Tan, Johns Hopkins University 4:15 - 5:00 A machine learning approach for predicting the EC numbers of proteins James Howse, Los Alamos National Laboratory 5:30 Dinner at DIMACS Wednesday, July 12, 2006 8:15 - 9:00 Breakfast and Registration 9:00 - 9:45 Motif Refinement by Improving Information Content Scores using Neighborhood Search Chandan Reddy, Cornell University 9:45 - 10:30 An expectation-maximization algorithm for inferring the evolution of eukaryotic gene structure Liran Carmel, National Institutes of Health 10:30 - 11:00 Break 11:00 - 11:45 Learning the cis regulatory code by predictive modeling of gene regulation Christina Leslie, Columbia University 12:00 - 1:30 Lunch 1:30 - 2:15 Genome-wide Tagging SNPs with Entropy Based Methods Zhenqiu Liu, University of Maryland Medicine 2:15 - 3:00 Machine Learning and data combination for regulatory pathway prediction Mark Kon, Boston University 3:00 - 3:45 How to Avoid Misinterpreting Microarray Data Sungchul Ji, Rutgers University