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).
Monday, August 15, 2005 8:15 - 9:00 Breakfast and Registration 9:00 - 9:15 Welcome and Opening Remarks Mel Janowitz, DIMACS Associate Director 9:15 - 10:00 Genome organization, gene expression, and germline development in C. elegans (with introduction to gene regulation) Valerie Reinke, Yale University 10:00 - 10:45 Introduction to machine learning Rob Schapire, Princeton University 10:45 - 11:15 Break 11:15 - 12:00 Reverse Engineering of Gene Networks from Microarray Data with Heterogeneous Genome-Wide Biological Information Satoru Miyano, University of Tokyo (Japan) 12:00 - 1:30 Lunch 1:30 - 2:30 Technical challenges associated with RNAi screen in Drosophila cells Norbert Perrimon, HHMI and Harvard University 2:30 - 3:15 In silico detection of cis-regulatory elements under complex genomic and evolutionary context: a probabilistic graphical model approach Eric Xing, Carnegie Mellon University 3:15 - 3:45 Break 3:45 - 4:30 Regulatory Network Dependencies From Quantitative Trait Loci David Kulp, University of Massachusetts, Amherst 4:30 - 5:15 Function-centric Mining of Gene Expression Data: Profiling Distinctions between Similar Cancer Subtypes Gustavo Stolovitzky, IBM Watson Research Center Tuesday, August 16, 2005 8:15 - 9:00 Breakfast and Registration 9:00 - 9:45 Building network-level pathway models from diverse functional genomic data Olga Troyanskaya, Princeton University 9:45 - 10:30 Inference of gene regulation in bacterial pathogens Chris Myers, Cornell University 10:30 - 11:00 Break 11:00 - 12:00 Extracting biological information from DNA microarray experiments David Botstein, Princeton University 12:00 - 1:30 Lunch 1:30 - 2:15 Quality, quantity, and diversity of high-throughput data: methodological ramifications and biological results Alex Hartemink, Duke University 2:15 - 3:00 Discovering regulatory element motifs by predictive modeling of gene regulation Christina Leslie, Columbia University 3:00 - 3:30 Break 3:30 - 4:15 Understanding protein function on a genome-scale using networks Mark Gerstein, Yale University 4:15 - 5:00 Gene regulation by microRNAs Nikolaus Rajewsky, New York University 5:00 - 6:00 Reception Wednesday, August 17, 2005 8:15 - 9:00 Breakfast and Registration 9:00 - 9:45 Inferring Molecular Pathways in Mammals: A Single Cell Approach Dana Pe'er, Harvard University 9:45 - 10:30 Modeling overlapping sequence elements and other challenges in uncovering regulatory networks in bacteria Mark Craven, University of Wisconsin, Madison 10:30 - 11:00 Break 11:00 - 11:45 Condition-specific regulation of mRNA stability in yeast Harmen Bussemaker, Columbia University 11:45 - 12:30 Variation and Transcriptional Control in Drosophila Segment Determination John Reinitz, SUNY Stony Brook 12:30 - 2:00 Lunch 2:00 - 2:45 Selective integration of multiple biological data for supervised inference of protein and gene networks Koji Tsuda, AIST (Japan) 2:45 - 3:30 Predicting evolution from topology: a machine learning approach Chris Wiggins, Columbia University 3:30 - 4:00 Break 4:00 - 4:45 SVMs and probabilistic approaches for classifying promoters Anirvan Sengupta, Rutgers University 4:45 - 5:30 TBA