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
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