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, May 9, 2006
8:00 - 8:30 Breakfast and Registration
Conference Registration Desk
8:30 - 8:45 Opening Remarks
Mel Janowitz, DIMACS Associate Director and Conference Organizers
Session T1 Analyzing Metabolic and Protein Networks
Chair: Panos Pardalos
8:45 - 9:15 Using Mathematical Programming for the Analysis and Redesign of
Metabolic and Signaling Networks
Costas Maranas, Pennsylvania State University
9:15 - 9:45 Dynamic Modules in Metabolic Networks
Eivind Almaas, Lawrence Livermore National Laboratory
9:45 - 10:15 Analysis of Interaction Networks from Clusters of Co-
Expressed Genes: A Case Study on Inflammation
Ioannis Androulakis, Rutgers University
10:15 - 10:45 Break
Session T2 Graph-Based Clustering Techniques
Chair: Art Chaovalitwongse
10:45 - 11:15 Clique Relaxation Models of Clusters in Biological Networks
Sergiy Butenko, Texas A&M University
11:15 - 11:45 Maximal Hyperclique Pattern in Gene Profiles
Weili Wu, The University of Texas at Dallas
11:45 - 12:15 Practical Fixed-Parameter Algorithms for Graph-Modeled Data Clustering
Sebastian Wernicke, Friedrich-Schiller-University, Germany
12:15 - 1:45 Lunch
Session T3 Optimization Techniques for Biological Data Comparison
Chair: Sergiy Butenko
1:45 - 2:15 Mathematical Programming Methods for Comparison Problems in Biocomputing
Carlos Oliveira, Oklahoma State University
2:15 - 2:45 Using Formal Concept Analysis for Microarray Data Comparison
Vicky Choi, Virginia Tech
2:45 - 3:15 Stereotyped Activity Flow in Auditory Neocortical Microcircuits
Kenneth Harris, Rutgers University
3:15 - 3:45 Break
Session T4 Clusters and Dynamics of Biological Networks
Chair: Carlos Oliveira
3:45 - 4:15 The Pure Parsimony Problem
Allen Holder, Trinity University
4:15 - 4:45 A Time Series Clustering Algorithm for Brain Network Analysis
W. Art Chaovalitwongse, Rutgers University
4:45 - 5:15 Fast and Effective Clustering Very Large Networks Using Density-
Based Clustering Algorithm
Xiaowei Xu, University of Arkansas
Wednesday, May 10, 2006
8:00 - 8:45 Registration and Registration
Conference Registration Desk
Session W1 Models and Algorithms for Genetic Expression Data
Chair: Sergiy Butenko
8:45 - 9:15 Mining High-Throughput Biological Data:
Methods, Algorithms and Applications
Eytan Domany, Weizmann Institute of Science, Israel
9:15 - 9:45 Clustering Algorithms for the Analysis of Type 1 Diabetes Data
Michael Langston, University of Tennessee
9:45 - 10:15 A Projected Clustering Algorithm for Biological Data Analysis
Ping Deng, The University of Texas at Dallas
10:15 - 10:45 Break
Session W2 Coregulation in Metabolic Networks
Chair: Sungchul Ji
10:45 - 11:15 Sequence-Based Predictive Modeling of Posttranscriptional Regulatory Networks
Harmen Bussemaker, Columbia University
11:15 - 11:45 Posttranscriptional Regulation within the Transcriptome of Human Tissues
Gary Brewer, University of Medicine & Dentistry of New Jersey -
Robert Wood Johnson Medical School
11:45 - 12:15 Five Levels of Molecular Networks Underlying the
Structure and Function of the Living Cell
Sungchul Ji, Rutgers University
12:15 - 1:45 Lunch
Session W3 Optimization-Based Clustering Techniques
Chair: Panos Pardalos
1:45 - 2:15 A Novel Mixed-Integer Nonlinear Optimization-Based Clustering Approach:
Global Optimum Search in Clustering with Enhanced Positioning
(EP_GOS_Clust)
Christodoulos Floudas, Princeton University
2:15 - 2:45 Nonlinear Skeletons of Data Sets and Kernel Fuzzy Hyperplane
Clustering Algorithm
Pando Georgiev, University of Cincinnati
2:45 - 3:15 Consistent Biclustering via Fractional 0-1 Programming
Stas Busygin, University of Florida
3:15 - 3:45 Break
Session W4 Clustering Microarray Data
Chair: Dhammika Amaratunga and Javier Cabrera
3:45 - 4:15 Generalizations of the Topological Overlap Matrix for Module
Detection in Gene and Protein Networks
Steve Horvath, University of California
4:15 - 4:45 Clustering as a Means of Identifying Co-Regulated Genes
Jyotsna Kasturi, Johnson & Johnson Pharmaceutical Research & Development
4:45 - 5:15 Tuned Two-Way Bagging for Clustering Microarrays
Vladimir Kovtun, Johnson & Johnson Pharmaceutical Research & Development
5:15 - 5:45 Data Analysis in Immune Response Profiling using Human Protein Microarrays
Mariusz Lubomirski, Johnson & Johnson Pharmaceutical Research & Development
6:30 - 8:30 Reception at Holiday Inn
Thursday, May 11, 2006 (JOINT WITH CSNA)
8:00 - 8:45 Breakfast and Registration
Conference Registration Desk
Session H1 CSNA Invited Talks
Chair: Mel Janowitz - 1st Floor Lecture Hall
8:45 - 9:30 Data Mining and Network Models of Massive Datasets
Panos Pardalos, University of Florida
9:30 - 10:15 Multi-Class Protein Classification Using String Kernels and Adaptive Codes
Christina Leslie, Columbia University
10:15 - 10:45 Break
Session H2-1 Classification and Anomaly Detection in Biological Processes
Chair: Bernie Harris - Room 431
10:45 - 11:15 Comparison of Classification Methods to Predict Complications to Liver Surgery
Leah Ben-Porat, Memorial Sloan-Kettering Cancer Center
11:15 - 11:45 Self-Organizing Maps for Brain Electrical Activity Classification
Wei Zeng, Rutgers University
11:45 - 12:15 Using Scan Statistics for Anomaly Detection in Genetic Networks
Christopher Overall, George Mason University
Session H2-2 Author Identification - 1st Floor Lecture Hall
Chair: Paul Kantor, Rutgers University
10:45 - 11:15 Identifying Authors and Authors' Styles
David Hoover, NYU
11:15 - 11:45 Simulated Entity Resolution: DIMACS Work on the
KDD Challenge of 2005
Aynur Dayanik, Dmitriy Fradkin, Paul Kantor, David Lewis,
David Madigan,and Fred Roberts, Rutgers University
11:45 - 12:15 The Words of Our Lives: Analyzing Age-and Sex-Linked
Language Variation in the Blogosphere
Shlomo Argamon, Moshe Koppel, James W. Pennebaker, and Jonathan Schler,
Illinois Institute of Technology
12:15 - 1:30 Lunch
Session H3 Classification vs Clustering, Analyzing Gene Functionality
Chair: Claudia Perlich - 1st Floor Lecture Hall
1:30 - 2:00 Protein Cluster Analysis via Directed Diffusion
Yosi Keller, Yale University
2:00 - 2:30 Learning and Classification in Biological Data
Sofus Macskassy, Fetch Technologies, Inc.
2:30 - 3:00 Information-Based Clustering
Gurinder Singh Atwal, Princeton University
3:00 - 3:30 Classification vs Clustering, Analyzing Gene Functionality
Claudia Perlich, IBM T.J. Watson Research Center
3:30 - 3:45 Break
Session H4 Clustering and Sequencing Genomic Data
Chair: Panos Pardalos - 1st Floor Lecture Hall
3:45 - 4:15 Using Cluster Analysis to Relate Subjective and Objective
Pharmacovigilance Association Measures
Ronald Pearson, ProSanos Corporation
4:15 - 4:45 Distance Based Probabilistic Clustering of Data
Cem Iyigun, Rutgers University
4:45 - 5:00 Closing Remarks from the Conference Organizers
5:00 Adjourn
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