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