Genomes to Proteomes: Introduction to Molecular Cell Biology
Donald McEachron, Ph.D.
Drexel University

Keynote address on Thursday, June 29, Brian Wigdahl Ph.D.
Drexel University School of Medicine

New large scale biological tools have challenged biologists to take a global view of the gene and protein networks underlying cell communication. This course will focus on the fundamentals of molecular cell biology and will present a bioinformatics approach to investigating functions of genes and proteins and their regulation.

Medical Image Processing and Classification
Andres Kriete, Ph.D.
Coriell Institute for Medical Research
Todd Doehring, Ph.D. and Bilge Karacali, Ph.D.
Center for Integrated Bioinformatics, Drexel University

Keynote address on Thursday, July 6, by Nick Bryan M.D., Ph.D.
University of Pennsylvania School of Medicine

This course presents the fundamentals of automated image processing and image classification in medicine. Automated image processing yields unbiased quantitation of tissue phenotype markers. Supervised classification of images based on genotypic data has the potential of relating tissue phenotype to global molecular profile.

Microarrays and Differential Gene Expression
Donald Baldwin, Ph.D.
Penn Microarray Facility, University of Pennsylvania

Keynote address on Thursday, July 13, by Michael Liebman Ph.D.
Windber Research Institute

This course will present the fundamentals of microarray experiments for high throughput measurement of RNA abundance profiles, focusing on the labwork and data analysis required to determine the probability that the genes represented on a microarray show differential expression between two or more conditions. Wet laboratory sessions for this course will be conducted at the Penn Microarray Facility.         

Proteomics
David Speicher, Ph.D.
Systems Biology Division, The Wistar Institute

Keynote address on Thursday, July 20, by Steven A. Carr, Ph.D.
Massachusetts Institute of Technology and Harvard University

Proteomics is the systematic analysis of proteins in cellular machines, entire cells, tissues or entire organisms. Proteomics provides an exciting new way to pursue biological and biomedical science in taking a comprehensive, systematic approach to understanding biology. The course will focus on the computational challenges associated with analysis and interpretation of diverse types of proteomic data including the mass spectrometry data.

Biostatistics, Clustering, and Classification
Michael Ochs, Ph.D.
Fox Chase Cancer Center

Keynote address on Thursday, July 27, by Clayton Naeve Ph.D.
St. Jude Children's Research Hospital

This course will introduce biostatistics measures used in the analysis of high-throughput biological data. Participants will be exposed to hands-on data analysis using TMEV open source tool from The Institute for Genomics Research (TIGR), Oak Ridge National Laboratory’s GO Tree Machine (GOTM) gene ontology tool, and ClutrFree open source visualization tool from Fox Chase Cancer Center.  

Bioinformatics Databases and Biomolecular Networks
Ricardo Saban DVM, Ph.D.
University of Oklahoma Health Sciences Center

Keynote address on Thursday, August 3, TBA

This course will focus on computational data resources and approaches which allow expanding from single gene analyses to system-level analyses. Software tools to predict regulatory, functional and/or “knowledge” network interactions will be used to analyze the high-throughput molecular biology data.

Pharmacogenomics
Patrick Bender, Ph.D.
Coriell Institute for Medical Research

Keynote address on Wednesday, August 9, TBA

Pharmacogenomics is an emerging discipline focusing on the use of genome information for informed decision making along the pharmaceutical pipeline. This course reviews the bioinformatics and high-throughput methods for identification of targets, candidate drugs and their potential adverse effects.

caBig™ Databases
J. Robert Beck, M.D.
Fox Chase Cancer Center

Keynote address on Thursday, August 10, TBA

The National Cancer Institute’s Center for Bioinformatics has taken the lead to develop a comprehensive cancer database project to facilitate and expedite cancer research by integrating many imaging and genetic
databases into a unified web based service made available for use by researchers. This project is entitled the cancer Biomedical Informatics Grid™ , or caBIG™. This course will present an overview of the caBIG™ project and its practical uses.