Part 1 of a video podcast from the American Museum of Natural Historys 2007 Mack Lipkin Man and Nature Series entitled Save the Microbes, Save the World: The Fate of Microbial Life on a Changing Planet. The panel was introduced by Michael Novacek, Senior Vice President and Provost of Science for the AMNH and moderated by Julie Burstein, Public Radio International and WNYC Radio’s Studio 360. Panelists include: # Rita Colwell, Distinguished University Professor, University of Maryland...

Kimmen Sjolander, Ph.D. Associate Professor, Department of Bioengineering University of California - Berkeley

Principles of image analysis. Segmentation, edge detection, and feature extraction. Imaging tissue section images obtained by H&E staining, immuno-histochemistry, and multi-color FISH. Part of the Computer-Aided Discovery Methods course taught at Baylor College of Medicine.

Identifying protein interactions suitable for therapeutic intervention. Design of short peptides and peptidomimetics. Pharmacogenetics. Part of the Computer-Aided Discovery Methods course taught at Baylor College of Medicine.

Inference of gene modules and protein interaction networks using using synthetic lethality method (e.g., Pan X et al, Cell 124 1069-1081, 2006) the yeast-two-hybrid method and homology with model organisms. Part of the Computer-Aided Discovery Methods course taught at Baylor College of Medicine.

Expression profiles of osteosarcoma that can predict response to chemotherapy. Lab for the Computer-Aided Discovery Methods course taught at Baylor College of Medicine.

Recent advances in genomic and proteomic technologies have revolutionized our way of classifying diseases. These high-throughput technologies allow the development of powerful and multivariate classifiers to distinguish different diseases or tumors based on their molecular profiles. Molecular classification provides a new way to distinguish histologically similar but molecularly different types of tumors, and hence improves tumor diagnosis and prognosis. In this course, we introduce major...

Recent advances in genomic and proteomic technologies have revolutionized our way of classifying diseases. These high-throughput technologies allow the development of powerful and multivariate classifiers to distinguish different diseases or tumors based on their molecular profiles. Molecular classification provides a new way to distinguish histologically similar but molecularly different types of tumors, and hence improves tumor diagnosis and prognosis. In this course, we introduce major...

The goal of this exercise is to show how we can relate the results of two independent gene expression datasets to each other. In the case where one dataset provides "transcriptional signatures" of known oncogenic pathways, we can get clues as to which oncogenic pathways may be represented within the results obtained from another dataset. Lab for the Computer-Aided Discovery Methods course taught at Baylor College of Medicine.

Lecture on gene expression studies of cancer and gene transcription signatures. Part of the Computer-Aided Discovery Methods course taught at Baylor College of Medicine.