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...

Simulation of tumour cord growth where conversion of the tumour to glycolytic (anaerobic) metabolism takes place under hypoxia. This video shows volume fraction of glycolytic cell population and velocity of tissue movement. Isolines show hypoxia limits for aerobic and anaerobic cell lines respectively. This video reflects work in progress and may be different from the final results.

Simulation of tumour cord growth where conversion of the tumour to glycolytic (anaerobic) metabolism takes place under hypoxia. This video shows evolution of the region where the aerobic cells suffer from hypoxia (ATP deficit) as well as the limit where the glycolytic cells start suffering too. This video reflects work in progress and may be different from the final results.

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.

My talk at the "Tag der Anatomie 2007"