Dr. Kevin R. Coombes
The University of Texas M. D. Anderson Cancer Center
Department of Bioinformatics and Computational Biology
- Statistical, mathematical, and computational models of gene expression profiles
- cDNA microarrays and SAGE
I am interested in all aspects of collecting and analyzing gene expression data from microarrays. From a bioinformatics standpoint, the process starts with analyzing and quantifying a microarray image and proceeds to background correction and normalization. Collections of many microarrays are then analyzed using clustering algorithms, self-organizing maps, and other sophisticated multivariate techniques to identify interesting sets of genes that can be used to distinguish between normal tissue and cancer, or between different types or stages of cancer, or between treated and untreated cancer cells. Finally, one applies more traditional bioinformatics techniques to understand the function of these genes by examining genetic sequences and related information in public databases like GenBank, SwissProt, and PubMed. The analysis of SAGE data presents a similar set of problems, and I am particularly interested in finding ways to combine data from SAGE with microarray data.
Doing a tutorial with me would provide advanced training in the mathematical, statistical, and computational techniques needed to understand, model, and analyze gene express data.
Program in Biostatistics, Bioinformatics and Systems Biology