TITLE:

GENE-LEVEL STUDY OF T-CELL RESPONSE TO IL-2, A MICROARRAY DATA MINING APPROACH (No. 88)

DATE:

Friday, September 23rd, 2005

TIME:

3:30 PM

LOCATION:

GMCS 214

SPEAKER:

Christopher Peters, CSRC, San Diego State University

ABSTRACT:

Microarray technology allows researchers to simultaneously study the
expression levels of thousands of genes. Microarrays are therefore used in a wide range of studies, including understanding and diagnosis of diseases, drug development, and understanding gene-function relationships. In this project, we have used cDNA microarrays to study the behavior of human T cells when exposed to IL-2, a growth factor involved in the immune response. Gene expression levels have been recorded using microarray technology for two cell types, TBC (Primary T cell) and T1 (Tax-immortalized cell). The cells were deprived of IL-2 to find baseline expression levels, then the cells were stimulated with IL-2 and expression levels were recorded at three time points. Two repetitions of each experiment were performed to ensure consistency. In this presentation we discuss the methodology for solving two data mining problems with this data set: first, we need to filter out the genes with inconsistent expression levels, and second, we need to find groups of genes that have similar expression behavior through time under the influence of IL-2. In this presentation we will discuss the cluster analysis and other computational techniques that we have applied to solve the above two problems.

HOST:

Farmarz Valafar

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