Prof. David K Gifford

The effort of Gifford’s group in computational genomics focuses on developing computational methods for the analysis of data from high-throughput molecular biology experiments. Advanced technologies that study organisms at the genomic level have created large amounts of information derived from a broad range of formats. Availability of this vast body of information requires new computational approaches for data analysis. The Gifford research group develops methods for integrating data from different formats, such as expression profiling and DNA-binding data, to create quantitative models of complex biological phenomena. Expression profiling uses DNA microarray technology to understand expression of genes based on genomic knowledge. Microarray research uses levels of messenger RNA (mRNA) expression as a measure of gene expression on a genome-wide scale. Because this technology can interrogate large numbers of genes, expression profiling reveals quantitative, system-level information. However, the challenge remains to distill the results into an interpretable computational form from which a predictive model can be established. The Gifford group is developing computational methods to visualize microarray data in a graphical model and to incorporate other types of data into a predictive model. These methods will enable computational assembly of the collective knowledge into a cohesive picture of cellular and organism function.