Matt’s graduate research was based on developing and applying massively parallel methods for dissecting sequence function in yeast. His work studied the fitness effects of point mutations in a yeast promoter required for growth in sulfate limitation. He also developed methods for massively parallel methods for all-by-all interactome assays that would enable, for instance, measuring all yeast two-hybrid interactions in a single pool. In his postdoc he is using C. elegans to develop tools for automating the annotation of neuronal gene expression patterns, as well as to dissect the signaling pathways required for axon guidance and synaptic maturation.
