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In recent years, novel biotechnologies and computational tools have revealed a diverse landscape of gene, RNA and protein regulation in eukaryotic cells. These diverse molecular species collaborate and interact to execute complex cellular programs in a ‘network’ of interactions between the individual species.  This network can be used together with computational algorithms that analyze high-throughput measurements of messenger RNA (mRNA) via RNA-Seq from a tissue or cell population of interest to infer specific changes in protein signaling that give rise to the observed differences in RNA expression. Uncovering how a network can be perturbed in disease can help us identify drug targets.

The goal of my ongoing research is to build better integrative models of high throughput data and then use these models to study the changes that occur in diverse datasets  that occur in disease.

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