Our lab’s research involves designing algorithms that leverage biological networks to connect different types of experimental data and detect surprising relationships among them. We use such techniques to study human disease, in particular cancer and viral infection. We also focus on the dynamic behaviors of biological networks and develop techniques to reconstruct dynamic models of signaling pathways and transcriptional regulatory networks from high-throughput proteomic and transcriptomic data.
Updates from the Lab
Our Lag Penalized Weighted Correlation clustering algorithm has been published.
The CHTC GPU Lab now has a home page, and the first GPU hardware will be arriving to CHTC soon.
Atul successfully defended his PhD dissertation! Congratulations!