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 manuscript Practical model selection for prospective virtual screening has been published with software on GitHub.
We contributed to a drug function prediction study that is now available on bioRxiv.
Our Temporal Pathway Synthesizer manuscript has been published.