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. In addition, we use machine learning to prioritize biological experiments for drug discovery, protein engineering, and other biomedical challenges.
There are open positions for new graduate student researchers in the Spring 2023 semester, particularly in computational drug discovery or network biology. Please contact Anthony if you are interested in learning more.
In the Fall 2019, 2021, and 2022 semesters Anthony co-taught Computational Network Biology with Sushmita Roy.
In the Spring 2016-2018 semesters Anthony taught Advanced Bioinformatics.
In the Spring 2015 semester Anthony taught a special topics course on Cancer Bioinformatics.