Currently, there are five research groups at the Computational Biology Center. These groups are headed by faculty members Grégoire Altan-Bonnet, Christina Leslie, Franziska Michor, Chris Sander and José Vilar.
The research interests of the Altan-Bonnet Group are in studying the robustness and adaptability of self/non-self discrimination in the immune system, and includes combining experiments and computer models to understand T cell ligand discrimination.
The Leslie Group develops machine learning algorithms to study molecular systems from a global and data-driven perspective. These algorithms "train" on diverse high-throughput molecular and genomic data to learn predictive computational models. Current areas of study include transcriptional gene regulation, gene silencing by microRNAs, signal transduction and splicing. In addition, the Leslie lab pioneered the use of "k-mer" based string kernels for support vector machine classification of protein sequences into structural categories.
The Michor Group is interested in the evolutionary dynamics of cancer initiation and progression as well as anti-cancer therapy and resistance. Current areas of research include mathematical biology of human leukemias, kinetics of treatment responses to targeted therapy, cancer stem cells, evolution of drug resistance, and dynamics of metastasis formation.
The primary research interests of the Sander Group are in computational and systems biology, including predictive simulations of biological processes, integrated molecular profiling of disease states, gene regulation by small RNAs, structural genomics and the development of multiplex cancer therapy. In addition, the Sander Group leads community efforts to create an open-source information resource for biological pathways.
The research interests of the Vilar Group are in the integrative modeling of biological networks. These include gene regulation, signal transduction networks, and control of cell growth and death. In addition, they are also developing new computational approaches to determine, capture, and use relevant biological information, and are especially interested in stochastic analyses and in multilevel and multiscale methods.
There is an active faculty recruitment effort currently underway. Any interested individuals should visit our Jobs page.
