Research Areas

Research Areas

By design, the Computational Biology and Medicine Program is not focused in one area of computational biology. Faculty in CBM engage in a wide range of research, as described here, providing students with diverse opportunities for thesis study. More information about the research of our graduate faculty can be found on the Faculty Directory page.

Computational genomics and gene regulation

  • Computational analysis of epigenomic and transcriptomic data
  • Development of new sequencing technologies and analysis methods
  • Modeling transcriptional and post-transcriptional gene regulation
  • Discovery and functional characterization of non-coding RNAs
  • Integrative genomics of multi-layer data sets
  • Disease surveillance, pathogen tracking, and predictive infectious models

Quantitative and systems biology

  • Quantitative modeling of the integration of signal transduction, gene regulation and cell activation
  • Quantitative methods: live-cell imaging, mass cytometry
  • Single-cell stochastic and deterministic modeling
  • Multiscale modeling, from molecular and cellular levels to tissue levels
  • Agent-based modeling of cell populations

Cancer biology and genomics

  • Computational analysis of massive tumor profiling data sets
  • Modeling and predicting response to therapeutics and designing drug combinations
  • Modeling tumor-stromal interactions in the tumor microenvironment

Structural biology and biophysics 

  • Analysis, modeling, and prediction of biomolecular structure and assembly
  • Simulation of biomolecular function and mechanism
  • Macromolecular interactions in subcellular targeting
  • Protein folding and aggregation
  • Protein-protein interaction partner discovery
  • Structure-based drug design
  • Membranes and membrane protein structure and function

Computational neuroscience

  • Large scale data acquisition, analysis, and curation
  • Sensory coding and information processing
  • Biophysical modeling of neurons and neural circuits
  • Dynamical systems modeling
  • Stimulation-based strategies for treatment of neurological disorders


Computational modeling

Organ-level modeling and bioengineering