The goal of our lab is to develop artificially intelligent systems to translate a patient’s genome into precision diagnosis and treatment. Our premise is that this task will ultimately require comprehensive information about the structure of biological systems, including the internal organization of cells and tissues. With this principle in mind, we are developing methods that learn to model hierarchical cell structure directly from ‘omics data sets, including data on protein and gene networks. For this purpose, we run an experimental facility for systematic network measurement. As a second major activity, we are then using this network information to guide intelligent systems that translate genotype to phenotype. As supporting software, we are developers of Cytoscape, a popular platform for visualization and modeling of biological networks which is supported by a consortium of many labs including our own.

Awards and Achievements

  • AAAS
  • TR35
  • ISCB Overton Prize