Exciting developments in sequencing technologies offer multi-facetted molecular pictures of complex diseases, from cell-level (single-cell sequencing) to cohorts (bulk sequencing), and across different molecular domains (genetics, epigenetics etc). These large, comprehensive and yet disparate data still requires intelligent approaches to interpret their contexts and to inform novel therapeutics for the diseases. Situated in Manhattan, New York, Song Lab aims to harness the full potentials from these big data, take advantages of huge computational resources (super-computer, Minerva) to build informative models of the complex genetic diseases. Collaboratively working with clinicians and biologists, the ultimate goal is to advance the personalized medicine and cure the complex diseases.

  • Gene regulator network inference method development

  • Integrative analysis of multi-facetted molecular data

  • Identifying novel mechanisms to target unmet clinical needs.