Sha Cao

Assistant Professor


Sha Cao is highly motivated to pursue an academic career in bioinformatics and computational biology applied in translational sciences. My research tracks include: 1) development of novel statistical and machine learning techniques; and 2) addressing important translational and biological questions, through multiple omics data mining and quantitative modeling. Her current research focuses are:

1) Multiple omics data mining. This has been my main research focus, and the challenges we are dealing with include: how to effectively integrate multiple omics data types and enable knowledge transfer among them, locating latent structures within a dataset, and detecting locally homogeneous structures within the noisy background.

2) Cancer microenvironment and epigenetic regulation. Towards this goal, our specific aims are to understand: the regulatory effect of epigenome on transcriptome particularly regarding stress responses, and how the epigenome are aggregated in a way to cope with the cellular stresses.