Big Data Analysis on Biomedical Related Problems

In this era of big data, imaging, digital pathology, genomics, proteomics, and electrophysiological data have become promptly available. As a consequence, complex statistical modeling and sophisticated computational tools have been developing to search through a large number of models, looking for meaningful patterns. We will continue developing and applying cutting edge analytical tools and statistical approaches to identify, explore, and implement effective uses of data, information, and knowledge for decision-making and problem-solving in public health. The aims of our research are as follows.

 Identify rare variants associated with complex traits;
 Investigate gene-gene and gene-environment interactions;
 Elucidate pathways of complex disease;
 Develop approaches for integrating ‘omics data;
 Construct prediction models;
 Develop algorithms or tools for combining different sources of data.