Novel Deep Learning Methods Development，to investigate how the tumor microenvironment influence the progress of solid tumors including glioma and renal cell carcinoma

      We have particular interests in developing novel deep learning methods such as new probabilistic models,  derivative methods, followed by using these new methods to datamine high throughput omics data for investigating the mechanisms associated with tumor microenvironment and progress and tumorigenesis of solid tumors.