报告主题：计算系统医学展望
报告人： 周小波 教授 （Wake Forest University）
报告时间：2018年 3月15日（周四）14:30
报告地点：校本部G507
邀请人：应时辉
报告摘要：Precision medicine initiative (PMI) is making it increasingly feasible for physicians to prescribe the right drug, at the right dose, at the right time according to the makeup of their patient’s genome, making genome informed clinical decision support technologies as a reality. Computational systems medicine paves a way to PMI at systems level. In this talk, I will give a brief overview of our research projects on the computational systems bioinformatics, clinical informatics, systems biology and imaging informatics. At molecular level, we will decipher genetics and epigenetic code of Alternative Splicing using a newly developed multi-label and multi-layer deep learning neural network, and then we apply it to TCGA cancer signature discovery. By integrating the signatures from biomedical big data such as genome, imaging and electronic medical records (EMR), we investigate signature-based drug mining approaches to reveal the underlying mechanisms of drug responses, and thus to optimize personalized medicines. At systems level, we will demo how to integrate intracellular, intercellular and tissue level data to model disease progress. The multiscale modeling system established will provide us a critical tool to see how we can manipulate biological conditions to interrupt disease development, which eventually leads to the cure of the diseases. We recently pioneered a new direction called imaging aided surgical design and device optimization. We will demo how to develop a novel biomechanical property-based machine learning approach to prevent Aortic Valve Insufficiency after transcatheter aortic valve replacement (TAVR). Putting these studies together, we hope to draw a big picture of the trend of computational systems medicine.
欢迎教师、学生参加 ！