题目：Harness open genomic data and artificial intelligence to discover new cancer therapeutics
报告人: BinChen 教授
时间：2019年7月10日（周三）上午9:00
地点：苏州大学欧洲杯官网402楼一楼A101会议室
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报告摘要：Rapidly decreasing costs of molecular measurement technologies not only enable profiling of disease sample molecular features (e.g., transcriptome, proteome, metabolome) at different levels (e.g., tissues, single cells), but also enable measuring of molecular signatures of individual drugs in clinically relevant models. Exploring methods to relate diseases to potentially efficacious drugs through various molecular features is critically important in the discovery of new therapeutics. We propose to employ a systems-based approach that identifies drugs that reverse the molecular state of a disease. Using this approach, we and others have successfully identified drug candidates for various diseases. We have shown that the success of this approach is made possible by multiscale procedures, such as quality control of tumor samples, selection of appropriate reference normal tissues, evaluation of disease signatures, and integration of drug expression profiles from multiple cell lines. There is a plethora of relevant datasets and analysis modules that are publicly available, yet are isolated in distinct silos, making it tedious, if not possible, to implement this approach in translational research for many labs. In this talk, I will describe in detail how these resources and analysis modules can be orchestrated in translational research. I will mainly use liver cancer as an example.
报告人简介：