Critical state warning method for complex biological system based on high dimensional data

：刘锐（华南理工大学）
：2022-04-21 10:00
：Tencent Meeting ID：384498535（No Passward）

报告人：刘锐（华南理工大学）

时  间：4月21日上午10:00

地  点：腾讯会议ID：384498535（无密码）

内容摘要:

The occurrence and development of complex diseases can be characterized mathematically by dynamical systems.  From the perspective of dynamic system, both health and disease belong to local stable state, and the occurrence and development of complex disease is the dynamic evolution process of human body gradually transforming from healthy state to disease state.  From systematic evolution level of abstraction, many complex disease development process has a common characteristic, that is, from health to illness state between a "critical state", on or before the critical state period, by changing the way of life and positive development of medical intervention can effectively prevent the illness usually (reversible).  Therefore, the key of health management lies in how to quantify health criticality and realize early warning so as to implement effective intervention.  In this report, we will present some of our efforts and results in early warning of criticality of complex biological systems based on biomedical data.  It mainly involves the prediction method of the future state of the high-dimensional dynamical system, the screening method of the dynamic network markers, and the warning method of the critical point of the dynamical system. 

个人简介：

刘锐，华南理工大学数学学院教授。2001年至2010年在北京大学数学科学学院本硕博连读。2010年至今在华南理工大学工作。围绕复杂生物过程的临界点预警这一条主线，在数据挖掘与时间序列分析、生物分子网络的推断等几个方面发展数学理论与智能学习算法，在Nature Communications，Science Bulletin，Bioinformatics等杂志发表论文40余篇，主持过4项国家自然科学基金项目，2021年起主持国家自然科学基金 “数学与医疗健康交叉”重点研发专项。2019年起兼任广州市工业与应用数学学会副理事长、广东省工业与应用数学学会常务理事。2016年获评广州市“珠江科技新星”，2019年获得广东省杰出青年基金，2020年入选国家高层次青年人才，2021年获得上海市自然科学一等奖（第三完成人）。

 

联系人：周达