报告题目：Detecting the early-warning signal of the critical transition for complex biological diseases

报告时间：2021年6月17日，星期四，上午8:30-11:30（北京时间）

腾讯会议：757 779 767 ，密码：0617

报告人: 刘锐教授，华南理工大学

报告摘要：

Complex disease progression, such as cancer, is generally a nonlinear process with three stages, i.e., normal state, pre-disease state, and disease state, where the pre-disease state is the critical state just before disease appearance. It is generally a challenging task to identify the pre-disease state. In this talk, by exploiting the information of differential associations among the observed molecules between the normal and pre-disease states, we introduce a computational approach, i.e., single-sample landscape entropy (SLE) method, to identify the tipping point during disease progression with only one sample data. Specifically, by evaluating the disorder of a network projected from a single-sample data, SLE effectively characterizes the criticality of this single sample network in terms of network entropy, thereby capturing not only the signals of the impending transition but also its leading network, i.e. dynamic network biomarkers.

报告人简介：

    刘锐，华南理工大学数学学院教授，2001年9月至2010年6月在北京大学数学科学学院本硕博连读。2010年7月至今在华南理工大学工作，2016年4月晋升教授。目前兼任华南理工大学数学学院大数据中心副主任、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。主持国家自然科学基金重点专项、广东省杰出青年基金等项目。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、Bioinformatics等杂志发表SCI论文40多篇。