报告题目：Rich and realistic dynamics of resource quality based population models
报 告 人：况阳 教授（美国亚利桑那州立大学）
报告时间：6月14日上午10：30-11：30
报告地点：腾讯会议号 8779667496
报告摘要：All organisms are composed of multiple chemical elements such as nitrogen (N), phosphorus (P), and carbon (C). P is essential to build nucleic acids (DNA and RNA) and N is needed for protein production. To keep track of the mismatch between P requirement in the consumer and the P content in the producer, stoichiometric models have been constructed to explicitly incorporate food quality and quantity. Most stoichiometric models have suggested that the consumer dynamics heavily depend on P content in the producer when the producer has low nutrient content (low P:C ratio). Motivated by recent lab experiments, researchers explored the effect of excess producer nutrient content (extremely high P:C ratio) on the grazer dynamics. This phenomenon is called the stoichiometric knife edge. However, the global analysis of these resource quality based models is challenging because the phase plane/space is separated into many regions in which the governing nonlinear equations are different. The aim of this talk is to present an overview of the rich and novel dynamics embodied in these stoichiometric population models and its many biological implications and present an alternative framework to build mathematically more tractable and biologically more plausible models.
报告人简介：Yang Kuang is a professor of mathematics at Arizona State University (ASU) since 1988. He received his B.Sc from the University of Science and Technology of China in 1984 and his Ph.D degree in mathematics in 1988 from the University of Alberta. He is the author of more than 200 refereed journal publications and 16 books (including 11 special issues) and the founder and editor of Mathematical Biosciences and Engineering. He has directed 28 Ph.D dissertations in mathematical and computational biology and several major (funding exceeding $1m) multi-disciplinary research projects in US. He is well known for his efforts in developing practical theories to the study of delay differential equation models and models incorporating resource quality in biology and medicine. His recent research interests focus on the formulation and validation of scientifically well-grounded and computationally tractable mathematical models to describe the rich and intriguing dynamics of various within-host diseases and their treatments. These models have the potential to speed up much-needed personalized medicine development.
