Upcoming Talk:
Title: Modeling Microbial Networks: Unraveling Gut Ecosystem Dynamics for Disease Management
Speaker: Jianan Yin (尹嘉楠), Research Assistant, BIMSA; Doctoral Student, Tianjin University
Time: Wed., 2:00-3:45 pm, Dec. 13, 2023
Venue：Shuangqing Complex Building 双清B725报告厅
Zoom ID: 427 154 2002 PW: BIMSA
Abstract:
The gut microbiota is vital for digestive health and immune function. However, current research tends to focus on individual microbial strains, missing the broader understanding of the entire ecosystem. Constructing microbial networks is key to understanding how these communities form, but existing methods have limitations, prompting the need for new approaches. By merging concepts from evolutionary game theory, predator-prey dynamics, and graph theory, we developed an ecological network featuring directionality, symbols, and weights. This groundbreaking model overcomes previous limitations, enabling us to reconstruct comprehensive, dynamic, and personalized networks (idopNetwork) from static abundance data. We applied this approach to examine interactions among microbial strains in the gut microbiota of both healthy individuals and those with inflammatory bowel disease. This method deepens our understanding of microbial operations within the ecosystem, particularly across various disease states. Such insights offer crucial guidance for tailoring precise microbiota-based therapies for these conditions.
Past Talks:
Title: The statistical topology theory of aging
Speaker：Rongling Wu （邬荣领），BIMSA
Time：Wed., 2:00-3:45 pm, Dec. 6, 2023
Venue：Shuangqing Complex Building 双清B725报告厅
Zoom ID：427 154 2002 PW：BIMSA
Abstract:
The traditional view suggests that aging is a progressive decline of physiological and physical function with passage of time. However, increasing evidence shows that aging may be subject to abrupt change in metabolic capacity within a certain time window of the lifespan. This phenomenon, in conjunction with the multifactorial etiology of aging, makes it extremely difficult to portray a comprehensive atlas of when and how aging is progressed. In this talk, I will present a new norm of statistical mechanics for coalescing all aging-related or even -unrelated factors into informative, dynamic, omnidirectional, and personalized networks (idopNetworks) from cross-sectional data. The integration of GLMY homology theory into idopNetworks hastens the formulation of statistical topology as a new theory to extract and excavate the fundamental principles behind aging processes from increasing bulks of data at various levels of organization from molecules to cells to organs to total organisms. I will demonstrate the applied value of the statistical topology in disentangling aging in practice.
Title: The metabolomic physics of complex diseases
Speaker：Shuang Wu (吴双，BIMSA visiting PhD candidate)
Time: Wed., 2:00-3:45 pm, Nov. 29, 2023
Venue: Zoom ID: 427 154 2002 PW: BIMSA
Abstract:
Human diseases involve metabolic alterations. Metabolomic profiles have served as a vital biomarker for the early identification of high-risk individuals and disease prevention. We have leveraged a statistical physics model to combine all metabolites into bidirectional, signed, and weighted interaction networks and trace how the flow of information from one metabolite to the next causes changes in health state. We integrate concepts from ecosystem theory and evolutionary game theory to model how the health state-dependent alteration of a metabolite is shaped by its intrinsic properties and through extrinsic influences from its conspecifics. We code intrinsic contributions as nodes and extrinsic contributions as edges into quantitative networks and implement GLMY homology theory to analyze and interpret the topological change of health state from symbiosis to dysbiosis. The application of this model to real data allows us to identify several hub metabolites and their interaction webs, which play a part in the formation of inflammatory bowel diseases.
Title: Quantitative thoughts and their usefulness
报告人：Kiranmoy Das，BIMSA 研究员
时间: 11月22日， 周三，下午2：00-3：45
线下地点：双清B725报告厅
线上Zoom: 816 6785 5492 密码：666666
Abstract:
Quantitative thoughts always play an important role in science. In recent years, due to the availability of vast datasets it is more important to analyze those datasets appropriately for obtaining useful scientific decisions. In this talk, I will discuss some important statistical issues related to data analysis and inference methods. I will use real-life datasets to illustrate those issues.
Title: Metabolic crosstalk in the aging brain
报告人：Chengwen Xue（薛程文），Qiuchen College , Tsinghua University
时间: 11月15日， 周三，下午2；00-3：45
线下地点：双清B725报告厅
线上Zoom: 816 6785 5492 密码：666666
Abstract:
The brain is a complex organ composed of distinct modules that govern thought, memory, motion, emotion, touch, vision, olfaction, and every process that regulates the body, respectively. The overall function of the brain critically relies upon the coordination among these modules. Despite extensive investigation on its mechanism, we still know little about how different brain regions crosstalk and communicate as a cohesive whole. In this talk, I will present a new model of statistical mechanics for reconstructing inter-module crosstalk networks in the aging brain. These networks can capture a full set of interaction properties, including bidirectionality, sign, weight, and feedback cycle. We use this model to analyze metabolic data collected from the mouse brains at a spectrum of ages, identifying several key metabolites that mediate inter-modular crosstalk and its age-specific change in the mouse brain. This model could potentially serve as a tool to unveil the genetic and developmental secrets of how the brain functions and dysfunctions during aging processes. (Joint work with Shen Zhang and Rongling Wu at Tsinghua University Yau Mathematical Sciences Center and Beijing Institute of Mathematics and Applications, Daqi Cao at Beijing University of Architecture and Civil Engineering, Mengmeng Sang at Nantong University).
Title: idopNetwork as a tool to dissect complex systems
报告人：Ang Dong (董昂）Post-doc researcher, Beijing Institute of Mathematics and Applications
时间: 11月8日， 周三，下午2：00-3：45
线下地点：双清B725报告厅
线上Zoom: 816 6785 5492 密码：666666
Abstract:
The past few years have seen the development of powerful computational models for reconstructing informative, dynamic, omnidirectional, and personalized networks (idopNetworks) of complex systems. We pack an R-based cartographic tool for idopNetwork reconstruction from any data. The tool includes several key steps, including fitting power curve fitting based on allometrical scaling law, functional clustering, LASSO-based variable selection, quasi-dynamic ordinary differential equation solving, species abundance decomposition and network visualization. Ultimately, it can coalesce all nodes into multilayer idopNetworks. We demonstrate the utility of this tool by analyzing different organs that are spatially interconnected via microbiomes using two datasets from the gut microbiota and plant microbiota. Given that biodiversity and organization vary biogeographically at different scales, idopNetwork will find its widespread application to modelling and estimating interspecific interactions with differing functions across space.
Title: The genetic architecture of competition and cooperation
报告人：张珅， 致理书院, Tsinghua University
时间: 11月1日， 周三，下午2:00-3:45
线下地点：双清B725报告厅
线上Zoom: 951 7537 9655 密码：666666
Abstract:
This report primarily discusses how evolutionary game theory can be used to interpret the dysbiotic gut microbiota of inflammatory bowel disease (IBD) patients. We will focus on one of two types of IBD - ulcerative colitis (UC). The pathogenesis of UC is believed to be closely related to the shift of the gut microbiota from symbiosis to dysbiosis, and this shift leads to the abnormal activation of the immune system and the occurrence of inflammation. Here, we integrate the principle of evolutionary game theory to formulate the mathematical equations describing how microbes interact with each other in the gut microbiota. These equations found a basis for the reconstruction of informative, dynamic, omnidirectional, and personalized networks (idopNetwork). The topological analysis of idopNetwork can help to identify key microbial interaction pathways underlying the shift of the gut microbiota from the symbiosis to dysbiosis and vice versa. I will demonstrate this idea by analyzing a real dataset of the gut microbiota.
Title: Evolutionary Game Theory Acts in the Dysbiotic Gut Microbiota
报告人：高天辰 Visiting Doctoral Candidate, Tsinghua University Yau Mathematical Sciences Center,
时间:10 月25日， 周三，下午2：00-3：45
线下地点：双清B725报告厅
线上Zoom: 951 7537 9655 密码：666666
Abstract:
This report primarily discusses how evolutionary game theory can be used to interpret the dysbiotic gut microbiota of inflammatory bowel disease (IBD) patients. We will focus on one of two types of IBD - ulcerative colitis (UC). The pathogenesis of UC is believed to be closely related to the shift of the gut microbiota from symbiosis to dysbiosis, and this shift leads to the abnormal activation of the immune system and the occurrence of inflammation. Here, we integrate the principle of evolutionary game theory to formulate the mathematical equations describing how microbes interact with each other in the gut microbiota. These equations found a basis for the reconstruction of informative, dynamic, omnidirectional, and personalized networks (idopNetwork). The topological analysis of idopNetwork can help to identify key microbial interaction pathways underlying the shift of the gut microbiota from the symbiosis to dysbiosis and vice versa. I will demonstrate this idea by analyzing a real dataset of the gut microbiota.
Title: A high-order game theory of complex systems
Speaker: Rongling Wu (BIMSA)
Time: 10 月18日， 周三，下午2；00-3：45
线下地点：双清B725报告厅
线上Zoom: 951 7537 9655 密码：666666
Abstract:
Interactions among the underlying units of a complex system are not limited to dyads, but can also occur in larger groups. However, no generic model for capturing both lower- and high-order interactions has been developed, making it impossible to chart a comprehensive picture of internal workings within complex communities. Here, we propose a new norm of statistical mechanics derived from the integration of evolutionary game theory and behavioral ecology theory to encode all units (nodes) and their bidirectional, signed, and weighted interactions (including links and hyperlinks) at various orders into hypernetworks. We apply our method to multi-species microbial communities, showing that the method can distinguish between how pairwise interactions modulate the abundance of the third species and how the altered abundance of each species in turn governs interactions between other species and further predict the eco-evolutionary trajectories of community structure and behavior. We validate the new method by designing a series of in vitro mono-, co-, and tri-cultural experiments of three bacterial species. Our hypernetwork model paves the way for inferring a detailed network fundamental to complex systems (joint work with Li Feng, Shen Zhang, Chengwen Xue, Shuo Li Liu, Ang Dong, Christopher H. Griffin, and Shing-Tung Yau).
Title: Foundational and Philosophical Aspects of Game Theory and Evolution
Speaker: Shuoli Liu, Qiuzhen College
Time: Wednesday, 2:00-3:45 pm, October 11, 2023
Venue: Lecture Hall B725, Tsinghua University Shuangqing Complex Building A（清华大学双清综合楼A座B725报告厅）; Online Zoom: 951 7537 9655 Passcode：666666
Abstract:
This introductory seminar will explore the foundational and philosophical aspects of game theory and evolution. In particular, we will examine how an evolutionary game theorist would treat the randomness of data and observations, and how it compares with the classic model by frequentists. For example, we will talk about the game theorists' approach to the randomness of choice data, height data, and presence of suboptimal phenotypes. Finally, we will discuss how the foundational axioms used by game theorists differ from those in frequentist statistics by introducing the influential works of von Neumann and Morgenstern, the fathers of game theory.
Title: How Game Theory Can Help Us Understand the World: From the Dark Forest to the Evolution of Cooperation (现实世界的博弈论：从黑暗森林到合作共赢)
Speaker: Shuoli Liu, Qiuzhen College
Time: Wednesday, 2:00-3:45 pm, September 20, 2023
Venue: Lecture Hall B725, Tsinghua University Shuangqing Complex Building A（清华大学双清综合楼A座B725报告厅）; Online Zoom: 951 7537 9655 Passcode：666666
Abstract:
This report will take you on a journey through the fascinating world of game theory, the mathematical study of how people or groups make decisions in situations where their actions affect each other. You will see how game theory can help us explain and predict various phenomena, such as why civilizations may hide in the dark forest of the universe, how nuclear weapons can prevent wars, how criminals can cooperate or betray each other, and how cooperation can emerge among selfish individuals. You will also take a glimpse of the basic concepts and tools of game theory, such as single person games, representation theory of weak orderings, fixed-point theorem, Nash equilibria, games on graphs, and the dynamics of cooperation. By the end of this report, you will have a better understanding of game theory, its central role in economic and social research, and its applications to various other fields and disciplines.
