2025秋季学期交叉科学中心博士生课程

课程负责人：周珍楠

课程学分: 3

课程时间：星期一 13:30-15:55

课程地点：E13-207，云谷校区

This course explores the principles and computational methods essential for modeling multiscale systems prevalent in science and engineering, including materials science, fluid dynamics, and biological processes. Traditional single-scale models often fall short in capturing the complexity of these systems. This course introduces a hierarchy of physical models, from quantum mechanics and molecular dynamics to kinetic theory and continuum mechanics. It emphasizes analytical and computational techniques connecting microscopic mechanisms to macroscopic behavior, such as matched asymptotics, averaging, homogenization, multigrid methods, fast multipole methods, and Heterogeneous Multiscale Methods (HMM). Students will learn to build and analyze models based on first principles rather than empirical relations, tackling complex problems with multiscale coupling effects like equations with multiscale coefficients, dynamics across multiple timescales, and rare events. The course aims to cultivate a sophisticated multiscale perspective for modeling and computation, preparing students to address cutting-edge research and complex engineering challenges through a combination of theory, analysis, and computational practice.

课程大纲

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课程大纲

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4. BIO5125 定量生物学

课程负责人：王寿文

课程学分: 2

课程时间：星期五 09:50-11:25

课程地点：E10-215，云谷校区

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5. BIO5129 合成生物学前沿

课程负责人：陈子博

课程学分: 3

课程时间：星期四 15:10-17:45

课程地点：E10-211，云谷校区

Synthetic biology is an innovative and rapidly evolving field that merges principles from biology, engineering, physics, chemistry, and computer sciences to design and construct new biological systems or redesign existing ones for purposeful applications. This course offers a comprehensive exploration of synthetic biology, tracing its conceptual foundations and cutting-edge advancements. Beginning with an introduction to the three major schools of thought in synthetic biology, the course journeys through the molecular biology revolution of the 1970s, the development of biocircuits, and the emergence of genetic engineering tools. Students will delve into key concepts such as bistability, oscillations, stochasticity, metabolic engineering, molecular programming, and population-level dynamics. The course also tackles advanced concepts like kinetic proofreading, combinatorial complexity, neural networks, and proteome partitioning, while addressing real-world implications through discussions on ethics and biosafety.

课程大纲

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Biological organisms exhibit many fascinating behaviors, from magical transformation of matter via thousands of steps of metabolic reactions, to robust homeostasis adapting to rapidly shifting environments, to survival and growth that balances persistence in extreme conditions and all-out ventures into opportunistic moments of rich nutrients, to dominance and terraforming of surroundings to its own advantage. Such complex behaviors involving lots of interacting components demand a rigorous and quantitative way of reasoning, like how we reason about complex engineered machines. In this course, we introduce and master tools of reasoning from three different schools of thought pondering about life: physics, system, and industry. Physics asks what life is as an object. System asks how life works as a machine. Industry asks how life could be useful as a tool. These three schools of thought have distinct origins, approaches to analysis, and goals. They shape how we think about life forms. The tools we learn from them span a wide range, from order of magnitude estimate to design of a single protein molecule, from Markov chains to control systems, from simple reasoning based on central dogma to whole-genome models. By the end of the course, you will be able to integrate these tools and perspectives into a cohesive whole and have the confidence to reason about any biological problem thrown at you, from single molecules to populations of organisms. No background needed, but an exuberant love for biology is mandatory.