时间：2025年8月12日（周二）下午15:30-16:10

Time：15:30-16:10, Tuesday, August 12, 2025

主持人: 西湖大学交叉科学中心讲席教授汤雷翰

Host: Dr. Leihan Tang, Chair Professor, the Center for Interdisciplinary Studies

地点：西湖大学云谷校区学术环E10-211

Venue:E10-211, Yungu Campus

讲座语言：英文

Lecture Language: English

Dr. Shiling Liang（梁师翎）

Max Planck Institute for the Physics of Complex Systems

主讲人/Speaker：

Shiling Liang is an ELBE Postdoctoral Fellow at the Center for Systems Biology Dresden (CSBD), with a joint affiliation at the Max Planck Institutes for Physics of Complex Systems (MPI-PKS) and Molecular Cell Biology and Genetics (MPI-CBG). He received his Ph.D. in Physics from EPFL in 2024, following a joint B.Sc. from Beijing Normal University and the University of Manchester in 2018. His research focuses on fundamental principles of non-equilibrium thermodynamics and their application to understanding the physical constraints that shape living systems.

讲座摘要/Abstract:

Living cells process information through biochemical networks operating far from equilibrium. Understanding how these systems respond to finite perturbations—changes in enzyme concentrations or metabolic fluxes—is crucial for deciphering cellular computation. While the fluctuation-dissipation theorem describes near-equilibrium responses, it fails for the strong perturbations common in cellular regulation.

This talk presents a rigorous framework addressing this gap. We establish an exact identity relating nonlinear responses to linear ones through a physically meaningful scaling factor, built on a connection between steady-state responses and mean first-passage times. This enables bidirectional inference: predicting global responses from local biochemical changes, or inferring metabolic costs from measurable observables. We also derive a universal response resolution limit—a strong-perturbation analogue of the fluctuation-dissipation theorem—bounding signal detectability by intrinsic fluctuations. This reveals fundamental signal-to-noise constraints in biochemical sensors and regulatory circuits.

Using transcriptional regulation as a paradigm, we show how these parameter-independent bounds constrain the computational expressibility of gene networks. Reliable detection of transcription factor changes requires fold-changes exceeding a universal threshold, independent of biochemical details. Our framework provides a rigorous foundation for understanding physical limits of cellular information processing, with applications from metabolic control to signal transduction.

[1] Bao, Ruicheng, and Shiling Liang. " Nonlinear Response Identities and Bounds for Nonequilibrium Steady States." arXiv preprint arXiv:2412.19602 (2024).

讲座联系人/Contact:

交叉科学中心，徐恺吟，邮箱：xukaiyin@westlake.edu.cn

Center for Interdisciplinary Studies, Kaiyin Xu, Email: xukaiyin@westlake.edu.cn