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227-0939-00L 6 Credits MSC D-MAVT , D-PHYS , D-BIOL , D-ITET , D-CHAB , D-HEST

Cell Biophysics

Lecturers & Examiners: Prof. Dr. Tomaso Zambelli
VVZ CR n/a

Last Updated: 2026-06-03 00:07:29

Abstract

Applying two fundamental principles of thermodynamics (entropy maximization and Gibbs energy minimization), an analytical model is derived for a variety of biological phenomena at the molecular as well as cellular level, and critically compared with the corresponding experimental data in the literature.

Objective

Engineering uses the laws of physics to predict the behavior of a system. Biological systems are so diverse and complex prompting the question whether we can apply unifying concepts of theoretical physics coping with the multiplicity of life’s mechanisms. Objective of this course is to show that biological phenomena despite their variety can be analytically described using only two principles from statistical mechanics: maximization of the entropy and minimization of the Gibbs free energy. Starting point of the course is the probability theory, which enables to derive step-by-step the two pillars of thermodynamics from the perspective of statistical mechanics: the maximization of entropy according to the Boltzmann’s law as well as the minimization of the Gibbs free energy. Then, an assortment of biological phenomena at the molecular and cellular level (e.g. cytoskeletal polymerization, action potential, photosynthesis, gene regulation, morphogen patterning) will be examined at the light of these two principles with the aim to derive a quantitative expression describing their behavior. Each analytical model is finally validated by comparing it with the corresponding experimental results from the literature. By the end of the course, students will also learn to critically evaluate the concepts of making an assumption and making an approximation.

Content

• Basics of theory of probability • Boltzmann's law • Entropy maximization and Gibbs free energy minimization • Ligand-receptor: two-state systems and the MWC model • Random walks, diffusion, crowding • Electrostatics for salty solutions • Elasticity: fibers and membranes • Molecular motors • Action potential: Hodgkin-Huxley model • Photosynthesis and vision • Gene regulation • Development: Turing patterns Theory and corresponding exercises are merged together during the classes.

Resources

Lecture Notes

No lecture notes because the two proposed textbooks are more than exhaustive!I am willingly available Mondays 17.00 o'clock - 18.00 in my office GLC F12.2 for whatever discussion about the lessons and the exercises.!!! I am using OneNote. All lectures will be broadcast via ZOOM, while corresponding videos of the previous years (lectures) are available in Moodle !!!

Literature

• (Statistical Mechanics) K. Dill, S. Bromberg, "Molecular Driving Forces", 2nd Edition, Garland Science, 2010. • (Biophysics) R. Phillips, J. Kondev, J. Theriot, H. Garcia, "Physical Biology of the Cell", 2nd Edition, Garland Science, 2012. • (Biophysics) P. Nelson, "Biological Physics", Student Edition, Chiliagon Science, 2020. • (Soft Matter) W. van Saarloos, V. Vitelli, Z. Zeravcic, "Soft Matter", Princeton University Press, 2024. As further deepening: • (Biophysics) D. Barrick, "Biomolecular Thermodynamics", 1st Edition, CRC Press, 2017. • (Biophysics) D.T. Haynie, "Biological Thermodynamics", 2nd Edition, Cambridge University Press, 2008.

General Information

Language
English
Levels
MSC
Frequency
Yearly recurring

Examination

Type
session examination
Mode
written 180 minutes
Aids
none (closed book)

Course Components

Type Title Time & Place Hours
lecture with exercise Cell Biophysics No time listed 4 h weekly

Offered In