Course Identification

Introduction to biological physics

Lecturers and Teaching Assistants

Prof. Ofer Feinerman, Prof. David Biron, Prof. Ariel Amir
Dr. Aviram Gelblum

Course Schedule and Location

First Semester
Tuesday, 09:00 - 10:45
Wednesday, 09:00 - 10:45

Field of Study, Course Type and Credit Points

Physical Sciences: Lecture; Elective; Regular; 4.00 points
Chemical Sciences: Lecture; Elective; Regular; 4.00 points
Life Sciences: Lecture; Elective; Regular; 4.00 points
Life Sciences (Molecular and Cellular Neuroscience Track): Lecture; Elective; Regular; 4.00 points
Life Sciences (Brain Sciences: Systems, Computational and Cognitive Neuroscience Track): Lecture; Elective; Regular; 4.00 points


All courses in the first semester will be held on-line via zoom.





Language of Instruction


Attendance and participation

Expected and Recommended

Grade Type

Numerical (out of 100)

Grade Breakdown (in %)


Evaluation Type

Final assignment

Scheduled date 1


Estimated Weekly Independent Workload (in hours)



Mathematical models can explain observations and offer mechanistic insight pertaining to
complex phenomena. This course will provide a model-based introduction to biological physics.
Topics that commonly arise in modeling biological phenomena include non-linear dynamics and
stochastic processes. Students will acquire an introductory level familiarity with topics, as well
as with fundamental concepts in biology. Specific topics will be introduced through relevant
models of biological phenomenon and the students will learn to analyze such models and
assess their performance and predictive power under various conditions. Examples may widely
vary in scale, ranging from populations to cells and molecules.

We will address a wide variety of questions and subjects such as:

1. How is translation error rate  so low?
2. Are genetically identical populations identical? How do cells resist noise?
3. Can rod cells count photons?
4. How does a bug find food?
5. How big can a bacterium get?
6. Is there such a thing as too good (a predator)?
7. How much regulation goes into cell differentiation?
8. Does hardware need to be replaced perfectly for conservation of  function?
9. Information seeking behavior
10. How do flocking birds turn in unison?


Learning Outcomes

Upon successful completion of the course the students will:

  • Be acquainted with some of the major experimental and theoretical works in the field of biological physics.
  • Further obtain general knowledge of the main mathematical and physics methodologies that were applied to biological systems to date. Examples will touch on varoius subjects such as:: Statistical mechanics, phase transitions, Boltzmann distribution, The central dogma of biology The central dogma of biology, statistical noise and robustness,  Stochastic processes, Random Walks and diffusion, Non linear dynamics, quick primers, explanatory power, Information theory. 


Reading List