Course Identification

Cell biology and sustainability by the numbers

Lecturers and Teaching Assistants

Prof. Ron Milo
Dr. Ron Sender, Dr. Yinon Moise Bar-On

Course Schedule and Location

First Semester
Monday, 11:15 - 13:00, Belfer, Botnar Auditorium

Field of Study, Course Type and Credit Points

Life Sciences: Lecture; Elective; Regular; 2.00 points
Life Sciences (Molecular and Cellular Neuroscience Track): Lecture; Elective; Regular; 2.00 points
Life Sciences (Brain Sciences: Systems, Computational and Cognitive Neuroscience Track): Lecture; Elective; Regular; 2.00 points
Life Sciences (Computational and Systems Biology Track): Lecture; Elective; Regular; 2.00 points


* December 2nd, 2019, the lecture will be held at Wolfson Auditorium


Knowledge of molecular biology at the level of an introductory undergraduate course is required. Alternatively, if no such course was taken, willingness to read relevant chapters in the first few weeks of class is important in order to gather knowledge. No advanced math required, but love for numbers is useful.



Language of Instruction


Attendance and participation

Required in at least 80% of the lectures

Grade Type

Numerical (out of 100)

Grade Breakdown (in %)


Evaluation Type

Final assignment

Scheduled date 1


Estimated Weekly Independent Workload (in hours)



Over the past decades, biology has evolved rapidly from a descriptive, qualitative discipline to a more analytical, data-driven and quantitative one. Our ability to collect numbers that describe the most basic molecular processes within the cell has increased significantly, and simple calculations based on these data can provide important insights and enrich our scientific intuition.

This course is aimed at exposing students to the practice of making back of the envelope calculations (so called Fermi problems) with key numbers in biology, and its useful applications in research. We will learn how to identify the major factors that determine the order of magnitude of the results, when to allow simplification, how to calculate them efficiently, and how to avoid common pitfalls.

The course is composed of weekly lectures on different aspects of quantitative cell biology through many examples of basic (yet often surprising) questions:

  • Size and geometry (e.g. What is larger, mRNA or the protein it codes for? How many cells are there in a human?)
  • Concentrations and absolute numbers (e.g. What is the elemental and macromolecular composition of a cell? How many virions result from a single viral infection?)
  • Rates and durations (e.g. How long does it take cells to copy their genomes? What is faster, transcription or translation? What are the time scales for diffusion in cells?)
  • Energy, food & planet Earth (e.g. What is the power consumption of a cell? How much land is needed to supply our food?)
  • Information and errors (e.g. What is the mutation rate during genome replication? What is the error rate in transcription and translation?)

As part of the final assignment, students will present a calculation in front of the class (ideally in application to their field of research) and an active discussion by the course participants will follow. 

There will be 5 written homework assignments during the course.

Learning Outcomes

Upon successful completion of this course students should be able to:

  1. Demonstrate how knowledge of key numbers can be used to make useful inferences in cell biology and sustainability, and applied in research.
  2. Experienced hands-on making back of the envelope calculations as a powerful tool in biology.
  3. Avoid pitfalls in interpretation and correctly balance the complexity of biology and the clear-cut deductions often used potently in the physical sciences.
  4. Bring a deeper quantitative perspective to their field of research expertise.

Reading List

Course book is freely available at:

Specific reading material will be given during the course.

Those who did not take a molecular biology course should read the first few chapters of "Essential Cell Biology", Alberts et al, Garland Science