MCB137/237 Spring 2020

Physical Biology of the Cell

Biology is being revolutionized by new experimental techniques that have made it possible to quantitatively query the inner workings of molecules, cells and multicellular organisms in ways that were previously unimaginable. The objective of this course is to respond to this deluge of quantitative data through quantitative models and the use of biological numeracy. The course will explore the description of a broad array of topics from modern biology using the language of physics and mathematics. One style of thinking we will emphasize imagines the kinds of simple calculations that one can do with a stick in the sand.

We will draw examples from broad swaths of modern biology from our department and beyond including cell biology (signaling and regulation, cell motility), physiology (metabolism, swimming), developmental biology (patterning of body plans, how size and number of organelles and tissues are controlled), neuroscience (action potentials and ion channel gating) and evolution (population genetics) in order to develop theoretical models that make precise predictions about biological phenomena. These predictions will be tested through the hands-on analysis of experimental data and by performing numerical simulations using Python. Physical biology will be introduced as an exciting new tool to complement other approaches within biology such as genetics, genomics and structural biology. The course will introduce students to the enabling power of biological numeracy in scientific discovery and make it possible for them to use these tools in their own future research.

The class as a whole will meet twice a week for one hour and a half. This time will be devoted to lectures, discussions and hands-on activities including Python exercises. Further, the class will be split into weekly one-hour lab sessions. During these lab sessions, students will work closely with the GSIs to implement the concepts they learned in class in the context of different biological problems. Homework assignment will be given every week and will represent 75% of the final grade. Twice during the semester, students will prepare a project. The first project will be a written assignment, while the second project will be presented in class. These projects will represent 25% of the final grade.

For undergraduate students (MCB137L), the projects will consist on carrying out an estimate on a biological phenomenon of interest following the style presented in class. These presentations will be five minutes long.

For graduate students (MCB237L) the project will consist on presenting a theoretical model developed in a recent paper of their choosing to the class. These presentations will be ten minutes long. Attending class and office hours
If you miss classes, it is your responsibility to get notes from one of your classmates. You cannot expect the instructor or GSI to redo the lecture during office hours.
Being able to attend office hours are a key to success. If you cannot attend any of the three offered office hours, you might want to reconsider taking this course.

Homework assignments
Homeworks are due at the beginning of class one week after they are posted.
Homeworks should be submitted through GradeScope (link) to the GSIs in PDF form. Any other form of homework submission will not be accepted. No late homeworks. Time management is key. Start to work on your homework assignments early and make use of office hours and our availability over Piazza.
It is important to describe your reasoning. Just writing an equation or drawing a plot does not constitute a satisfactory answer to a homework problem. All plots in the homeworks need to have labeled axes. All code used needs to be submitted through GraceScope by the homework due date. You can work in groups, but the answers should be your own. This includes the code!

Grading
Regrading is done only until a week after the homework solutions are posted. If you ask us to regrade an answer in a homework assignment, we reserve the right to regrade all the answers it that homework assignment. Your two worst scoring homeworks will not be considered for the final grade. We do not grade on a curve(distribution) or anything like that.
Title Due Date Required Materials Solutions
Homework 1 1/30 at 3:30 PM
  • Homework 1 Solutions
Homework 2 2/6 at 3:30 PM
  • Homework 2 Solutions
Homework 3 2/13 at 3:30 PM
  • Homework 3 Solutions
  • Python Code
Estimate Paragraph 2/13 at 3:30 PM
Homework 4 2/20 at 3:30 PM
  • Homework 4 Solution
  • Python Code, Problem 2
  • Python Code, Problem 5
2/27 at 3:30 PM
Homework 5 3/12 at 3:30 PM
  • Homework 5 Solution
  • Python Code, Problem 1
  • Python Code, Problem 2
Homework 6 4/2 at 3:30 PM
  • Homework 6 solutions
  • Python code, problem 1
  • Python code, problem 2
  • Python code, problem 3
Homework 7 4/4 at 8:00 PM
  • Homework 7 Solutions
  • Python Code, Problem 2
Homework 8 4/9 at 3:30 PM
  • Homework 8 Solutions
  • Python Code, Problem 2
  • Python Code, Problem 4
  • Python Code, Problem 5
Homework 9 4/16 at 3:30 PM
  • Homework 9 solutions
  • Python Code, Problem 2
  • Python Code, Problem 3
Homework 10 4/23 at 3:30 PM
  • Homework 10 Solutions
  • Python Code, Problem 1
  • Python Code, Problem 3
  • Python Code, Problem 4
Number Date Topics Materials Discussion
1
2 1/23 A feeling for the numbers in biology, Part II
  • Introduction to GradeScope and Python CoLab
  • Simple estimates
  • PBoC Chapters 2 & 3
  • Kinder & Nelson Chapters 1 - 3
3 1/28 An obsession with dN/dt. Bacterial Growth Part I: Solving the Exponential Growth Equation
4 1/30 Biological time scales. An aobsession with dN/dt. Bacterial Growth - Part II: Solving the Exponential Growth Equation
  • Measuring bacterial growth using image analysis, Part I
  • Python Code
  • Data
5 2/4 An obsession with dN/dt. Bacterial Growth Part III: The Physical Limits to Bacterial Growth
6 2/6 Diffusion, the null hypothesis of biological dynamics, Part I : Diffusion and Axonal Transport
7 2/11 Diffusion, the null hypothesis of biological dynamics, Part II. Diffusion using continuum theory and diffusion by coin flips
8 2/13 Diffusion, the null hypothesis of biological dymaics, Part III: Diffusion using Continuum Theory and Diffusion by Coinflips
9 2/18 Diffusion, the null hypothesis of biological dynamics, Part IV. Diffusion using master equations and FRAMP: Measuring diffusion using photobleaching
10 2/20 Diffusion, the null hypothesis of biological dynamics, Part V. A universal diffusion speed limit ofr enzyme catalysis and other reactions
11 2/25 Study haall to prepare for your first estimate
12 2/27 Biological Dynamics, Part I. The mean dynamics of the constitutive promoter
  • Diffusion by master equations, Part II
13 3/3 Biological dynamics, part II: The single-cell distribution of the constitutive promoter
14 3/5 Membraneless organelles adn phase transitions in biology, Part I. Entropy maximization and the second law of thermodynamics
  • Phase Separatation: Powerpoint Presentation
15 3/10 Membraneless organelles and phase transitions in biology, Part II: Free energy minimization
16 3/12 Membraneless organelles and phase transitions in biology, Part III: Free energy minimization and the emergence of phase separation
17 3/17 Membraneless organelles and phase transitions in biology, Part IV: Biological regulation of phase transitions. A life-or-death decision: THe lambda Switchh, Part I. The statistical mechanics rprotocol: ion channels and constitutive promoters
  • The Lambda Switch: Powerpoint Presentation
18 3/19 A life-or-death decision: The Lambda Switch, Part II. The statistical mechanics protocol: ion channels and constitutive promoters
  • Sequencing Depth: Binomial and Poisson distribution
19 3/31 A life-or-death decision: THe Lambda Switch , Part III. Simple repression by Lac and Lambdaa repressor
20 4/2 A life-or-death decision: The Lambda switch, Part IV. Cooperativity and the generation of biological sharpness
21 4/7 A life-or-death decision: The Lambda Switch, Part V. A dynamical systems view of the Lambda switch
22 4/9 A life-or-death decision: The Lambda switch, Part VI. A dynamical systems view of the Lambda Switch
23 4/14 Coronavirus by the numbers, Part I
  • Coronavirus by the Numbers: Powerpoint Presentation
24 4/16 Coronavirus by the Numbers, Part II
25 4/21 Dynamics of epidemics, Part I
26 4/23 Dynamics of epidemics, part II. Physical biology of the Cell Recap
27 4/28 Second Project Presentations, Part I
28 4/30 Second Project Presentations, Part II