Quantitative Biology Module

Biology is being revolutionized by new experimental techniques that have made it possible to measure the inner workings of molecules, cells and multicellular organisms with unprecedented precision. The objective of this short module is to explore this deluge of quantitative data through the use of biological numeracy. We will survey exciting research examples from our department and beyond 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 Matlab.

Physical biology will be introduced as an exciting new tool to complement other approaches within biology such as genetics, genomics and structural biology. The module 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 research.

Course instructor: Hernan Garcia (hggarcia@berkeley.edu)

Course TA: Yang Joon Jim (yjkim90@berkeley.edu)

Class materials:


Schedule: Class meets in 177 LSA from 2pm to 4:30pm. See below for class dates.  

Class date Topics Materials


A Feeling for the Numbers in Biology: Estimation and biological numeracy

E. coli by the Numbers: Thinking up the bacterial census

Matlab tutorials: 1 and 2

Papers: Neidhardt1999

Powerpoint: Biological Numeracy, E. coli By The Numbers

Matlab code: Making simple plots


Bacterial Growth: Simulations, analyzing movies of growing colonies and fitting our data

Matlab tutorial: 3

Microscopy images of growing bacteria

Matlab code: Simulating bacterial growth, Analyzing movies of growing bacteria


Flies by the Numbers: The making of a fly one cell at a time.

Morphogen Gradients and the French Flag model

Powerpoint: Flies by the numbers

Recombination and the first mapping of a chromosome: Sturtevant1913.

Snapshots of developing fly embryos; Matlab code; Papers: Driever1989 and Liu2013.

Homework 1 (Solutions)


The Machines of the Central Dogma: DNA replication in bacteria and flies and transcription in the early fly embryo

A Probabilistic View of Biology, Part I: The coin flip metaconcept and the binomial distribution. Poisson distributions and probability of mutations.


Transcriptional elongation in flies: Data; Matlab code

Number of human and bacterial cells in a human body: Sender2016

Powerpoint: The Coinflip Metaconcept

Molecular Partitioning: Papers: Savage2010 and Rosenfeld2005 

Matlab tutorial: 4


A Probabilistic View of Biology, Part II: The coin flip metaconcept and the binomial distribution. Poisson distributions and probability of mutations.



A Probabilistic View of Biology, Part III: Poisson distributions and probability of mutations.

The Ubiquitous Nature of Binding Problems in Biology, Part I: Voltage-gated ion channels and ligand-receptor binding


Voltage-Gated Na Channel: Keller1986Keller1986 Data, Matlab code

Powerpoint: Binding in biology

Introduction to Statistical Mechanics for Life Scientists: Garcia2007b 

Homework 2


The Ubiquitous Nature of Binding Problems in Biology, Part II: Ligand-receptor binding and cooperativity



Regulatory Biology: How bacteria decide what to eat

Course survey

Gene expression in bacteria: Sample data setfull data set

Dissecting simple repression in bacteria: Garcia2011c

Homework 3


Matlab tutorials: We will assume no previous Matlab experience. These are small tutorials that introduce the different concepts we'll use in each class.

  1. Variable and arrays, and plotting.
  2. For-loops.
  3. Loading and displaying images (sample image).
  4. If-statements.


If you want to go beyond our introductory Matlab tutorials, here are some other great sources: 



  • Phillips, R., et al. (2013). Physical Biology of the Cell, 2nd Edition. New York, Garland Science.
  • Alberts, B. (2015). Molecular Biology of the Cell. New York, NY, Garland Science.
  • Milo, R. and Phillips, R. (to be published in 2016, can be downloaded from http://book.bionumbers.org/). Cell Biology by the Numbers. New York, NY, Garland Science.
  • Mahajan, S. (2010). Street-Fighting Mathematics: The Art of Educated Guessing and Opportunistic Problem Solving. MIT Press (2010).
  • Weinstein, L. and Adam, J.A. (2008). Guesstimation: Solving the World's Problems on the Back of a Cocktail Napkin. Princeton University Press.
Fall 2016
Monday, August 22, 2016