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 handson 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). Office hours: Thursdays 4pm to 5pm at 501C LSA.
Course TA: Simon Alamos (simon.alamos@berkeley.edu). Office hours: Mondays 4pm to 5pm outside of 501C LSA.
Class materials:
 Course syllabus (subject to change)
 Download and install Matlab by logging on to the UC Berkeley Software Central
Schedule: Class meets Tuesdays and Thursdays in 150D Moffitt from 2pm to 4pm (lecture and lab/discussion).
Homework policy: Homeworks are due at the beginning of class one week after they are posted. Solutions will be posted two days after the homeworks are submitted, and homeworks will be returned a week after they are submitted. NO late homeworks will be accepted (late means anytime after class starts the day the homework is due) unless you have a note from someone like a doctor or a Dean. You may discuss the homework with others, but your explanations and derivations must be your own. Your logic and the significance of your results should also be explained.
Class date 
Topics 
Materials 
1/17 
A feeling for the numbers in biology: Estimation and biological numeracy E. coli by the Numbers 
A feeling for the numbers: PowerPoint Presentation Matlab tutorials: 1 and 2 
1/19 
E. coli by the Numbers 
Making simple plots: Matlab code Adding scale bars to images: Images, Matlab code 
1/24 
Bacterial growth: Physical limits to bacterial growth

Homework 1 out, due 1/31: Sender2016, Li2014, Schmidt2016, Mass spec data on ATP synthase The physical limits to bacterial growth: PowerPoint Presentation Papers: An obsession with dN/dt (Neidhardt1999), Stouthamer1973, VanOijen2006 
1/26 
Bacterial Growth: Simulations, analyzing movies of growing colonies and fitting our data

Simulating bacterial growth: Matlab code Analyzing movies of growing bacteria: Microscopy images of growing bacteria, Matlab code V1 
1/31 
Flies by the Numbers: The physical limits to DNA replication in development 
Homework 1 due Homework 2 out, due 2/7: Sturtevant1913, Gregor2007a, Gregor2007b Analyzing movies of growing bacteria: Matlab code V2 Flies by the Numbers: PowerPoint Presentation Recombination and the first mapping of a chromosome: Sturtevant1913. 
2/2 
Flies by the Numbers: The physical limits to transcription in development 
Transcriptional elongation in flies: Data; Matlab code 
2/7 
Diffusion: Axonal transport and deriving the diffusion equation 
Homework 2 due (send abstract for estimate over email to Hernan and Simon) Diffusion: PowerPoint Presentation 
2/9 
Diffusion: Numerical simulations 
Homework 3 out, due 2/21: Klumpp2013 
2/14 
Diffusion to capture and the physical limits to binding rates 
Matlab code: Simulating diffusion 
2/16 
Regulatory biology and the constitutive promoter, Part I: Phase diagrams and solving for mean mRNA levels 
Matlab code: Dynamics of the constitutive promoter The constitutive promoter: PowerPoint slides 
2/21 
Regulatory biology and the constitutive promoter, Part II: Master equations and transcriptional noise, a numerical approach 
Homework 3 due 
2/23 
Regulatory biology and the constitutive promoter, Part III: Master equations and transcriptional noise, an analytical approach Presentation of first estimate (1/4 of the class) 
Homework 4 out, due 3/2: Taniguchi2010 Solving the master equation for the constitutive promoter: Matlab code Clarke1946: Flyingbomb attacks on London and the Poisson distribution 
2/28 
Presentation of first estimate (1/2 of the class) 

3/2 
Presentation of first estimate (1/4 of the class) Regulatory biology: Simple repression, Part I 
Homework 4 due 
3/7 
Regulatory biology: Simple repression, Part II 
Homework 5 out, due 3/14: Voltagegated ion channel data and paper (Keller1986), A First Exposure to Statistical Mechanics for Life Scientists (Garcia2007b). 
3/9 
Regulatory biology: Simple repression, Part III 
Measuring gene expression in bacteria: Theoretical prediction, Sample data set, Full data set, First version of image analysis code, Final version of image analysis code Simple repression: Powerpoint Presentation 
3/14 
Image analysis and discussion with Simon 
Homework 5 due, Homework 5 solutions 
3/16 
Binding problems in biology: Cooperativity, the MWC model, and ion channels 
Homework 6 out, due 3/23: Garcia2011c PBoC problem 4.1 and table 4.1 Oxygen binding and dimoglobin: Matlab code, Powerpoint Slides RossiFanelli1958, data extracted using DigitizeIt 
3/21 177 LSA 
Developmental patterning: The French Flag model and how to make morphogen gradients 
Install LapseIt on your iPhone, Android phone, or iPad. Bring it, together with a charger, to class. Papers: Testing the French Flag model (Driever1989 and Liu2013); measuring Bicoid degradation (Drocco2011), diffusion (AbuArish2011), bicoid localization (Little2011), and translation (Petkova2014) 
3/23 
Developmental patterning: Testing the French Flag model 
Homework 6 due, Homework 6 solutions Homework 7 out, due 4/6: Gregor2007b data Testing the French Flag model: Snapshots of developing fly embryos, Matlab code 
4/4 
A probabilistic view of biology, Part I: Carboxysome partitioning 
Coin flips and carboxysomes: Matlab code, Powerpoint slides 
4/6 
A probabilistic view of biology, Part II: Carboxysome partitioning and using fluctuations to count molecules 
Homework 7 due, Homework 7 solutions 
4/11 
Evolution by the numbers, Part I: Genetic drift and the random forces that drive evolution 
Genetic drift: Buri1956, Matlab code, Powerpoint slides Homework 8 out, due 4/25: Rosenfeld2005, Buri data 
4/13 
Evolution by the numbers, Part II: Genetic drift and the random forces that drive evolution 
The WrightFisher model of genetic drift: Matlab code 
4/18 
Presentation of second estimate (first half of the class) 
Bring a smartphone or computer to fill out the offical course survey as well as Hernan's survey 
4/20 
Presentation of second estimate (second half of the class) 

4/25 
A dynamical view of biology: Genetic switches 
Homework 8 due, Homework 8 solutions Homework 9 out, due 5/8 at 10am in 505 LSA: Eden2011 (SI), Abouchar2014 (SI), GarciaBellido1979. Note that this homework is optional and only for extra credit. It is longer and harder than usual, and will be worth 200% of a regular homework. If you do it, will only take it into account if it improves your grade. Genetic switches: Gardner2000, Laslo2006, Matlab code, Powerpoint slides 
4/27 
Biological specificity: Kinetic proofreading 
Gunawardena2014: Models in biology: `accurate descriptions of our pathetic thinking' 
Matlab tutorials: We will assume no previous Matlab experience. These are small tutorials that introduce the different concepts we'll use in each class.
 Variable and arrays, and plotting.
 Forloops.
 Loading and displaying images (sample image).
 Ifstatements.
If you want to go beyond our introductory Matlab tutorials, here are some other great sources:
Bibliography:
 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). StreetFighting 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.