About
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 bootcamp will explore the description of a broad array of topics from modern biology using the language of physics, mathematics and computation. 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.
Quantitative 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.
Note that no previous coding or advanced math skills are required. The course is designed with the objective of being widely accessible. Further, interested students will have the opportunity to participate in evening experimental rotations in several labs aimed at learning how experiments to obtain the type of quantitative data that our models will be talking to are implemented and executed.
The syllabus for the course can be found here.
When and where
Lecture: Wednesday 8/12/26 through Thursday 8/20/26, 9:00am–4:30pm, IGI Conference Room. Note that there will be no bootcamp on 8/19/26 and Saturday/Sunday 8/15 and 8/16.
Quantitative courses at Berkeley
A list of computational and quantitative biology courses at Berkeley can be found here.
People
Instructors:
Hernan Garcia
(MCB/ Physics)
Priya Moorjani
(MCB/ Computational Biology)
Graduate Student Instructors:
Vinu Harihar
(Biophysics)
Jianjie Xu
(Physics)
Course structure
A typical day in the bootcamp looks like this:
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9:00am–12:00pm: Lectures, hands-on activities and copious amounts of coffee.
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12:00pm–12:30pm: Lunch (provided).
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12:30pm–1:30pm: Research talk from Berkeley faculty members on their research in quantitative biology. We aim for these talks to be of high pedagogical value, so interruptions and questions are encouraged!
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1:30pm–2:00pm: Breakout session between the students and the speaker. These sessions are perfect venues to ask follow up questions about the talk, but to also learn about the speaker’s career path.
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2:00pm–4:00pm: More lectures, hands-on activities and coffee.
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4:00pm–4:30pm: Study hall to work on final project.
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5:00pm: Optional experimental rotations (see more below).
Speakers
| Number | Date | Speaker | Title |
|---|---|---|---|
| 1 | 8/12 |
Ahmet Yildiz |
TBD |
| 2 | 8/13 |
Aaron Streets |
TBD |
| 3 | 8/14 |
Dan Fletcher |
TBD |
| 4 | 8/17 |
Ian Swinburne |
TBD |
| 5 | 8/18 |
Priya Moorjani |
TBD |
| 6 | 8/20 |
Holger Muller |
TBD |
Experimental Rotations
Sign up for experimental rotations here (signups are now closed, contact Yovan or Aaron if you need to make any changes). Please sign up only for dates and times you can attend.
| Number | Lab (instructor) | # days and dates available | Project(s) description |
|---|---|---|---|
| 1 | Garcia Lab (Aaron Fultineer) | 8/12 and 8/13 | Building a cellular identity, one morphogen at a time |
| 2 | Garcia Lab (Kaden Tro) | 8/17 or 8/18 | Single-molecule measurement of live transcription in the fly embryo |
| 3 | Yildiz Lab (Joseph Slivka and Leo Li) | 8/12 and 8/20 | Watching kinesin step in real time using fluorescence imaging with one nanometer accuracy. |
| 4 | Bustamante Lab (Francesca) | 8/18 | Tracking Transcription-Coupled Nuclear Factors Binding Using Single-Molecule Optical Tweezers and Confocal Microscopy |
| 5 | Bustamante Lab (Jason) | 8/20 | Following individual transcription trajectories by Pol II across the nucleosome |
| 6 | Bustamante Lab (Daniel) | 8/17 | Following the unfolding and refolding reactions of a small protein with single molecule resolution. |
| 7 | Fletcher Lab (Smiti and Elaine) | 8/15 | "Now you see it, now you don't! Hands-on visualization of how light diffracts and interferes inside a microscope |
| 8 | Swinburne Lab (Maria) | 8/14 | Live imaging while "poking" fluid-filled organs in zebrafish embryos with magnetic droplets |
| 9 | Hallatschek Lab (Aditya) | 8/12 or 8/13 | Evolution in Spatially Structured Populations |
Syllabus
The full syllabus for the course can be found here
| Number | Date | Topics | Slides | Python Code | Suggested Readings | Notes and Videos | Extra Problems | ||
|---|---|---|---|---|---|---|---|---|---|
| 1 | Wed, 8/12 |
Bootcamp Introduction + Order of Magnitude Biology
Stuff(t): The Protocol of Biological Dynamics, Part I
Speaker: Ahmet Yildiz |
A Feeling for the Numbers in Biology: Your Turn |
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| 2 | Thu, 8/13 |
Stuff(t): The Protocol of Biological Dynamics, Part II
Diffusion as Biology’s Null Hypothesis for Dynamics, Part I
Speaker: Aaron Streets |
Stuff(t), Part II: Diffusion, Part I: |
Stuff(t), Part II: Diffusion, Part I: |
Stuff(t), Part II:
Diffusion, Part I:
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Stuff(t), Part II:
Diffusion, Part I: |
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| 3 | Fri, 8/14 |
Diffusion as Biology’s Null Hypothesis for Dynamics, Part II
Quantifying Prejudice — The Great Probability Distributions of Biology
Speaker: Dan Fletcher |
Diffusion, Part II: Probability Distributions: |
Probability Distributions: |
Diffusion, Part II:
Probability Distributions:
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Diffusion, Part II: Probability Distributions: |
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| 4 | Mon, 8/17 |
Theory in Biology: Insights from Population Genetics
Speaker: Ian Swinburne Vectors and Representations, Part I
Speaker: Ian Swinburne |
Theory in Biology: Vectors and Representations, Part I: |
Theory in Biology: |
Theory in Biology:
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| 5 | Tue, 8/18 |
Uncertainty in Biology: Quantifying and Making Inferences amidst errors
Speaker: Priya Moorjani |
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| 6 | Thu, 8/20 |
Vectors and Representations, Part II
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