CS279: Structure and Organization of Biomolecules and Cells
Course Information
Description:
This course will focus on computational techniques used to study the structure and dynamics of
biomolecules, cells, and everything in between. For example, what is the structure of proteins, DNA,
and RNA? How do their motions contribute to their function? How do they bind to other molecules?
How are molecules distributed and compartmentalized within a cell, and how do they move around?
How might one modify the behavior of these systems using drugs or other therapeutics? How can structural information and associated computational methods contribute to the design of drugs, vaccines, proteins, or other important molecules?
Computation can contribute to addressing such questions in at least two distinct ways. First, computational analysis is required to extract useful information from experimental measurements. Second, one can use computational techniques to predict structures, dynamics, and important biochemical properties.
The course will cover (1) atomic-level molecular modeling methods for proteins and other biomolecules, including structure prediction, molecular dynamics simulation, docking, and protein design, (2) computational methods involved in solving molecular structures by x-ray crystallography and cryo-electron microscopy, and (3) computational methods for studying spatial organization of cells, including computational analysis of optical microscopy images and video, and simulations at the cellular scale. The course will cover both foundational material and cutting-edge research in each of these areas, including recent advances in machine learning for structural biology.
Coursework:
Students will be expected to complete three assignments, each of which will involve a combination of theoretical questions and computer work. Additionally, students will be expected to complete a project. The project will involve about as much work as an assignment, but it will be more open-ended and will allow students to delve into a topic of their choosing in more depth. Finally, students will be expected to complete an exam at the end of the quarter. More details regarding content of the exam will be released toward the second half of the quarter.
Prerequisites:
Elementary programming background (at the level of CS 106A) and introductory course in biology.
Class: Tuesdays and Thursdays, 3:00 PM - 4:20 PM in Shriram 104.
Materials:
There is no required textbook. We will suggest a variety of optional reading material throughout the course.
Live Streams and Recordings:
All lectures will be recorded this year and will be available to enrolled students on Canvas (linked here). After navigating to the CS279 Course Page on Canvas, click on the Panopto Course Videos tab on the left side of the screen. The live lecture will be available to view on Canvas in real-time.
Lectures will also publish under this tab thirty minutes after class ends. We strongly encourage real-time attendance (either in-person or virtually) if possible; please note our participation policy.
All TA-led tutorials will be recorded (attendance is not required) and posted to Canvas (in the Kickstarts and Tutorials folder in the Panopto Course Videos tab).
Instructor: Ron Dror
- Professor Dror's Office Hours: Tues. & Thurs. 4:20 - 4:45 PM, outside Shriram 104 (i.e., right after each class, outside the classroom). If you are participating in lecture remotely, you can join these office hours through the zoom room located at bit.ly/cs279-ron.
A TA will be monitoring this zoom and will be able to add you to a queue so Professor Dror can answer your questions.
Contact and Questions:
Please use Ed Discussion for questions related to assignments, lectures,
and course logistics. If you have issues that cannot be resolved on Ed, please contact us at cs279staff@cs.stanford.edu. For
instructions on how to get set up on Ed, please see the Getting Set Up handout.
TA: Jasper McAvity
TA: Patricia Suriana
TA: Jennifer Xu
TA: Ruhi Sayana
TA: Luci Bresette
TA: Douglas Li
Office Hours:
- Some office hours will be held in-person and others will be held virtually over zoom. The same zoom link will be used for all virtual office hours.
- Queuestatus will be used to manage the queue for both virtual and in-person office hours. Please see the Getting Set Up handout for further instructions on QueueStatus.
- The weekly office hour schedule can be viewed through the Google Calendar below. The in-person office hours will indicate the location and the virtual office hours will show the same zoom link as described above.
Announcements:
All announcements will be made on Ed Discussion. For instructions on how to get set up on Ed, please see the Getting Set Up handout.
Handouts
Lectures
Some topics may be covered a bit earlier or later than listed, due to circumstances beyond the instructor’s control.
- Introduction (Sept. 26)
[slides]
- Biomolecular Structure, including Protein Structure (Sept. 28 and Oct. 3)
[slides]
Optional Reading:
- Michael Levitt's Molecular Architecture Lecture from former course SB228
[slides]
- RNA Structure: Advances and Assessment of 3D Structure Prediction
[Public]
[Stanford Only]
- [optional] Python and Terminal tutorial (Oct. 2, 7-8pm over Zoom)
[slides]
[recording] (available on Canvas)
- [optional] Assignment 1 Kickstart and PyMOL tutorial (Oct. 5, 6-7pm over Zoom)
[PyMOL notes]
[assn1 notes]
[recording] (available on Canvas)
- Energy functions & their relationship to molecular conformation (Oct. 3 and 5)
[slides]
Optional Reading:
- ANI-1: An Extensible Neural Network Potential with DFT Accuracy at Force Field Computational Cost
[Public]
[Stanford Only]
- TorchANI: A Free and Open Source PyTorch-Based Deep Learning Implementation of the ANI Neural Network Potentials
[Public]
[Stanford Only]
- Molecular dynamics simulation (Oct. 10 and 12)
[slides]
Optional Reading:
- Predicting structures of proteins and other biomolecules, including machine learning methods (Oct. 12, 17, and 19)
[slides]
Optional Reading:
- [optional] Assignment 2 Kickstart (Oct. 16, 6-7pm over Zoom)
[kickstart notes]
[recording] (available on Canvas)
- [optional] Assignment 2 FAQ (Oct. 20, 4:30-5pm over Zoom)
[recording] (available on Canvas)
- Protein design (Oct. 24)
[slides]
Optional Reading:
- Fourier transforms and convolution (Oct. 26)
[slides]
Optional Reading:
- Image Analysis (Oct. 31)
[slides]
- Microscopy (Nov. 2)
[slides]
Optional Reading:
- [optional] Assignment 3 Code Tutorial Part 1 (Nov. 3, 6-7pm over Zoom)
[code tutorial notes]
[recording] (available on Canvas)
- Diffusion and cellular-level simulation (Nov. 2 and 9)
[slides]
Optional Reading:
- Random Walks and 1-D Diffusion
[Stanford Only]
(notes from Chris Burge from his class at UCSF)
- Continuum Diffusion Equations
[Stanford Only]
(notes from Chris Burge from his class at UCSF)
- Monte Carlo Methods for Simulating Realistic Synaptic Microphysiology Using MCell
[Stanford Only]
- Colloidal Physics Modeling Reveals How Per-Ribosome Productivity Increases with Growth Rate in Escherichia coli
[Public]
- [optional] Assignment 3 Code Tutorial Part 2 (Nov. 10, 1:30-2:30pm over Zoom)
[code tutorial notes]
[recording] (available on Canvas)
- Project topics (Nov. 9 and 14) [slides]
- Ligand docking and virtual screening (Nov. 14 and 16) [slides]
Optional Reading:
- X-ray crystallography (Nov. 28) [slides]
[notes]
Optional Reading:
- Cryo-electron microscopy (Nov. 30 and Dec. 5)
[slides]
Optional Reading:
- Review (Dec. 5 and Dec. 7)
[slides]
Assignments
Please note that the following dates are approximate.
- Assignment 1 – Biomolecular Structure and Visualization
[handout]
[starter code]
[latex template]
Out: Tuesday, October 3, 2023
Due: Tuesday, October 17, 2023 at 1:00 PM
- Assignment 2 – Atomic-Level Molecular Modeling
[handout]
[starter code]
[latex template]
[challenge question]
Out: Thursday, October 12, 2023
Due: Thursday, October 26, 2023 at 1:00 PM
- Assignment 3 – Cellular Structure and Dynamics
[handout]
[starter code]
[latex template]
[challenge question]
Out: Tuesday, October 31, 2023
Due: Thursday, November 16, 2023 at 1:00 PM
- Project
[Project Instructions]
[Sample Projects from Previous Years (only accessible to enrolled students)]
Out: Tuesday, November 14, 2023
Due: Friday, December 8, 2023 at 11:59 PM
Submission:
All assignments and the project writeup should be submitted to Gradescope. If you are not already added to Gradescope,
see instructions for accessing Gradescope in the Getting Set Up handout.
Exam
The final exam will be on Thursday, December 14, 2023 from 12:15-3:15pm, at Bishop Auditorium (ground floor of Lathrop Library).
Python Resources
In this class, the programming assignments will be in Python. If you have prior experience with Python, great! If you don't, no worries! All we expect is familiarity with basic programming. That said, if you've never worked with Python before, it may be helpful to look at some of the following resources to help you get up to speed.
- This class's "Python and Terminal Tutorial" tutorial will give a brief introduction to Python programming.
- Codecademy is a site that does a good job of introducing the basics of Python, organized by topic. If you're just getting started with Python or if you want to brush up on specific issues, this may be helpful.
- Check out CME 193: Introduction to Scientific Python! It's a 1-unit course that runs for eight weeks. It is recommended for students who want to use Python in math, science, or engineering courses and for students who want to learn the basics of Python programming.
Click here for last year's (Fall 2022) website and content.