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 changes in their shape contribute to their function? How do they bind to one another and 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 folded structures, dynamics, and important biochemical properties.
This field has advanced dramatically in recent years thanks to breakthroughs on multiple fronts, including AI, computing power, and experimental methods.
The course will cover (1) atomic-level molecular modeling methods for proteins and other biomolecules, including structure prediction, molecular dynamics simulation, docking, protein design, and drug discovery, (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 microscopy data, and simulations at the cellular scale. The course will cover both foundational material and cutting-edge research in each of these areas, including dramatic recent advances in AI (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 Packard 101.
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 expect real-time attendance (either in-person or virtually) from students who are able to do so; 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
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 cs279-aut2627-staff@lists.stanford.edu. For
instructions on how to get set up on Ed, please see the Getting Set Up handout.
TA: Aditri Patil
TA: Artemis Xu
TA: Ayush Pandit
TA: Chiho Im
TA: Jay Shenoy
Office Hours:
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.
Please note that the following dates are approximate. When an assignment is released, the PDF and starter code will be available to download here. An optional LaTeX template will also be provided specifically for students who wish to typeset their solutions in LaTeX, but you are not expected or required to do so.
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.