Time: TuTh 9:30-10:45 AM (via Zoom)
Interested in the course, but unsure about registering? If you are interested in the course but not yet registered (and perhaps just wish to audit), please email me (firstname.lastname@example.org). I'll send you a zoom invitation (which requires registration).
Teaching Assistant: Vladimir Smirnov (email@example.com)
Vlad's Office hours: Monday and Thurdays 4-5 PM.
Tandy's office hours: Fridays 4-5 PM.
See this link for zoom info for office hours.
Course description: This is a course on applied algorithms, focusing on the use of discrete mathematics, graph theory, probability theory, statistics, machine learning, and simulations, to design and analyze algorithms for phylogeny (evolutionary tree) estimation, multiple sequence alignment, genome-scale phylogenetics, genome assembly and annotation, and metagenomics. Each of these biological problems is important and unsolved, so that new methods are needed. Every year, at least one student in the course has done a project that was subsequently published in scientific conferences and journals; you can be one of these students!
Additional Syllabus statements The College of Engineering has recommended several extra statements, which I agree with, and hence include here.
Pre-requisites CS 374 and CS 361/STAT 361, or consent of the instructor; no biology background is required. If you did not take these pre-requisites at UIUC but have equivalent coursework in algorithms and probability/statistics, you will probably do fine. If you are a biologist without this background but you are working on problems where phylogeny estimation or multiple sequence alignment are important, you may be able to take the course as well with some extra work. Please see me if you have any questions about whether the course is suitable for you!
Who should take this class: The course is designed for graduate students in CS, ECE, Math, and Statistics; no background in biology is required.
Paper presentations Please see this page for information on the paper presentations, schedule, list of papers, and associated homework assignments.
The course requires a final project of each student,
and is due on the last day the class meets.
You are strongly encouraged to do a research project, but you
can also do a survey paper on some topic relevant to the course material.
In both cases, your project should be a paper (single spaced, 1" margins,
of 8-15 pages not counting the title page or bibliography)
in a format and style appropriate for submission to a journal.
Research projects can involve two students, but
survey papers must be done by yourself.
Grades on the final project depend upon the kind of project you do.
For a research paper, your grade will be 30% writing, 40% scientific/algorithmic rigor, and 30% impact. If you do a survey paper, the grade will be 30% writing, 30% summary of the literature you discuss, and 40% commentary (i.e., insight, critical and thoughtful discussion of the issues that come up).
Note also the requirements for reproducibility (for research papers)
and the expectations about writing quality.
Please see this page for a list of possible research projects for this course.
Course Textbook: Computational Phylogenetics: An introduction to designing methods for phylogeny estimation, published by Cambridge University Press. Errata are posted as I find them. You can get the hardcopy at the university bookstore (it is supposed to be there) or on Amazon. You can also get the E-book at Google Play. The image of the Monterey Cypress is there because of the NSF-funded CIPRES project, whose purpose was to develop the methods and computational infrastructure to improve large-scale phylogeny estimation.
This will be a fully online course, without any requirement for anyone to be here in person. Despite this, I plan to be very available (by Zoom) to meet with students individually as well as through group meetings. All classes will be synchronous.
Paper presentations Please see this page.
Guidance on writing assignments.
Many of the activities in this course involve writing,
and this is particularly true for the final project
if you do any kind of survey of the literature.
It's very important that you familiarize yourself
with expectations about scholarly writing, and in particular
with how to avoid plagiarizing.
Please see the information in the Academic Integrity page
and specifically note the instructions about plagiarism and how
paraphrasing improperly can count as plagiarism.
In addition, please see my write-up with
guidelines for reviewing computational papers.