BCH394P BCH364C 2021
BCH394P/BCH364C Systems Biology & Bioinformatics
Course unique #: 55680/55580
Lectures: Tues/Thurs 11 – 12:30 PM on Zoom (log in to Canvas for the link)
Instructor: Edward Marcotte, marcotte @ utexas.edu
- Office hours: Fri 11 AM – 12 noon on Zoom
TA: Vy Dang, vyqtdang @ utexas.edu
- TA Office hours: Mon 3-4/Wed 1-2 on Zoom
Class Slack channel: bch394pbch364c2021.slack.com
Lectures & Handouts
Jan 19, 2021 - Introduction
- Today's slides
- We'll be conducting homework using the online environment Rosalind. Go ahead and register on the site, and enroll specifically for BCH394P/364C (Spring 2021) Systems Biology/Bioinformatics using this link. Homework #1 (worth 10% of your final course grade) has already been assigned on Rosalind and is due by 11:59PM January 27.
- Here's a very nice online Python resource, worth checking out!
- Some warm-up videos to get you started on Python (2 not 3, unless you pay for an upgrade): Code Academy's Python coding for beginners
- Khan Academy has archived their videos on Python here
- A useful online resource if you get bogged down: Python for Biologists. (& just a heads-up that some of their instructions for running code relate to a command line environment that's a bit different from the default one you install following the Rosalind instructions. It won't affect the programs, just the way they are run or how you specific where files are located.) However, if you've never programmed Python before, this also worth checking out.
Syllabus & course outline
An introduction to systems biology and bioinformatics, emphasizing quantitative analysis of high-throughput biological data, and covering typical data, data analysis, and computer algorithms. Topics will include introductory probability and statistics, basics of Python programming, protein and nucleic acid sequence analysis, genome sequencing and assembly, proteomics, synthetic biology, analysis of large-scale gene expression data, data clustering, biological pattern recognition, and gene and protein networks.
Open to graduate students and upper division undergrads (with permission) in natural sciences and engineering.
Prerequisites: Basic familiarity with molecular biology, statistics & computing, but realistically, it is expected that students will have extremely varied backgrounds. Undergraduates have additional prerequisites, as listed in the catalog.
Note that this is not a course on practical sequence analysis or using web-based tools. Although we will use a number of these to help illustrate points, the focus of the course will be on learning the underlying algorithms and exploratory data analyses and their applications, esp. in high-throughput biology.
Most of the lectures will be from research articles and slides posted online, with some material from the...
Optional text (for sequence analysis): Biological sequence analysis, by R. Durbin, S. Eddy, A. Krogh, G. Mitchison (Cambridge University Press),
No exams will be given. Grades will be based on online homework (counting 30% of the grade), 3 problem sets (given every 2-3 weeks and counting 15% each towards the final grade) and an independent course project (25% of final grade). The course project will consist of a research project on a bioinformatics topic chosen by the student (with approval by the instructor) containing an element of independent computational biology research (e.g. calculation, programming, database analysis, etc.). This will be turned in as a link to a web page. The final project is due by midnight, April 26, 2021. The last 3 classes will be spent presenting your projects to each other. (The presentation will account for 5/25 points for the project.)
In this semester of coronavirus lockdown, the entire class will be web-based. We will hold lectures by Zoom during the normally scheduled class time. Log in to the UT Canvas class page for the link, or, if you are auditing, email the TA and we will send the link by return email. Slides will be posted before class so you can follow along with the material. We'll record the lectures & post the recordings afterward on Canvas so any of you who might be in other timezones or otherwise be unable to make class will have the opportunity to watch them. Note that the recordings will only be available on Canvas and are reserved only for students in this class for educational purposes and are protected under FERPA. The recordings should not be shared outside the class in any form. Violation of this restriction by a student could lead to Student Misconduct proceedings.
Online homework will be assigned and evaluated using the free bioinformatics web resource Rosalind.
All projects and homework will be turned in electronically and time-stamped. No makeup work will be given. Instead, all students have 5 days of free “late time” (for the entire semester, NOT per project, and counting weekends/holidays). For projects turned in late, days will be deducted from the 5 day total (or what remains of it) by the number of days late (in 1 day increments, rounding up, i.e. 10 minutes late = 1 day deducted). Once the full 5 days have been used up, assignments will be penalized 10 percent per day late (rounding up), i.e., a 50 point assignment turned in 1.5 days late would be penalized 20%, or 10 points.
Homework, problem sets, and the project total to a possible 100 points. There will be no curving of grades, nor will grades be rounded up. We’ll use the plus/minus grading system, so: A= 92 and above, A-=90 to 91.99, etc. Just for clarity's sake, here are the cutoffs for the grades: 92% = A, 90% = A- < 92%, 88% = B+ < 90%, 82% = B < 88%, 80% = B- < 82%, 78% = C+ < 80%, 72% = C < 78%, 70% = C- < 72%, 68% = D+ < 70%, 62% = D < 68%, 60% = D- < 62%, F < 60%.
Students are welcome to discuss ideas and problems with each other, but all programs, Rosalind homework, problem sets, and written solutions should be performed independently . Students are expected to follow the UT honor code. Cheating, plagiarism, copying, & reuse of prior homework, projects, or programs from CourseHero, Github, or any other sources are all strictly forbidden and constitute breaches of academic integrity (UT academic integrity policy and Sec. 11–402. Academic Dishonesty) and cause for dismissal with a failing grade. In particular, any materials found online (e.g. in CourseHero) that are associated with you, or any suspected unauthorized sharing of materials, will be reported to Student Conduct and Academic Integrity in the Office of the Dean of Students. These reports can result in sanctions, including failure in the course.
The final project web site is due by midnight April 26, 2021.
- How to make a web site for the final project
- Google Site: https://support.google.com/sites/answer/153197?hl=en