BIO337 2014

BIO337 Systems Biology/Bioinformatics

Course unique #: 50524
Lectures: Tues/Thurs 11 – 12:30 PM in BUR 212
Instructor: Edward Marcotte, marcotte@icmb.utexas.edu

• Office hours: Wed 11 AM – 12 noon in MBB 3.148BA
  

TA: Dakota Derryberry, dakotaz@utexas.edu

• TA Office hours: Mon 4 - 5 PM/Fri 9 – 10 AM in MBB 3.304 Phone: 512-232-2459
  

Lectures & Handouts

Feb 13, 2014 - Next-generation Sequencing (NGS)

• Guest speaker: Dr. Vishy Iyer
• Today's slides

Feb 13, 2014 - HMMs II

• We're finishing up the slides from Feb. 11. Note that I added a few new slides to the end of the deck for today's lecture.
• There's a nice systems biology/bioinformatics research talk today by Steve Horvath (UCLA), Epigenetic clock, genomic biomarkers, and systems biology (2-3PM, NHB 1.720). Read more about the clock.

Feb 11, 2014 - Hidden Markov Models

• re: our discussion of databases, the remarkable growth of data, e.g. UniProt
• Today's slides
  

Problem Set 2, due before midnight Feb. 23, 2014:

• Problem Set 2.
• You'll need these 3 files: State sequences, Soluble sequences, Transmembrane sequences

Reading:

• HMM primer and Bayesian statistics primer, Wiki Bayes, and a simple example
• Care to practice your regular expressions? (In python?)

Feb 6, 2014 - Biological databases

• Just a note that we'll be seeing ever more statistics as go on. Here's a good primer from Prof. Lauren Myers to refresh/explain basic concepts.
• Today's slides
  
• The EteRNA paper and the news article about it

Feb 4, 2014 - Guest lecture: Intro to Appsoma

• We'll have a guest lecture by Zack Simpson, a Fellow of the UT Center for Systems and Synthetic Biology. For the curious, Science magazine wrote a nice feature on Zack several years ago (posted here). Zack co-founded the bioinformatics startup company Traitwise (full disclosure: I'm on their scientific advisory board) and is the lead developer of Appsoma, a web-based scientific cloud computing platform that has a number of enhancements (and dedicated computer clusters) specifically for UT students.

Jan 30, 2014 - BLAST

• Homework #2 (worth 10% of your final course grade) has been assigned on Rosalind and is due by 11:59PM February 9.
• Our slides today are modified from a paper on Teaching BLAST by Cheryl Kerfeld & Kathleen Scott.
• The original BLAST paper
• The protein homology graph paper. Just for fun, here's a link to a stylized version we exhibited in the engaging Design and the Elastic Mind show at New York's Museum of Modern Art.
• Repeats in the human genome, tallied here

Jan 28, 2014 - ICEPOCALYPSE 2014!!!

Jan 23, 2014 - Sequence Alignment II

• We're finishing up the slides from Jan. 21.
• Dynamic programming primer
• An example of dynamic programming using Excel, created by Michael Hoffman (a former UT undergraduate who took the prior incarnation of this class)
• A few examples of proteins with internally repetitive sequences: 1, 2, 3

Jan 21, 2014 - Sequence Alignment I

• News of the day: China cloning on an 'industrial scale'. Favorite quote: "If it tastes good you should sequence it..." BGI is one of the biggest (the biggest?) genome sequencing centers in the world and employs >1,000 bioinformatics researchers.
• Today's slides
  

Problem Set I, due before midnight Jan. 28, 2014:

• Problem Set 1
• T. volcanium genome
• 3 mystery genes (for Problem 5): Mgene1, Mgene2, Mgene3
  

Reading:

• BLOSUM primer
• The original BLOSUM paper (hot off the presses from 1992!)
• BLOSUM miscalculations improve performance

Jan 16, 2014 - Intro to Python

• Today's slides
  
• Python primer
• E. coli genome

Jan 14, 2014 - Introduction

• Today's slides
  
• Some warm-up videos to get you started on Python: Code Academy's Python coding for beginners
  
• We'll be conducting homework using the online environment Rosalind. Go ahead and register on the site, and enroll specifically for BIO337 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 21.
• 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 before, definitely check this out!!!
  
• An oldie (by recent bioinformatics standards) but goodie: Computers are from Mars, Organisms are from Venus

Syllabus & course outline

Course syllabus

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 upper division undergraduates in natural sciences and engineering.
Prerequisites: Biochem I or equivalent (e.g. CH339J or CH339K/L), basic familiarity with molecular biology.

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),

For biologists rusty on their stats, The Cartoon Guide to Statistics (Gonick/Smith) is very good. A reasonable online resource for beginners is Statistics Done Wrong.

Some online references:
An online bioinformatics course
Assorted bioinformatics resources on the web: Assorted links
Beginning Python for Bioinformatics
Online probability texts: #1, #2, #3

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 a course project (25% of final grade), which will be collaborative. Cross-discipline collaborations will be encouraged. The course project will consist of a research project on a bioinformatics topic chosen by the students (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.

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 percentage points 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, and written solutions should be performed independently (except the final collaborative project).

The final project is due by midnight April 28, 2014.

• How to make a web site for the final project
  • Google Site: http://www.google.com/sites/help/intl/en/overview.html

• Why we don't teach C++