Difference between revisions of "BCH391L 2015"

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* Guest speaker: [http://bonneaulab.bio.nyu.edu/people.html#kevin Dr. Kevin Drew]
 
* Guest speaker: [http://bonneaulab.bio.nyu.edu/people.html#kevin Dr. Kevin Drew]
 
* The [https://www.rosettacommons.org/software Rosetta] software suite for 3D protein modeling, and [http://www.marcottelab.org/users/BCH391L_2015/RosettaOverview.pdf what it can do for you]
 
* The [https://www.rosettacommons.org/software Rosetta] software suite for 3D protein modeling, and [http://www.marcottelab.org/users/BCH391L_2015/RosettaOverview.pdf what it can do for you]
 
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'''Feb 10, 2015 - Biological databases'''
 
'''Feb 10, 2015 - Biological databases'''
 
* Homework #2 (worth 10% of your final course grade) has been assigned on Rosalind and is '''due by 11:59PM February 19'''.
 
* Homework #2 (worth 10% of your final course grade) has been assigned on Rosalind and is '''due by 11:59PM February 19'''.
 
* Just a note that we'll be seeing ever more statistics as go on. Here's a [http://www.marcottelab.org/users/BCH391L_2015/StatisticsPrimer.pdf good primer] from [http://www.bio.utexas.edu/research/meyers/LaurenM/index.html Prof. Lauren Myers] to refresh/explain basic concepts.
 
* Just a note that we'll be seeing ever more statistics as go on. Here's a [http://www.marcottelab.org/users/BCH391L_2015/StatisticsPrimer.pdf good primer] from [http://www.bio.utexas.edu/research/meyers/LaurenM/index.html Prof. Lauren Myers] to refresh/explain basic concepts.
 
* [http://www.marcottelab.org/users/BCH391L_2015/BCH364C-391L-BiologicalDatabases-Spring2015.pdf Today's slides]<br>
 
* [http://www.marcottelab.org/users/BCH391L_2015/BCH364C-391L-BiologicalDatabases-Spring2015.pdf Today's slides]<br>
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'''Feb 5, 2015 - Guest lecture: Intro to Appsoma'''   
 
'''Feb 5, 2015 - Guest lecture: Intro to Appsoma'''   
 
* We'll have a guest lecture by [http://www.mine-control.com/zack/ Zack Simpson], a Fellow of the [http://web.cssb.utexas.edu/ UT Center for Systems and Synthetic Biology]. For the curious, ''Science'' magazine wrote a nice feature on Zack several years ago ([http://www.marcottelab.org/users/BCH391L_2015/Science_Zack.pdf posted here]).  Zack co-founded the bioinformatics startup company [http://www.traitwise.com/ Traitwise] (full disclosure: I'm on their scientific advisory board) and is the lead developer of [https://appsoma.com/home Appsoma], a web-based scientific cloud computing platform that has a number of enhancements (and dedicated computer clusters) specifically for UT students.
 
* We'll have a guest lecture by [http://www.mine-control.com/zack/ Zack Simpson], a Fellow of the [http://web.cssb.utexas.edu/ UT Center for Systems and Synthetic Biology]. For the curious, ''Science'' magazine wrote a nice feature on Zack several years ago ([http://www.marcottelab.org/users/BCH391L_2015/Science_Zack.pdf posted here]).  Zack co-founded the bioinformatics startup company [http://www.traitwise.com/ Traitwise] (full disclosure: I'm on their scientific advisory board) and is the lead developer of [https://appsoma.com/home Appsoma], a web-based scientific cloud computing platform that has a number of enhancements (and dedicated computer clusters) specifically for UT students.

Revision as of 17:43, 9 February 2015

BCH364C/391L Systems Biology/Bioinformatics

Course unique #: 54995/55095
Lectures: Tues/Thurs 11 – 12:30 PM in BUR 212
Instructor: Edward Marcotte, marcotte@icmb.utexas.edu

  • Office hours: Wed 4 PM – 5 PM in MBB 3.148BA

TA: Joe Taft, taft@utexas.edu

  • NOTE THE CHANGE IN OFFICE HOUR TIMES & LOCATIONS
  • TA Office hours: Mon/Fri 10 AM - 11 AM in MBB 2.456/3.204 Phone: listed on the syllabus

Lectures & Handouts

Feb 10, 2015 - Biological databases

  • Homework #2 (worth 10% of your final course grade) has been assigned on Rosalind and is due by 11:59PM February 19.
  • 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

Feb 5, 2015 - 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.

Feb 3, 2015 - BLAST

Jan 29, 2015 - Sequence Alignment II

Jan 27, 2015 - Sequence Alignment I

Problem Set I, due before midnight Feb. 5, 2015:

Reading:

Jan 22, 2015 - Intro to Python

Jan 20, 2015 - 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 BCH364C/391L 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.
  • 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 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.


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

The final project is due by midnight May 4, 2015.