Difference between revisions of "BCH391L 2015"

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(Lectures & Handouts)
(Lectures & Handouts)
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* [http://www.marcottelab.org/users/BCH391L_2015/BCH364C-391L_Classifiers_Spring2015.pdf Today's slides]
 
* [http://www.marcottelab.org/users/BCH391L_2015/BCH364C-391L_Classifiers_Spring2015.pdf Today's slides]
 
* [http://www.marcottelab.org/users/BCH391L_2015/AMLALLclassification.pdf Classifying leukemias]
 
* [http://www.marcottelab.org/users/BCH391L_2015/AMLALLclassification.pdf Classifying leukemias]
 
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'''Apr 7, 2015 - Clustering II
 
'''Apr 7, 2015 - Clustering II
 
* We're finishing up the slides from Mar. 31.<br>
 
* We're finishing up the slides from Mar. 31.<br>
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* [http://www.marcottelab.org/users/BCH391L_2015/SOM-geneexpression.pdf SOM gene expression]
 
* [http://www.marcottelab.org/users/BCH391L_2015/SOM-geneexpression.pdf SOM gene expression]
 
** Links to various applications of SOMs: [http://en.wikipedia.org/wiki/Self-organizing_map 1], [http://www.bentley.edu/centers/sites/www.bentley.edu.centers/files/csbigs/hua.pdf 2], [http://vizier.u-strasbg.fr/kohonen.htx 3], [http://wn.com/Self_Organizing_Maps_Application 4]. You can run SOMs on the [http://www.math.le.ac.uk/people/ag153/homepage/PCA_SOM/PCA_SOM.html following web site]. You can also run SOM clustering with the Open Source Clustering package (an alternative to Eisen's Cluster) with '-s' option, or GUI option. See http://bonsai.hgc.jp/~mdehoon/software/cluster/manual/SOM.html#SOM for detail. (FYI, it also supports PCA). If you are not happy with Cluster's SOM function, the statistical package R also provides a package for calculating SOMs (http://cran.r-project.org/web/packages/som/index.html).  
 
** Links to various applications of SOMs: [http://en.wikipedia.org/wiki/Self-organizing_map 1], [http://www.bentley.edu/centers/sites/www.bentley.edu.centers/files/csbigs/hua.pdf 2], [http://vizier.u-strasbg.fr/kohonen.htx 3], [http://wn.com/Self_Organizing_Maps_Application 4]. You can run SOMs on the [http://www.math.le.ac.uk/people/ag153/homepage/PCA_SOM/PCA_SOM.html following web site]. You can also run SOM clustering with the Open Source Clustering package (an alternative to Eisen's Cluster) with '-s' option, or GUI option. See http://bonsai.hgc.jp/~mdehoon/software/cluster/manual/SOM.html#SOM for detail. (FYI, it also supports PCA). If you are not happy with Cluster's SOM function, the statistical package R also provides a package for calculating SOMs (http://cran.r-project.org/web/packages/som/index.html).  
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'''Apr 2, 2015 - Functional Genomics & Data Mining - Clustering I'''
 
'''Apr 2, 2015 - Functional Genomics & Data Mining - Clustering I'''
 
* [http://www.marcottelab.org/users/BCH391L_2015/BCH364C-391L_LargeScaleExperiments_Spring2015.pdf Today's slides]
 
* [http://www.marcottelab.org/users/BCH391L_2015/BCH364C-391L_LargeScaleExperiments_Spring2015.pdf Today's slides]

Revision as of 09:10, 7 April 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

Apr 7, 2015 - Clustering II

Apr 2, 2015 - Functional Genomics & Data Mining - Clustering I

Problem Set 3, due before midnight Apr. 14, 2015. You will need the following software and datasets:

Mar 31, 2015 - Motifs

Mar 26, 2015 - Mapping protein complexes

Mar 24, 2015 - Mass spectrometry proteomics

  • Welcome back from Spring Break. Apparently, we had some down time on Rosalind, so I'm extending the HW3 deadline to 11:59PM March 26...
  • Guest speaker: Dr. Daniel Boutz

Mar 17-19, 2015 - SPRING BREAK

Mar 12, 2015 - Genomes II, Gene Expression

Mar 10, 2015 - Genome Assembly

Mar 5, 2015 - *** ICE STORM 2015***, UT classes cancelled

Mar 3, 2015 - Gene finding II

  • We're finishing up the slides from Feb. 26, then moving on into Genome Assembly
  • Due March 12 by email - One to two (full) paragraphs describing your plans for a final project, along with the names of your collaborators. This assignment will account for 5 points out of your 25 total points for your course project.
  • Here are a few examples of final projects from previous years: 1, 2, 3, 4, 5 6 7 8 9 10 11 12 13 14
  • Office hours tomorrow overlap a seminar (MBB 1.210, 4-5PM) from Prof. Wah Chiu of the Baylor College of Medicine, "Visualizing Viruses Inside and Outside the Cells". The talk will be better, so I propose office hours be skipped in favor of the talk. Here are a few snippets from Prof. Chiu's research to whet your appetite: Infected cyanobacteria, Lemon-shaped viruses, drug efflux pumps, and building "3D cellular context"

Feb 26, 2015 - Gene finding

Reading:

Feb 24, 2015 - HMMs II

  • News of the day: Mammoths!
  • We're finishing up the slides from Feb. 19.

Problem Set 2, due before midnight Mar. 10, 2015:

Feb 19, 2015 - Hidden Markov Models

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

Reading:

Feb 17, 2015 - Next-generation Sequencing (NGS)

Feb 12, 2015 - 3D Protein Structure Modeling

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.