Difference between revisions of "BCH339N 2016"
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'''Apr 12, 2016 - Mass spectrometry proteomics''' | '''Apr 12, 2016 - Mass spectrometry proteomics''' | ||
* Guest speaker: [http://www.researchgate.net/profile/Daniel_Boutz/ Dr. Daniel Boutz] | * Guest speaker: [http://www.researchgate.net/profile/Daniel_Boutz/ Dr. Daniel Boutz] | ||
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'''Apr 7, 2016 - Networks''' | '''Apr 7, 2016 - Networks''' | ||
* Go ahead and start mini-assignment 3, and try to finish it within a week. | * Go ahead and start mini-assignment 3, and try to finish it within a week. | ||
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* [http://www.marcottelab.org/paper-pdfs/JProteomics_GBAReview_2010.pdf Review of predicting gene function and phenotype from protein networks] | * [http://www.marcottelab.org/paper-pdfs/JProteomics_GBAReview_2010.pdf Review of predicting gene function and phenotype from protein networks] | ||
* [http://www.marcottelab.org/users/BCH339N_2016/NBTPrimer-NetworkVisualization.pdf Primer on visualizing networks] | * [http://www.marcottelab.org/users/BCH339N_2016/NBTPrimer-NetworkVisualization.pdf Primer on visualizing networks] | ||
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'''Apr 5, 2016 - Principal Component Analysis (& the curious case of European genotypes)''' | '''Apr 5, 2016 - Principal Component Analysis (& the curious case of European genotypes)''' | ||
* [http://www.marcottelab.org/users/BCH339N_2016/BCH339N_PCA_Spring2016.pdf Today's slides] | * [http://www.marcottelab.org/users/BCH339N_2016/BCH339N_PCA_Spring2016.pdf Today's slides] |
Revision as of 10:27, 7 April 2016
BCH339N Systems Biology & Bioinformatics
Course unique #: 54040
Lectures: Tues/Thurs 11 – 12:30 PM in BUR 212
Instructor: Edward Marcotte, marcotte @ icmb.utexas.edu
- Office hours: Mon 4 PM – 5 PM in MBB 3.148BA
TA: Claire McWhite, claire.mcwhite @ utexas.edu
- TA Office hours: Wed/Thurs 3 PM - 4 PM in MBB 3.128A Phone: on syllabus
Lectures & Handouts
Apr 7, 2016 - Networks
- Go ahead and start mini-assignment 3, and try to finish it within a week.
- Today's slides
- Metabolic networks: The wall chart (it's interactive, e.g. here's enolase), the current state of the human metabolic reaction network, and older but still relevant review of transcriptional networks (with the current record holder in this regard held by ENCODE), and an early review of protein interaction extent and quality whose lessons still hold.
- Useful gene network resources include:
- FunctionalNet, which links to human, worm, Arabidopsis, mouse and yeast gene networks. Not the prettiest web site, but useful, and helped my own group find genes for a wide variety of biological processes. Try searching HumanNet for the myelin regulatory factor MYRF (Entrez gene ID 745) and predicting its function, which is now known but wasn't when the network was made.
- STRING is available for many organisms, including large numbers of prokaryotes. Try searching on the E. coli enolase (Eno) as an example.
- GeneMania, which aggregates many individual gene networks.
- MouseFunc, a collection of network and classifier-based predictions of gene function from an open contest to predict gene function in the mouse.
- The best interactive tool for network visualization is Cytoscape. You can download and install it locally on your computer, then visualize and annotated any gene network, such as are output by the network tools linked above. There is also a web-based network viewer that can be incorporated into your own pages (e.g., as used in YeastNet).
Reading:
- Functional networks
- Review of predicting gene function and phenotype from protein networks
- Primer on visualizing networks
Apr 5, 2016 - Principal Component Analysis (& the curious case of European genotypes)
- Today's slides
- European men, their genomes, and their geography
- Relevant to today's discussion for his eponymous distance measure: Mahalanobis
A smattering of links on PCA:
- NBT Primer on PCA
- A PCA overview (.docx format) & the original post
- Science Signaling (more specifically, Neil R. Clark and Avi Ma’ayan!) had a nice introduction to PCA that I've reposted here (with slides)
- Python code for performing PCA yourself
Mar 31, 2016 - Classifiers I
- Today's slides
- Classifying leukemias
- For those of you interesting in trying out classifiers on your own, here's the best open software for do-it-yourself classifiers and data mining: Weka
Mar 29, 2016 - Clustering II
- We're finishing up the slides from Mar. 24.
- Fuzzy k-means
- SOM gene expression
- Links to various applications of SOMs: 1, 2, 3, 4. You can run SOMs on the following web site. You can also run SOM clustering with the Open Source Clustering package from problem set 3 with the '-s' option, or GUI option. See the manual for details. (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).
Mar 24, 2016 - Functional Genomics & Data Mining - Clustering I
- Today's slides
- Clustering
- Review of phylogenetic profiles
- B cell lymphomas
- Primer on clustering
- K-means example (.ppt)
Problem Set 3, due before midnight Apr. 14, 2016. You will need the following software and datasets:
- The clustering and treeview software is available here.
- Yeast protein sequences
- Yeast protein phylogenetic profiles
- Yeast mRNA expression profiles
Mar 22, 2016 - Motifs
- Homework #3 (worth 10% of your final course grade) is due on Rosalind by 11:59PM tonight. There were apparently problems with the Meme web server, but it appears to working now. Also, a mirror Meme server has been set up as an alternative.
- Go ahead and start mini-assignment 2, and try to finish it within a week.
- Today's slides
- NBT Primer - What are motifs?
- NBT Primer - How does motif discovery work?
- The biochemical basis of a particular motif
- Gibbs Sampling
- AlignAce
Mar 15-17, 2016 - SPRING BREAK
- Finish HW3 and and the first mini-assignment (#1) for your gene project.
Mar 10, 2016 - Genomes II
- For those of you interested in doing your homework/research with more experienced coders in the room, there is a weekly Open Coding Hour in the CCBB conference room / collaboratorium (GDC 7.514) each Tuesday from 5-6 PM. [1].
- Homework #3 (worth 10% of your final course grade) has been assigned on Rosalind and is due by 11:59PM March 22.
- We're finishing up the slides from Mar. 8, then on to motif-finding. Note: we'll increasingly be discussing primary papers in the lectures. Here are a few classics and reviews that will come up after Spring Break if you want to start looking ahead.
- Gene expression by ESTs
- Gene expression by SAGE
- Affy microarrays 1 & Affy microarrays 2
- cDNA microarrays
- RNA-Seq
- Clustering by gene expression
- Cell cycle data
Mar 8, 2016 - Genome Assembly
- Today's slides
- A gentle reminder that Problem Set 2 is due by 11:59PM tonight
- DeBruijn Primer and Supplement
- Here are a few explanations of using the BWT for indexing: 1 2
Mar 3, 2016 - Gene finding II
- We're finishing up the slides from Feb. 25, then moving on into Genome Assembly
Mar 2, 2016 - TA office hours canceled due to illness, rescheduled tomorrow, Mar 3, 3-4PM
Mar 1, 2016 - Next-generation Sequencing (NGS)
- Guest speaker: Dr. Scott Hunicke-Smith, former director of the Genome Sequencing and Analysis Facility, and current director of commercial NextGen sequencing diagnostics.
- Illumina/Solexa Sequencing (Youtube Video)
- Genome Analyzer (Youtube Video)
Feb 25, 2015 - Gene finding
Reading:
Feb 23, 2016 - HMMs II
- We're finishing up the slides from Feb. 18.
Problem Set 2, due before midnight Mar. 8, 2016:
- Problem Set 2.
- You'll need these 3 files: State sequences, Soluble sequences, Transmembrane sequences
Feb 18, 2015 - Hidden Markov Models
- Don't forget: Homework #2 (worth 10% of your final course grade) is due on Rosalind by 11:59PM today.
- It's also time to get started with our major class project. Here are the instructions. Go ahead and start mini-assignment 1, and try to finish it within a week. There will be 5 of these from now until the end of the semester. By classtime Tuesday, Feb. 23, email the TA the name of the gene you selected and a link to the web page you are creating for your project. (You can find instructions for how to create a google web site at the bottom of this page.)
- Another view of the remarkable growth of data, e.g. UniProt
- Today's slides
Reading:
- HMM primer and Bayesian statistics primer, Wiki Bayes
- Care to practice your regular expressions? (In python?)
Feb 16, 2016 - 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
Feb 11, 2016 - 3D Protein Structure Modeling
- Guest speaker: Dr. Kevin Drew, formerly of New York University and now at the UT Center for Systems and Synthetic Biology
- Today's slides
- The Rosetta software suite for 3D protein modeling, and what it can do for you
- The Protein Data Bank, HHPRED, MODELLER, and Pymol
Feb 9, 2016 - BLAST
- News of the day: farmaceuticals from transgenic chickens
- Homework #2 (worth 10% of your final course grade) has been assigned on Rosalind and is due by 11:59PM February 18.
- 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.
Feb 4, 2016 - Guest lecture: Homologs, orthologs, and evolutionary trees
- *** HEADS UP FOR THE PROBLEM SET *** If you're trying to use the Python string.count function to count dinucleotides, Python counts non-overlapping instances, not overlapping instances. So, AAAA is counted as 2, not 3, dinucleotides. You want overlapping dinucleotides instead, so will have to try something else, such as the python string[counter:counter+2] command, as explained in the Rosalind homework assignment on strings.
- We'll have a guest lecture by Ben Liebeskind, a postdoctoral fellow in the Center for Systems and Synthetic Biology, on decoding the evolutionary relationships among genes.
- Today's slides
- For those of you pre-med or health-focused students, you might be interested in volunteer opportunities in South Africa (application)
Feb 2, 2016 - Sequence Alignment II
- We're finishing up the slides from Jan. 28.
- Dynamic programming primer
- An example of dynamic programming using Excel, created by Michael Hoffman (a former UT undergraduate who took a prior incarnation of this class)
- A few examples of proteins with internally repetitive sequences: 1, 2, 3
Jan 28, 2016 - Sequence Alignment I
Problem Set I, due before midnight Feb. 4, 2016:
- 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
- There is a good discussion of the alignment algorithms and different scoring schemes here
Jan 26, 2016 - Rosalind help & programming Q/A
- The TA office hours have changed to better accommodate conflicts. The new office hours have shifted forward 1 hour, to Wed/Thurs 3-4.
- One of my favorite news items of the last few last years: 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 >2,000 bioinformatics researchers.
- Statistics in Python
- We'll be finishing Python slides from last time.
Jan 21, 2016 - Intro to Python
- News of the day/Science in action: There's a huge ongoing debate raging about the development of CRISPR genome editing technology, stemming in part from an ongoing patent contest over who made key innovations in characterizing, engineering, and applying CRISPR. You can read some of the debate here, here, and here, among many other sites.
- Today's slides
- Python primer
- E. coli genome
- Python 2 vs 3?. For compatibility with Rosalind and other materials, we'll use version 2.7.
Jan 19, 2016 - 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 BCH339N 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 28.
- 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
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 biochemistry majors. Prerequisites: Biochemistry 339F or Chemistry 339K with a grade of at least C-.
Requires basic familiarity with molecular biology & basic statistics, although varied backgrounds are expected.
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 an independent course project (25% of final grade). The course project will be focused on a specific gene & will involve bioinformatics research (e.g. calculation, programming, database analysis, etc.) developed over the semester in 5 mini-assignments, which will be turned in as a link to a web page that you will continue to expand over the semester. The completed final web site is due by midnight, April 27, 2016, and will be presented to the rest of the class on the last 3 class days. Each mini-assignment is 4% of the final grade; the presentation will be worth 5%.
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.
The final project web site is due by midnight April 27, 2016.
- How to make a web site for the final project
- Google Site: https://support.google.com/sites/answer/153197?hl=en