CH391L 2013

CH364C/CH391L Bioinformatics

Course unique #: 52716/52990
Lectures: Tuesday/Thursday 2:00 – 3:30 PM in WEL 3.260
Instructor: Edward Marcotte, marcotte@icmb.utexas.edu

• Office hours: Wednesdays 2:00 – 3:00 PM in MBB 3.148BA Phone: 471-5435
  

TA: John Woods, john.woods at marcottelab dot org

• TA Office hours: Tuesday/Friday 10:00 – 11:00 AM in MBB 3.128 Phone: 232-3919
  
  • NOTE #1: John will be out of town 4/18 through 4/22. If you need to meet with him, email him and schedule a gchat meeting for Friday sometime.
  • NOTE #2: TA office hours will start at 10:30am the week of 4/22 instead of 10am (and will end at 11:30am). If you can't make it during those hours, as always, email John to set up an appointment.

Lectures & Handouts

May 2, 2013 - Some of the (few!) publicly-viewable final projects. Many private ones this time!

• An Investigation of the Effects of Sequencing Depth on Binding Region Identification in ChIP-seq Data
• Extraction and Analysis of microRNA Precursor Sequences from Human RNA-Seq Datasets
• Structure and Evolution of AprD4
• Identifying differentially expressed genes
• Changes in host gene expression from Bordetella infection or toxicity
• Diagnosing breast cancer based on PBMC gene expression profile using Bayesian additive regression trees (BART) method
• Divergence of FRIGIDA in Arabidopsis thaliana ecotypes

April 30, 2013 - Synthetic biology

• Genome Transplantation
• JCVI-1.0
• A DNA Fab, courtesy of Andy Ellington
• One step genome assembly in yeast
• New cells from yeast genomic clones
• A new cell from a chemically synthesized genome, SOM
• Synthetic yeast chromosome and Build-A-Genome

April 25, 2013 - Synthetic biology

• Fun science news of the day: You and your dog share more than you might think
• & more Synthetic biology in the news
• The infamous repressilator
• The infamous toggle switch
• The Gillespie algorithm
• Handout on Gillespie
• Bacterial photography
• Edge detector
• & a more recent example of digital logic
• Finally, the example on metabolic engineering mentioned in class: yeast making malarial drugs

April 18-23, 2013 - Networks

• Hox genes
• Module networks
• Small world networks
• Dijkstra's algorithm (animated)
• Scale-free networks
• Attack tolerance
• Lethality-centrality
• Yeast complexes
• PathBlast, Supplement

April 16, 2013 - Networks

• Metabolic networks: The wall chart & the current state of the human metabolic reaction network
• Transcriptional networks: ChIP-Chip & ChIP-SEQ, large-scale screens-1, large-scale screens-2, heritability, and ENCODE
• Protein interactions: overview, one of the first large-scale screens & networks, and a recent map by co-fractionation
• Protein interaction extent and quality

April 11, 2013 - Motifs

• A linear algebra refresher
• NBT Primer - What are motifs?
• NBT Primer - How does motif discovery work?
• The biochemical basis of a particular motif
• Gibbs Sampling
• AlignAce

April 9, 2013

• IMPORTANT REMINDER! Today is one of our scheduled NO CLASS DAYS! Given that, and the trouble that several students have had getting clustering software working on Macs, I'm

extending the homework due date to April 11.

April 2-4, 2013 - Classification & PCA/SVD

• A PCA overview (.docx format) & the original post
• Science Signaling (more specifically, Neil R. Clark and Avi Ma’ayan!) had a nice, very gentle introduction to PCA that I've reposted here (with slides)
• NBT Primer on PCA
• The best open software for do-it-yourself data mining: Weka
• Mahalanobis & his Mahalanobis distance
• SVD of gene expression
• European men, their genomes, and their geography

Mar 28, 2013 - Clustering & Classification

• AML vs ALL
• Diffuse large B cell lymphoma redux
• Network visualization primer, LGL, Cytoscape

Mar 27, 2013

• The seminar by Bob Sauer (2:30-3:30, Welch convocation center) conflicts with office hours today, so office hours will be held after seminar instead (3:30-4:30).

Mar 26, 2013 - Clustering 2

• Fuzzy k-means
• SOM gene expression
  • & links to various applications of SOMs: 1, 2, 3, 4, and a picture of Teuvo himself (and his analyses of Finnish news feeds and USENET articles)
  • 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).

An assortment of datasets for Problem Set 4, due Apr. 9, 2013. Someone in the class noted that the phylogenetic profile file was space, not tab, delimited, and that there were a few lines with errors in the mRNA expression data. I've updated the links to be the correct versions. Also, several people have noted that the Mac/Linux versions of the tree viewing program seem to be a bit buggy; however, the Windows version (TreeView) seems to be fine.

• Yeast protein sequences
• Yeast protein phylogenetic profiles
• Yeast mRNA expression profiles

Mar 21, 2013 - Clustering

• Phylogenetic profiles 1 and 2
• Review of phylogenetic profiles
• Example phylo profiles from Neurospora
• B cell lymphomas
• Primer on clustering
• K-means example (.ppt)

Mar 19, 2013 - Gene expression Wrapping up sequencing:

• An overview of the current state of DNA sequencing and applications
• Forward genetics by kmer comparisons

& on to RNA expression!

• Gene expression by ESTs
• Gene expression by SAGE
• Affy microarrays 1
• Affy microarrays 2
• cDNA microarrays
• Clustering by gene expression
• Cell cycle data
• Clustering

Mar 7, 2013 - Assembly and mapping

• Bellman-Ford-Moore
• Burrows-Wheeler
• Suffix Array

Mar 5, 2013 - Assembling genomes + next-gen sequencing

• NextGen sequencing general review
• NextGen sequencing analysis review
• de Bruijn graph-based assembly using EULER and a de Bruijn primer (with Supplement)
• An intro to the Velvet assembler, assembled (no pun intended) by former UT undergraduate Matthew Tien
• Mapping primer
• Assembly/NGS slides

Feb 28, 2013 - Assembling genomes

• Due March 8 by email - One (full) paragraph describing your plans for a final project.
• Here are a few examples of final projects from previous years: 1, 2, 3, 4, 5 6 7 8 9 10
• Fly - the genome
• Fly - the genome assembly
• GigAssembler

Feb 26, 2013 - Assembling genomes

• BACs, YACs, and cosmids, oh my!
• The H. influenzae genome paper
• Next-gen sequencing news, surveying the field just 2 years ago
• Sequencing, sequencing, sequencing - new technologies, yet more, and even more
• Prenatal screening by sequencing, now whole fetal genomes
• HW2.1
• published T segment histograms and in our own data
• One published strategy that does what you tried in your homework: TMHMM
• General: You're now ahead of the pack...

Feb 21, 2013 - Gene finding

• The GeneMark.hmm paper and the program
• The GENSCAN paper
• A nice review of gene finding
• Evaluating gene annotations: GASP, EGASP, & nGASP

Feb 19, 2013 - HMMs and gene finding

• Given that we're running a lecture behind, HW#2 will be due on Feb. 26, rather than the 21st.
• Fly cell Markov chains

Feb 14, 2013 - HMMs

• Breaking news: science of the highest importance!
• HMM primer
• Problem Set 2, due Feb. 26, 2013
• State sequences
• Soluble sequences
• Transmembrane sequences

Feb 12, 2013 - Profiles

• Bayesian statistics primer, Wiki Bayes, and a simple example
• For the masochists in the class: Care to practice your regular expressions? (In python?) Try this crossword puzzle.
• Profile analysis, as originally described
• A commentary on computational challenges arising from DNA sequencing
• The remarkable growth of Genbank, and similarly, UniProt

Feb 7, 2013 - BLAST

• The original BLAST paper
• Teaching BLAST
• 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 5, 2013 - Sequence Alignment III

• A few examples of proteins with internally repetitive sequences: 1, 2, 3
• Repeats in the human genome, tallied here
• In the news: The pigeon genome

Jan 31, 2013 - Sequence Alignment II

• An example of dynamic programming using Excel, created by Michael Hoffman (a former CH391L student; you can read more about Michael here)
• Dynamic programming primer

Jan 24, 2013 - Sequence Alignment I

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

Jan 22, 2013 - Intro to Python

• Just FYI, we seem to be having a few issues with the server, but it should be up and running now (as of 9:50PM)
• Python primer
• Problem Set 1, due Feb. 5, 2013
• E. coli genome
• T. volcanium genome
• 3 mystery genes (for Problem 5): Mgene1, Mgene2, Mgene3

Jan 17, 2013 - Newsworthy computational biology story of the week!

• Gymrek et al. (Supplement) show that genomic datasets are not as anonymous as we thought!]
• There are some associated commentaries, if you're curious: #1 2 #3

Syllabus & course outline

Course syllabus

An introduction to computational biology and bioinformatics. The course covers typical data, data analysis, and algorithms encountered in computational biology. Topics will include introductory probability and statistics, basics of programming, protein and nucleic acid sequence analysis, genome sequencing and assembly, synthetic biology, analysis of gene expression data, data clustering, biological pattern recognition, and biological networks.

Open to graduate students and upper division undergraduates 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.

Most of the lectures will be from research articles and handouts, with some material from the...
Recommended text (for sequence analysis): Biological sequence analysis, by R. Durbin, S. Eddy, A. Krogh, G. Mitchison (Cambridge University Press),

For non-molecular biologists, I highly recommend (really!) The Cartoon Guide to Genetics (Gonick/Wheelis)
For biologists rusty on their stats, The Cartoon Guide to Statistics (Gonick/Smith) is also very good.

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

No exams will be given. Grades will be based on 4 problem sets (given every 2 weeks and counting 15% each towards the final grade) and a course project (40% of final grade), which can be individual or collaborative. If collaborative, cross-discipline collaborations are encouraged. The course project will consist of a research paper or 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 on April 30, 2013.

Helpful links

• If you don't have a unix/linux account to do the homework and/or project, send email to 'john.woods at marcottelab dot org'.
• CH391L_2013/Connecting_Server (If you don't know how to use the account info, this are the instructions.)
• If you are having trouble transferring files from your computer to server, here are some GUI programs that can help you:
  • http://winscp.net/eng/index.php (WinSCP, Windows)
  • http://cyberduck.ch/ (CyberDuck, Mac)
  • http://filezilla-project.org/ (FileZilla, all platforms)

• 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++

• Other relevant courses on campus:
  • Geometric (Bio-) modeling and visualization
  • Statistical and Discrete Methods for Scientific Computing
  • BIO 337: Developmental Biology, emphasizing how to how to critically read and dissect papers.