Difference between revisions of "BCH391L 2015"

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== Lectures & Handouts ==
 
== Lectures & Handouts ==
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'''May 5 - 7, 2015 - Final Projects'''
 
'''May 5 - 7, 2015 - Final Projects'''
 +
Note: There are some great [http://ccbb.biosci.utexas.edu/summerschool.html short summer courses in computational biology] being offered at UT. Of particular note, introductions to [http://ccbb.biosci.utexas.edu/summerschool.html#corengs core NextGen sequencing tools] and [http://ccbb.biosci.utexas.edu/summerschool.html#rosetta protein modeling using Rosetta]
 +
* [https://sites.google.com/site/azatliteratureexplorer/ LiteratureExplorer]
 +
* [https://sites.google.com/a/utexas.edu/erik_henry_jesus_391l/ Single Molecule Peptide Sequencing Simulations]
 +
* [https://sites.google.com/site/p53snps/ Effects of SNPs on p53]
 +
* [https://sites.google.com/site/rvwbch391final/home Integrating Big Data: Making sense of transcriptomic data in a cellular context]
 +
* [https://sites.google.com/a/utexas.edu/msprot/home Identification of Peptides using an HMM Approach]
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* [https://sites.google.com/site/dnashufflingopt/home A program to optimize DNA shuffling]
 +
* [http://clairemcwhite.github.io/ Ortholog Database Connector]
 +
* [https://sites.google.com/a/utexas.edu/bioinformatics-bch-364c-391l/ Single Nucleotide Polymorphisms Analysis]
 +
* [http://jedesautelle.wix.com/hmmp-substrates Residues involved in Human Matrix Metalloproteases substrate recognition]
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* [https://sites.google.com/a/utexas.edu/cilia/ Cilia]
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* [https://sites.google.com/site/structuredrnaprediction/ Structured RNA Predictor]
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* [https://sites.google.com/site/phanmcgurk/ Searching for conserved cis-regulatory modules]
  
'''April 30, 2015 - Synthetic Biology II'''
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'''April 30, 2015 - Synthetic Biology'''
* [http://www.marcottelab.org/users/BCH391L_2015/BCH364C-391L_SyntheticBio2_Spring2015.pdf Today's slides]
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* [http://www.marcottelab.org/users/BCH391L_2015/BCH364C-391L_SyntheticBio-Spring2015.pdf Today's slides]
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A collection of further reading, if you're so inclined:
 
* [http://www.marcottelab.org/users/BCH391L_2015/GenomeTransplantation.pdf Genome Transplantation]
 
* [http://www.marcottelab.org/users/BCH391L_2015/GenomeTransplantation.pdf Genome Transplantation]
 
* [http://www.marcottelab.org/users/BCH391L_2015/JCVI-1.0.pdf JCVI-1.0]
 
* [http://www.marcottelab.org/users/BCH391L_2015/JCVI-1.0.pdf JCVI-1.0]
* [http://www.marcottelab.org/users/BCH391L_2015/EllingtonDNAFab.jpg A DNA Fab], courtesy of [http://ellingtonlab.org/ Andy Ellington]
 
 
* [http://www.marcottelab.org/users/BCH391L_2015/OneStepAssemblyInYeast.pdf One step genome assembly in yeast]
 
* [http://www.marcottelab.org/users/BCH391L_2015/OneStepAssemblyInYeast.pdf One step genome assembly in yeast]
 
* [http://www.marcottelab.org/users/BCH391L_2015/StrainsFromYeastGenomicClones.pdf New cells from yeast genomic clones]
 
* [http://www.marcottelab.org/users/BCH391L_2015/StrainsFromYeastGenomicClones.pdf New cells from yeast genomic clones]
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* [http://www.marcottelab.org/users/BCH391L_2015/YeastSynthCsome.pdf 1/2 a synthetic yeast chromosome] and [http://syntheticyeast.org/ Build-A-Genome]
 
* [http://www.marcottelab.org/users/BCH391L_2015/YeastSynthCsome.pdf 1/2 a synthetic yeast chromosome] and [http://syntheticyeast.org/ Build-A-Genome]
 
* & the latest: [http://www.marcottelab.org/users/BCH391L_2015/Science-2014-Annaluru-55-8.pdf Entire synthetic yeast chromosome]  
 
* & the latest: [http://www.marcottelab.org/users/BCH391L_2015/Science-2014-Annaluru-55-8.pdf Entire synthetic yeast chromosome]  
Food for thought:<br>
 
[http://www.nationalgeographic.com/deextinction De-extinction I], [http://science.kqed.org/quest/video/reawakening-extinct-species/ II], and [http://www.popsci.com/woolly-mammoth-dna-brought-life-elephant-cells III]
 
 
'''April 28, 2015 - Synthetic Biology I'''
 
* [http://www.marcottelab.org/users/BCH391L_2015/BCH364C-391L_SyntheticBio1_Spring2015.pdf Today's slides]
 
* [http://www.kickstarter.com/projects/antonyevans/glowing-plants-natural-lighting-with-no-electricit Synthetic biology in the news]
 
 
* [http://en.wikipedia.org/wiki/Gillespie_algorithm The Gillespie algorithm]
 
* [http://en.wikipedia.org/wiki/Gillespie_algorithm The Gillespie algorithm]
* Download the synthetic biology comic [http://openwetware.org/wiki/Adventures here!]
 
 
* [https://www.igem.org/Main_Page iGEM], and an example part ([http://parts.igem.org/Featured_Parts:Light_Sensor the light sensor])
 
* [https://www.igem.org/Main_Page iGEM], and an example part ([http://parts.igem.org/Featured_Parts:Light_Sensor the light sensor])
 
* [http://www.popsci.com/diy/article/2013-08/grow-photo Take your own coliroids]
 
* [http://www.popsci.com/diy/article/2013-08/grow-photo Take your own coliroids]
Reading:<br>
 
 
* [http://www.marcottelab.org/users/BCH391L_2015/repressilator.pdf The infamous repressilator]
 
* [http://www.marcottelab.org/users/BCH391L_2015/repressilator.pdf The infamous repressilator]
 
* [http://www.marcottelab.org/users/BCH391L_2015/BacterialPhotography.pdf Bacterial photography], and [http://www.marcottelab.org/users/BIO337_2014/UTiGEM2012.pdf UT's 2012 iGEM entry]
 
* [http://www.marcottelab.org/users/BCH391L_2015/BacterialPhotography.pdf Bacterial photography], and [http://www.marcottelab.org/users/BIO337_2014/UTiGEM2012.pdf UT's 2012 iGEM entry]
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* [http://www.marcottelab.org/users/BCH391L_2015/nbt.2510.pdf A more recent example of digital logic]
 
* [http://www.marcottelab.org/users/BCH391L_2015/nbt.2510.pdf A more recent example of digital logic]
 
* An example of metabolic engineering: [http://www.nature.com/nature/journal/vaop/ncurrent/full/nature12051.html yeast making anti-malarial drugs]
 
* An example of metabolic engineering: [http://www.nature.com/nature/journal/vaop/ncurrent/full/nature12051.html yeast making anti-malarial drugs]
 +
Food for thought:<br>
 +
[http://www.nationalgeographic.com/deextinction De-extinction I], [http://science.kqed.org/quest/video/reawakening-extinct-species/ II], and [http://www.popsci.com/woolly-mammoth-dna-brought-life-elephant-cells III]
  
'''April 23, 2015 - Phenologs'''
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'''April 28, 2015 - Phenologs'''
 
* [http://www.marcottelab.org/users/BCH391L_2015/BCH364C-391L_Phenologs_Spring2015.pdf Today's slides]
 
* [http://www.marcottelab.org/users/BCH391L_2015/BCH364C-391L_Phenologs_Spring2015.pdf Today's slides]
 
* [http://www.marcottelab.org/paper-pdfs/PNAS_Phenologs_2010.pdf Phenologs] and the [http://www.marcottelab.org/paper-pdfs/PLoSBiology_TBZ_2012.pdf drug discovery story] we'll discuss in class
 
* [http://www.marcottelab.org/paper-pdfs/PNAS_Phenologs_2010.pdf Phenologs] and the [http://www.marcottelab.org/paper-pdfs/PLoSBiology_TBZ_2012.pdf drug discovery story] we'll discuss in class
 
* Search for phenologs [http://www.phenologs.org/ here].  You can get started by rediscovering the plant model of Waardenburg syndrome.  Search among the known diseases for "Waardenburg", or enter the human genes linked to Waardenburg (Entrez gene IDs 4286, 5077, 6591, 7299) to get a feel for how this works. Also, here's [http://www.nytimes.com/2010/04/27/science/27gene.html?_r=0 Carl Zimmer's NYT article] about phenologs and the scientific process.
 
* Search for phenologs [http://www.phenologs.org/ here].  You can get started by rediscovering the plant model of Waardenburg syndrome.  Search among the known diseases for "Waardenburg", or enter the human genes linked to Waardenburg (Entrez gene IDs 4286, 5077, 6591, 7299) to get a feel for how this works. Also, here's [http://www.nytimes.com/2010/04/27/science/27gene.html?_r=0 Carl Zimmer's NYT article] about phenologs and the scientific process.
* One good tool for discovering orthologs is [http://inparanoid.sbc.su.se/cgi-bin/index.cgi InParanoid].  Note: InParanoid annotation lags a bit, so you'll need to find the [http://www.ensembl.org/index.html Ensembl] protein id, or try a text search for the common name.
+
Tools for finding orthologs:<br>
 +
* One good tool for discovering orthologs is [http://inparanoid.sbc.su.se/cgi-bin/index.cgi InParanoid].  Note: InParanoid annotation lags a bit, so you'll need to find the [http://www.ensembl.org/index.html Ensembl] protein id, or try a text search for the common name. InParanoid tends towards higher recall, lower precision for finding orthologs. Approaches with higher precision include [http://omabrowser.org/oma/home/ OMA] (introduced in [http://www.marcottelab.org/users/BCH391L_2015/OMA.pdf this paper]), [http://phylomedb.org/ PhylomeDB], and just released, [http://pythonhosted.org/bio-MOSAIC/ MOSAIC]
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* [http://www.marcottelab.org/users/BCH391L_2015/Sonnhammer2002TiG.pdf All your ortholog definition questions answered!]
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'''April 23, 2015 - Networks II'''
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* We're finishing up the slides from Apr. 21.
 +
* Worth noting: [http://ccbb.biosci.utexas.edu/summerschool.html UT Summer school for big data in biology]
  
 
'''April 21, 2015 - Networks'''
 
'''April 21, 2015 - Networks'''
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'''Apr 16, 2015 - Genome Engineering'''
 
'''Apr 16, 2015 - Genome Engineering'''
 
* Guest speaker: [http://cssb.utexas.edu/fellows/christopher-yellman/ Dr. Chris Yellman]
 
* Guest speaker: [http://cssb.utexas.edu/fellows/christopher-yellman/ Dr. Chris Yellman]
* [http://www.marcottelab.org/users/BCH391L_2015/synthetic-biology-genome-engineering-2-2014.ppt Today's slides]
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<!--* [http://www.marcottelab.org/users/BCH391L_2015/synthetic-biology-genome-engineering-2-2014.ppt Today's slides]-->
  
 
'''Apr 14, 2015 - Principal Component Analysis (& the curious case of European genotypes)'''
 
'''Apr 14, 2015 - Principal Component Analysis (& the curious case of European genotypes)'''
 
* [http://www.marcottelab.org/users/BCH391L_2015/BCH364C-391L_PCA_Spring2015.pdf Today's slides]
 
* [http://www.marcottelab.org/users/BCH391L_2015/BCH364C-391L_PCA_Spring2015.pdf Today's slides]
 
* [http://www.marcottelab.org/users/BCH391L_2015/EuropeanGenesPCA.pdf European men, their genomes, and their geography]
 
* [http://www.marcottelab.org/users/BCH391L_2015/EuropeanGenesPCA.pdf European men, their genomes, and their geography]
* For those of you using classifiers for your projects, here's the best open software for do-it-yourself classifiers and data mining: [http://www.cs.waikato.ac.nz/ml/weka/ Weka]
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* Relevant to today's discussion for his eponymous distance measure: [http://en.wikipedia.org/wiki/Prasanta_Chandra_Mahalanobis Mahalanobis]
* & since he's come up in class several times: [http://en.wikipedia.org/wiki/Prasanta_Chandra_Mahalanobis Mahalanobis]
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A smattering of links on PCA:<br>
 
A smattering of links on PCA:<br>
 
* [http://www.marcottelab.org/users/BCH391L_2015/NBT_primer_PCA.pdf NBT Primer on PCA]
 
* [http://www.marcottelab.org/users/BCH391L_2015/NBT_primer_PCA.pdf NBT Primer on PCA]
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* Science Signaling (more specifically, Neil R. Clark and Avi Ma’ayan!) had a [http://stke.sciencemag.org/cgi/content/full/sigtrans;4/190/tr3/DC1 nice introduction to PCA] that I've reposted [http://www.marcottelab.org/users/BCH391L_2015/IntroToPCA.pdf here] (with [http://www.marcottelab.org/users/BCH391L_2015/2001967Slides-FINAL.ppt slides])
 
* Science Signaling (more specifically, Neil R. Clark and Avi Ma’ayan!) had a [http://stke.sciencemag.org/cgi/content/full/sigtrans;4/190/tr3/DC1 nice introduction to PCA] that I've reposted [http://www.marcottelab.org/users/BCH391L_2015/IntroToPCA.pdf here] (with [http://www.marcottelab.org/users/BCH391L_2015/2001967Slides-FINAL.ppt slides])
 
* Python code for [http://sebastianraschka.com/Articles/2015_pca_in_3_steps.html performing PCA yourself]
 
* Python code for [http://sebastianraschka.com/Articles/2015_pca_in_3_steps.html performing PCA yourself]
-->
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'''Apr 9, 2015 - Classifiers I'''
 
'''Apr 9, 2015 - Classifiers I'''
 
* [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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* For those of you using classifiers for your projects, here's the best open software for do-it-yourself classifiers and data mining: [http://www.cs.waikato.ac.nz/ml/weka/ Weka]
  
 
'''Apr 7, 2015 - Clustering II
 
'''Apr 7, 2015 - Clustering II

Latest revision as of 10:55, 7 May 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

May 5 - 7, 2015 - Final Projects Note: There are some great short summer courses in computational biology being offered at UT. Of particular note, introductions to core NextGen sequencing tools and protein modeling using Rosetta

April 30, 2015 - Synthetic Biology

A collection of further reading, if you're so inclined:

Food for thought:
De-extinction I, II, and III

April 28, 2015 - Phenologs

  • Today's slides
  • Phenologs and the drug discovery story we'll discuss in class
  • Search for phenologs here. You can get started by rediscovering the plant model of Waardenburg syndrome. Search among the known diseases for "Waardenburg", or enter the human genes linked to Waardenburg (Entrez gene IDs 4286, 5077, 6591, 7299) to get a feel for how this works. Also, here's Carl Zimmer's NYT article about phenologs and the scientific process.

Tools for finding orthologs:

April 23, 2015 - Networks II

April 21, 2015 - Networks

  • 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:

Apr 16, 2015 - Genome Engineering

Apr 14, 2015 - Principal Component Analysis (& the curious case of European genotypes)

A smattering of links on PCA:

Apr 9, 2015 - Classifiers I

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.