CS68 Bioinformatics - Spring 2017

Announcements

Jump to this week in the schedule
Your final project is due Friday, April 28.

This syllabus is a living document; please be aware that many elements on this page will change throughout the semester, including the course schedule. It is the student's responsibility to review this page periodically for updates.

I value any and all student feedback. If you would like to provide anonymous course feedback, use this submission form here. Please be constructive in any comments so that I can adjust the course as best possible.

Schedule

For the reading assignments the section numbers are inclusive, so "1.1-1.1.2" means you should read all the sections from 1.1 up to and including section 1.1.2. This is a tentative schedule, it will change as we go.

WEEK	DATE	ANNOUNCEMENTS	TOPIC & READING	LABS & NOTES
1	Jan 17	Video, Notes, Slides	Introduction to Bioinformatics & Molecular Biology Life and Its Molecules: A Brief Introduction by Lawrence Hunter Recommended: Primer on Molecular Genetics from the US DOE Recommended: Molecular Biology for Computer Scientists by Lawrence Hunter
	Jan 19	Video, Notes, Slides
2	Jan 24	Video, Notes, Slides	Pairwise Sequence Alignment - Detecting Homology Durbin et al., 2.1-2.3 Gapped BLAST and PSI-BLAST by Altschul et al., 1997 Alignment of Whole Genomes by Delcher et al., 1999. Recommended: Durbin et al., The rest of Chapter 2	Lab 0 - Central Dogma and Databases
	Jan 26	Video, Notes, Slides Drop/add ends (Jan 30)
3	Jan 31	Video, Notes, Slides (PSA)		Lab 1 - Dynamic Programming and Pairwise Sequence Alignment
	Feb 02	Video, Notes, Slides (MSA)	Multiple Sequence Alignment and Phylogenetic Trees Durbin et al., Chapter 6-6.4 Durbin et al., Chapter 7 ClustalX Tutorial MUSCLE by Edgar, 2004. UPGMA Video Neighbor Joining Introduction Ultrametric(Optional)
4	Feb 07	Video, Notes, Slides (MSA)
	Feb 09	Video, Notes, Slides (Phylogenetic Trees)
5	Feb 14	Video, Notes, Slides		Lab 2 - Multiple Sequence Alignment
	Feb 16	Video, Notes, Slides	Functional Genomics and Clustering Algorithms Interactive animation of microarray experiments from the University of Utah Cluster Analysis for Gene Expression Data: A Survey by Daxin Jiang, Chun Tang, and Aidong Zhang Chapter 16: Flat Clustering from Introduction to Information Retrieval by C. Manning, P. Raghavan, and H. Schutze. (You are not responsible for algorithms not covered in class) Supplementary Exploring the new world of the genome with DNA microarrays by Patrick Brown and David Botstein Chapter 17: Hierarchical Clustering from Introduction to Information Retrieval by C. Manning, P. Raghavan, and H. Schutze RNA-Seq: a revolutionary tool for transcriptomes by Zhang Wong, Mark Gerstein, and Michael Snyder
6	Feb 21	Video, Notes, Slides		Lab 3 - Inferring the Tree of Life In lab notes for NJ and WP
	Feb 23	Video, Notes, Slides
7	Feb 27	Midterm exam - in lab 02/27
	Feb 28	Video, Notes, Slides	Supervised Machine Learning (Recommended) Using Machine Learning to Design and Interpret Gene-Expression Microarrays by M. Molla, M. Waddell, D. Page and J. Shavlik, in AI Magazine, 2004 A Few Useful Things to Know About Machine Learning by Pedro Domingos in Communications of the ACM, 2012 Decision Trees
	Mar 02	Video, Notes, Slides
	Mar 07	Spring Break
	Mar 09
8	Mar 14	Domingos Sec. 1-4 Visual Intro to ML Video, Notes, Slides	Supervised Machine Learning (Recommended) Using Machine Learning to Design and Interpret Gene-Expression Microarrays by M. Molla, M. Waddell, D. Page and J. Shavlik, in AI Magazine, 2004 A Few Useful Things to Know About Machine Learning by Pedro Domingos in Communications of the ACM, 2012 Decision Trees (continued)	Lab 4 - Clustering Gene Expressions In lab notes for EM In lab notes on Eisen et al. paper
	Mar 16	Domingos - 5,6,11,12 Decision Trees (Intro and Example) Video, Notes, Slides
9	Mar 21	Information Gain (through page 7) Video, Notes, Slides
	Mar 23	Video, Notes, Slides Durbin et al., Ch 1.3 Last day to declare CR/NC or withdraw (Mar 24)	Probabilistic Sequence Models - Markov Models Basic Probability Definitions Durbin et al., Chapter 1 Durbin et al., Chapter 11 (at a high level) Durbin et al., Chapter 3.1-3.2	Lab 5 - Classifying Leukemia Patients Final project proposal
10	Mar 28	Basic Probability Video, Notes, Slides
	Mar 30	Durbin et al., Ch 3.1 Video, Notes, Slides
11	Apr 04	Durbin et al., Ch 3.5 Video, Notes, Slides	Hidden Markov Models and applications Durbin et al., Chapter 3.3-3.5 Durbin et al., Chapter 5 Profile hidden Markov models by Sean R. Eddy	Final Project HMM Problem Set
	Apr 06	Durbin et al., Ch 3.2 (stop at Viterbi pg. 56) Video, Notes, Slides
12	Apr 11	Durbin et al., Ch 3.2 (forward, backward) Video, Notes, Slides
	Apr 13	Durbin et al., Ch 3.3 Video, Notes, Slides
13	Apr 18	Durbin et al., Ch 5-5.2 Video, Notes, Slides
	Apr 20	Yann LeCun's Deep Learning Tutorial Video, Notes, Slides	Deep Learning Neural Network Playground Deep Learning by LeCun, Bengio, & Hinton in Nature, 2015 The Great A.I. Awakening in New York Times, 2016. Autoencoders Visualizing a Trained Autoencoder Deep Learning in Bioinformatics by Min, Lee, and Yoon in Briefing in Bioinformatics, 2016. Supplementary A Neural-Network Primer by Thomas R. Schultz, Chapter 2, from Computational Developmental Psychology Scaling Learning Algorithms towards AI by Bengio and LeCun Representation Learning: A Review and New Perspectives by Bengio, Courville, and Vincent.
14	Apr 25	Video, Notes, Slides
	Apr 27	Video, Notes, Slides
	May 06	Final exam - 7-10pm SC 181/183

CS68 - BioinformaticsSpring 2017

Announcements

Schedule

Introduction to Bioinformatics & Molecular Biology

Pairwise Sequence Alignment - Detecting Homology

Multiple Sequence Alignment and Phylogenetic Trees

Functional Genomics and Clustering Algorithms

Supplementary

Supervised Machine Learning

Supervised Machine Learning

Probabilistic Sequence Models - Markov Models

Hidden Markov Models and applications

Deep Learning

Supplementary

CS68 - Bioinformatics
Spring 2017