ETH - BSSE - CBG Bioinformatics

Our paper Reliable detection of subclonal
single-nucleotide variants in tumor cell populations appeared in Nature Communications today (see also ETH Life). In this work, we present the deepSNV algorithm and demonstrate its capability to detect subclonal mutations present in only 1/10,000 cells.

Gerstung et al. (2012) Nat Commun 3:811. DOI: 10.1038/ncomms1814.

Abstract	The course introduces concepts of bioinformatics starting from first principles: DNA sequence alignment, phylogenetic tree inference, genome annotation, protein structure and function prediction. Key methods and algorithms are covered, including dynamic programming, Markov and Hidden Markov models, and molecular dynamics simulations. Practical applications and limitations are discussed.
Objective	The course aims at introducing the fundamental concepts and methods of bioinformatics. Emphasis is given to a deep understanding of the methods' foundations and limitations to enable critical evaluations and applications of bioinformatics tools in areas such as biotechnology and systems biology.
Content	Lecture topics: (1) Background: DNA, proteins, databases; (2-4) Sequence alignments, dynamic programming; (5-7) Evolutionary processes, Markov models, phylogenetic trees; (8-9) Genome characteristics, Hidden Markov models, genome annotation; (10-12) Protein structure and function, molecular modeling; (13) Outlook: genomics and proteomics.
Literature	Marketa Zvelebil, Jeremy O. Baum. Understanding Bioinformatics. Garland Science, 2008. http://www.garlandscience.co.uk/textbooks/0815340249.asp

Course Details

Number and title: 626-002-00L Bioinformatics

	Date	Room
Lecture	Tuesday, 13-15h	BSA E 46
Tutorial	Tuesday, 15-16h	BSA E 46

All lectures will be given in English and are accompanied
by a 1h tutorial session. To each tutorial corresponds an assignment that will be given on the same day. The assignments imperatively have to be handed by the following Monday before 9a.m. The latter will be corrected and discussed on the same day. The assignments can be returned either electronically to
Pejman.Mohammadi(-at-)bsse.ethz.ch, or as a hardcopy to Pejman Mohammadi, D-BSSE, Room 7.48. A 15 Min oral exam for each student will take place at the end of the semester. The assignments will help a lot in learning the material, but not mandatory (no testate).

	Date	Title	Lecture	Assignment	Tutorial
1	Sep 22	MATLAB Tutorial	Matlab Tutorial
2	Sep 28	Introduction/MATLAB	Introduction		DBs+Matlab
3	Oct 5	Producing and Analyzing Sequence Alignments	Lecture 01	Assignment1	Basics of Probabilities and Statistics
4	Oct 12	Pairwise Sequence Alignment and Database Searching	Lecture 02	Assignment2
5	Oct 19	Markov Chains and Hidden Markov Models	Lecture 03	Assingment3	Assignment 3 Guidelines
6	Oct 26	Patterns, Profiles, and Multiple Alignments	Lecture 04	Assignment4
7	Nov 2	Recovering Evolutionary History	Lecture 05	Assignment5
8	Nov 9	Building Phylogenetic Trees	Lecture 06	Assignment6
9	Nov 16	Revealing Genome Features	Lecture 07	Assignment7
10	Nov 23	Gene Detection and Genome Annotation	Lecture 08	Assignment8
11	Nov 30	Protein Secondary Structure Prediction	Lecture 09	Assignment9
12	Dec 7	Protein Tertiary Structure Prediction	Lecture 10	Assignment10
13	Dec 14	Systems Biology	Lecture 11	Assignment11
14	Dec 21	Summary and Perspectives	Lecture 12

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