1. Introduction - Algorithms in Bioinformatics

2 Bioinformatics I, WS’09-10, D. Huson, November 26, 2009
1.3 Course notes and assignments
When possible, course notes (“the script”) will be handed out at the beginning of each lecture. The
lecture notes will also be made available on the course website.
Assignment sheets will usually be handed out and published on the course web-site on Mondays.
Assignments are due a week later. Solutions should be sent to the tutor by email or handed in before
the beginning of the lecture.
1.4 Contents of the lecture
Bioinformatics I: Sequences and machine learning
Bioinformatics II: Structures and systems biology
1.4.1 Overview Bioinformatics I
• Builds on “Grundlagen der Bioinformatik”
• Mandatory lecture for Msc. bioinformatics students
• Focuses on algorithms for the analysis of biological primary sequences
• Algorithms: dynamic programming, heuristics, machine learning
1.4.2 Textbooks
Introduction to Computational Biology by Michael Waterman
Introduction to Computational Biology by Setubal / Maidanis
Biological sequence analysis by Durbin, Eddy, Krogh and Mitchison
Bioinformatics - The Machine Learning Approach by Pierre Baldi and Soren Brunak
1.5 Summary of Grundlagen-der-Bioinformatik lecture
• Pairwise alignments (Scoring matrices, NW, SW)
• Blast
• Multiple alignments (SP score, star, progressive)
• Phylogeny (UPGMA, NJ, Maximum Parsimony)
• HMMS (CpG, Viterbi, supervised training)
• gene finding (ORF prediction in procaryotes, GenScan)
• RNA structures (Nussinov, Zuker)
• Protein secondary structures (classification, Chou-Fasman, SSP)
• Protein tertiary structures (classification, threading, de novo, comparison)