Algorithm for Sequence Analysis in Bioinformatics

ESCI-BDIB, January 2018

Cedric Notredame


An intermediate level course on algorithms in bioinformatics. We will use it to explain common concepts in sequence analysis, starting from the biological relevance of sequence alignment and making our way through the most commonly used algorithms, including Needleman and Wunsch, Smith and Waterman for pairwise alignments, BLAST for database searches, Nussinov for RNA folding and the progressive multiple alignment. The practicals will be in Python and will involve driving the students through an implementation of these algorithms. The biobliography is given by order of importance.


Practicals will be in python 2.7. They will involve adapting existing scripts rather than programming from scratch. For this reason, students with no practical knowledge of python but with a good grasp of programming languages like Perl, C or JAVA should manage reasonnably well. Students are expected to bring their own lap-top and advised to have a LINUX boot though Virtual MAchine support will be provided.

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1ASABLECTUREPairwise comparisons in an evolutionary contextL
2ASABLECTURESubstitution MAtricesL
3ASABLECTUREIntroduction to Dynamic Programming-1L
4ASABLECTUREIntroduction to Dynamic Programming-2L
5ASABLECTUREBlast AlgorithmL
6ASABLECTUREIntroduction to Multiple Sequence AlignmentL
7ASABLECTUREMultiple Sequence Alignment AlgorithmsL
8ASABLECTURERNA Folding AlgorithmsL
1ASABPRACTICALSParsing Biological FilesP
2ASABPRACTICALSComputing Substitution MatricesP
3ASABPRACTICALSIntroduction to Dynamic Programming 1P
4ASABPRACTICALSIntroduction to Dynamic Programming 2P
5ASABPRACTICALSParsing and manipulating binary treesP
6ASABPRACTICALSImplementing your own multiple sequence alignerP


1. Algorithms: Durbin et al., Biological Sequence Analysis, 1999, Oxford Press

2. Algorithms: Python for Biologists: A complete programming course for beginners, Martin Jones,2013 , Createspace Independent Publishing Platform

3. Evolution: Pathy, Protein Evolution, 2007, Blackwell

This Entire Course Was Automatically Generated Using BED, the Bioinformatics Exercise Database. BED is a freeware available on request Cedric Notredame