Algorithms for Sequence Analysis

Algorithms for Sequence Analysis 2019 - Tobias Marschall

General info

  • Advanced lecture (computer science) / Spezialvorlesung (Bioinformatics), 4V+2Ü with exercises
  • Lecture : Tuesday 12:15-13:45 + Thursday 10:15-11:45, room 001, Campus E2.1 (CBI)
  • Exercise: weekly, time to be determined in first lecture
  • You get 9 credit points
  • Please note that in previous years, this was a 2V+1Ü lecture (5 credits), therefore the amount of content has almost doubled and the courses are not equivalent
  • Oral exams at the beginning of semester break, re-exams at the end of the break (exact dates tbd)
  • Registration: Please register at the course mailing list if you are interested to join the course, additional information during the course will be announced over the list: register here
  • Successful participation in excercises/assignments required to be eligible to take the exam

Course overview

Sequence information is ubiquitous in many application domains. DNA sequencing data are one example that motivates this lecture, but the focus of this course is on algorithms and concepts that are not specific to bioinformatics. This lecture addresses classic as well as recent advanced algorithms for the analysis of large sequence databases. Topics include: full text search without index; approximate pattern matching; index structures such as suffix trees and suffix arrays, Burrows-Wheeler transformand the FM index; data compression; multiple sequence alignment; and min hashing.

Course material

Course material will be available here: password protected area.


We will mostly make use of the following books during the lecture (all available in the library):
  • Ohlebusch - Bioinformatics Algorithms (more details on the book are available here )
  • Navarro and Raffinot - Flexible Pattern Matching in Strings
  • Mäkinen, Belazzougui, Cunial, Tomescu - Genome-Scale Algorithm Design
  • Gusfield - Algorithms on Strings, Trees, and Sequences