Algorithms for Sequence Analysis

Algorithms for Sequence Analysis 2017 - Tobias Marschall & Marcel Schulz

General info

  • Spezialvorlesung (2+1) with exercises
  • Lecture : Wednesday 10:15-11:45, room 007, Campus E2.1 (CBI)
  • Exercise: biweekly, data and time to be determined.
  • You get 5 credit points
  • 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. Handling the large amounts of sequence data produced by todays DNA sequencing machines is particularly challenging. 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 transform and the FM index. These algorithms are introduced in the context of modern software packages routinely employed for analysis of large DNA sequencing datasets.

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