ΗΥ-590.72

Introduction to Bioinformatics for Computer Scientists

Μεταπτυχιακό

Course Description
 
First, some basic terms and mechanisms of molecular biology are introduced. Algorithms and models from the areas of sequence analysis (sequence alignment, dynamic programming, sequence assembly), population genetics (major evolutionary forces, basic models of population evolution), and discrete as well as numerical algorithms for calculating molecular phylogenetic trees (parsimony, likelihood, Bayesian inference, Markov Chain Monte Carlo methods) are then discussed.
Furthermore, discrete operations on trees are introduced (topological distances between trees, consensus tree algorithms). An important focus in the presentation of all these subject areas will also be on the practical parallelization and optimization of the respective operations.
 
Goals
 
Students attain a comprehensive knowledge of the standard methods, algorithms, theoretical foundations and open problems in the field of sequence-based bioinformatics (biological foundations, sequence assembly, pairwise sequence alignment, multiple sequence alignment, phylogenetic tree inference under parsimony, likelihood, and Bayesian models, basics of population genetics). Students can classify and evaluate algorithms and problems.

Course Setup

The Master level course on “Introduction to Bioinformatics for Computer Scientists” deviates substantially from the standard course schemes at KIT (Karlsruhe Institute of Technology) and UoC (University of Crete) as your lecturer (Prof. Alexandros (Alexis) Stamatakis) is currently setting up a second research lab in Crete while maintaining his lab and position in Germany.

The course will be taught simultaneously at both Universities. Live lectures will either take place at UoC or at KIT (exact schedule for live lectures to be determined) and be streamed via Zoom to the respective other university. Keep in mind the time difference between Greece and Germany - Greece is one hour ahead!

Further, because winter semester lecture periods between Greece and Germany deviate substantially, the course has been condensed into 9 lectures of three hours each to fit the time period during which the respective winter semesters do overlap.

The exams will take place during the standard exam periods of the respective universities (to be discussed with the KIT students).

As far as your lecturer knows this is the first time a course is being taught in this form at KIT and UoC, so he is really looking forward to this experiment.

KIT Students: Please register properly for the course via the KIT campus system.

KIT & UoC Students: send an Email to Alexandros.Stamatakis@h-its.org to make sure to be added to the course mailing list.

Course material from previous semesters including links to the video lectures on youtube is available on-line; updated slides will be provided shortly before the course (typically on Fridays).
They can also select suitable models and methods for a given problem and justify their choice. Participants are able to design analysis pipelines for biological data analyses.

3

Basic knowledge in the areas of theoretical computer science (algorithms, data structures) and technical computer science (sequential optimization in C or C++, computer architectures, parallel programming, vector processors) is required.

https://cme.h-its.org/exelixis/web/teaching/BioinformaticsModule.html