Algorithms in bioinformatics

Aim

The course gives an introduction to some fundamental concepts and applications of algorithms in bioinformatics. Module A is about Markov models and algorithms in bioinfomatics. We will give the fundamental definitions of higher order Markov chains of fixed and variable lengths and see how they are useful in modelling biological data and answering specific questions (for example in Horizontal Gene Transfer). Algorithms to infer the unknown order and structure of Markov chains will be presented and discussed. A short introduction will be given to Markov Chain Monte Carlo methods in phylogentic analysis.
Module B deals with some combinatorial inference methods that have found applications in molecular biology. In particular, we study Group Testing strategies, the Hitting Set and Vertex Cover problem, and some applications including the design of informative experiments, splice-site detection, reconstruction problems, unraveling protein interaction networks. Other such problems of current interest may be inserted. Besides these specific problems, the module will give an idea of the usefulness of combinatorial thinking in general in biology.
In both modules, after the introductory lectures, guided literature study, discussion and problem solving sessions that test your understanding will be a major part.

Location & Organization

Organizer

FLÄK - The Research School in Pharmaceutical Sciences

Course Director

Peter Damaschke; Devdatt Dubhashi

Location / venue

Chalmers and Göteborg University

Timing & Workload

Duration 1 week
ECTS points 3
Frequency Annual
 

Examination yes

Criteria

Is the course taught in English? yes
Is documentation available? (book, syllabus)? yes
Is the course open for external researchers? yes

More Information

http://www.biol.lu.se/cellorgbiol/postgrad/courses/course_25.html