Entry requirements

Basic knowledge of molecular biology, programming, algebra, mathematical analysis and statistics.

Learning outcomes

To provide an introduction to essential concepts of Bioinformatics, Computational Biology and Systems Biology. To master abstraction and modelling abilities necessary in precise formulation of computational structures and their interpretations in life sciences. To support the computer-based exploratory thinking and experimenting in life sciences.

Upon completing the course, the student should:

• Be fluent in using data structures and algorithms to independently design programs that model basic computational problems in life sciences related to sequence, structure and function of biological entities
• Have substantial knowledge of discrete mathematics issues useful in modelling living systems
• Understand and apply appropriate techniques to deal with complexity of problems and complexity of programs
• Be able to apply this knowledge to independently model fundamental concepts in life sciences such as gene and their product annotation and protein-protein interaction

Content

Introduction to Scheme. Abstraction and modeling principles: recursive procedural abstractions and the processes they create; data structure abstractions such as sequences and trees; mutable data structures, search and greedy algorithms, dynamic programming, Hidden Markov Models. Compund methods appplied to selected biological problems: DNA-mapping and sequencing, gene prediction, local and global alignment as well as genome reorganisation.

Instruction

Lectures, computer exercises and individual tutorial.

Assessment

Written closed-book exam at the end of the course (7 credits). Written and computer exercises (3 credits).