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: propositional logic, combinatorics, graphs and automata.
• 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 phylogeny and evolution, transcriptional and other networks, gene and their product annotation and protein-protein interaction.

Content

The first block of lectures and computer exercises is devoted to learning abstraction and modelling principles: recursive procedure abstractions and the processes they generate; building abstractions with hierarchical data such as sequences and trees; mutable data structures, queues and arrays, interfaces as streams.

The second block is focused on introducing advanced concepts and applying them in designing programs for a variety of biological problems. These will be selected from the following issues: mapping and sequencing DNA, comparing sequences, predicting genes and indentifying proteins, genome rearrangements, molecular evolution.

The third and final block is devoted to basic systems biology concepts such as building simple network models and ontologies.

Instruction

Lectures and lab-based computer exercises.

Assessment

Written exam at the end of the course - 7 credits. Successful (pass/fail) completion of 66% of the problem sets - 3 credits.