FDD3450 Algorithmic Bioinformatics 6.0 credits

Algorithms for problems such as alignment, phylogeny, sorting by reversals, an introduction to hidden Markov chains.

The student should, on completion of the course, be able to

• account with own words for important computing problems in bioinformatics: pairwise sequence comparisons, multiple alignment, composition of genetic material, phylogeny, hidden Markov models;

• implement the algorithms that are described in the course and describe how they relate to one another;

• teach about the algorithms that are described in the course;

• identify and formalise computational problems in biology;

• apply the basic algorithm design methods, such as as dynamic programming within bioinformatics;

• account for the modelling principles parsimony and Bayesian modelling;

Articles, unless otherwise announced before the start of the course.

If the course is discontinued, students may request to be examined during the following two academic years.

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

Project and home assignments. Presentation of research results.

• All members of a group are responsible for the group's work.
• In any assessment, every student shall honestly disclose any help received and sources used.
• In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.