FDD3450 Algorithmic Bioinformatics 6.0 credits

Algoritmisk Bioinformatik

Offering and execution

Course offering missing for current semester as well as for previous and coming semesters

Course information

Content and learning outcomes

Course contents *

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

Intended learning outcomes *

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;

Course Disposition

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Literature and preparations

Specific prerequisites *

No information inserted

Recommended prerequisites

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

Examination and completion

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

Grading scale *

P, F

Examination *

    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.

    Other requirements for final grade *

    Project and home assignments. Presentation of research results.

    Opportunity to complete the requirements via supplementary examination

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    Opportunity to raise an approved grade via renewed examination

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    Ethical approach *

    • 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.

    Further information

    Course web

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    Offered by

    EECS/Computational Science and Technology

    Main field of study *

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    Education cycle *

    Third cycle

    Add-on studies

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    Postgraduate course

    Postgraduate courses at EECS/Computational Science and Technology