Universität Wien
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053520 VU Algorithmic bioinformatics (2020S)

6.00 ECTS (4.00 SWS), SPL 5 - Informatik und Wirtschaftsinformatik
Continuous assessment of course work
Moodle

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 25 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

Kickoff-meeting: TUE 03.03.2020 10.00-12.00 Ort: Seminar room Structural Chemistry, Campus Vienna Biocenter 5, 1030 Vienna;
TUE weekly from 03.03.2020 to 30.06.2020 10.00-12.00 Location: STB/Seminar room Structural Chemistry, Campus Vienna Biocenter 5, 1030 Vienna;
FRI weekly from 06.03.2020 to 26.06.2020 9.30-11.30 Location: Seminar room 4, Max Perutz Labs (formerly MFPL), Dr. Bohr-Gasse 9, 1030 Vienna

  • Tuesday 03.03. 10:00 - 12:00 extern (Kickoff Class)
  • Friday 06.03. 09:30 - 11:30 extern
  • Tuesday 10.03. 10:00 - 12:00 extern
  • Friday 13.03. 09:30 - 11:30 extern
  • Tuesday 17.03. 10:00 - 12:00 extern
  • Friday 20.03. 09:30 - 11:30 extern
  • Tuesday 24.03. 10:00 - 12:00 extern
  • Friday 27.03. 09:30 - 11:30 extern
  • Tuesday 31.03. 10:00 - 12:00 extern
  • Friday 03.04. 09:30 - 11:30 extern
  • Tuesday 21.04. 10:00 - 12:00 extern
  • Friday 24.04. 09:30 - 11:30 extern
  • Tuesday 28.04. 10:00 - 12:00 extern
  • Tuesday 05.05. 10:00 - 12:00 extern
  • Friday 08.05. 09:30 - 11:30 extern
  • Tuesday 12.05. 10:00 - 12:00 extern
  • Friday 15.05. 09:30 - 11:30 extern
  • Tuesday 19.05. 10:00 - 12:00 extern
  • Friday 22.05. 09:30 - 11:30 extern
  • Tuesday 26.05. 10:00 - 12:00 extern
  • Friday 29.05. 09:30 - 11:30 extern
  • Friday 05.06. 09:30 - 11:30 extern
  • Tuesday 09.06. 10:00 - 12:00 extern
  • Friday 12.06. 09:30 - 11:30 extern
  • Tuesday 16.06. 10:00 - 12:00 extern
  • Friday 19.06. 09:30 - 11:30 extern
  • Tuesday 23.06. 10:00 - 12:00 extern
  • Friday 26.06. 09:30 - 11:30 extern
  • Tuesday 30.06. 10:00 - 12:00 extern

Information

Aims, contents and method of the course

a. Aims: The students gain fundamental knowledge and understanding of the algorithms used in modern bioinformatics in theory and practice. The students can independently develop, apply and modify existing algorthms.
b. Content: The course aims at giving an overview about the different classes of algorithmic and their application in bioinformatics like randomised algorithms, graph algorithms, brute force algorithms, dynamic programming, combinatorial algorithms, evolutionary tree reconstruction, clustering algorithms, cominatorial pattern matching, hidden Markov modells and methods of computational proteomics.
c. Methods: Lectures, exercises about each lecture topic including programming, exercise discussion including students presenting their solutions.

Assessment and permitted materials

Type of assessment: During the course ecxercises have to be solved and submitted via Moodle. The exercises include implementing algorithms to solve the exercise tasks. In addition all students have to present solutions at the blackboard during the course.

Minimum requirements and assessment criteria

a. Minimum requirements: Attendance during the course, presentation of results, submission of exercises. To pass the course one has to obtain at least 50% of the possible sum of points. The obtained percentage of the points determines the actual grade.
b. Assessment criteria: The following obtained percentages correspond to the following grades:
>=87.5%: grade 1 (very good)
<87.5%: grade 2 (good)
<75.0%: grade 3 (satisfactory)
<62.5%: grade 4 (sufficient)
<50.0%: grade 5 (insufficient)

Examination topics

Relevant is all content of the course, the lectures, the exercises and the exercise discussions.

Reading list

Useful literatur for the course is "Bioinformatics Algorithms: An Active Learning Approach" by Compeau and Pevzner, either the two-volume version from 2015 or the one-volume version from 2018.

Association in the course directory

Module: BIOINF02

Last modified: Mo 07.09.2020 15:20