Universität Wien

053520 VU Algorithmic bioinformatics (2022S)

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

REMARK: According to the rules of the University, all parts of the VU take place in presence at the moment, as also announced in the (online) initial meeting (Vorbesprechung).

  • Tuesday 01.03. 10:00 - 12:00 Digital (Kickoff Class)
  • Friday 04.03. 09:30 - 11:30 STB/Hörsaal A Campus Vienna Biocenter 5, 1030 Wien
  • Tuesday 08.03. 10:00 - 12:00 STB/Hörsaal A Campus Vienna Biocenter 5, 1030 Wien
  • Tuesday 15.03. 10:00 - 12:00 STB/Hörsaal A Campus Vienna Biocenter 5, 1030 Wien
  • Friday 18.03. 09:30 - 11:30 STB/Hörsaal A Campus Vienna Biocenter 5, 1030 Wien
  • Tuesday 22.03. 10:00 - 12:00 STB/Hörsaal A Campus Vienna Biocenter 5, 1030 Wien
  • Friday 25.03. 09:45 - 11:15 Seminarraum 8, Währinger Straße 29 1.OG
  • Tuesday 29.03. 10:00 - 12:00 STB/Hörsaal A Campus Vienna Biocenter 5, 1030 Wien
  • Friday 01.04. 09:30 - 11:30 STB/Hörsaal A Campus Vienna Biocenter 5, 1030 Wien
  • Tuesday 05.04. 10:00 - 12:00 STB/Hörsaal A Campus Vienna Biocenter 5, 1030 Wien
  • Friday 08.04. 09:45 - 11:15 Seminarraum 8, Währinger Straße 29 1.OG
  • Tuesday 26.04. 10:00 - 12:00 STB/Hörsaal A Campus Vienna Biocenter 5, 1030 Wien
  • Friday 29.04. 09:30 - 11:30 STB/Hörsaal A Campus Vienna Biocenter 5, 1030 Wien
  • Tuesday 03.05. 10:00 - 12:00 STB/Hörsaal A Campus Vienna Biocenter 5, 1030 Wien
  • Friday 06.05. 09:30 - 11:30 STB/Hörsaal A Campus Vienna Biocenter 5, 1030 Wien
  • Tuesday 10.05. 10:00 - 12:00 STB/Hörsaal A Campus Vienna Biocenter 5, 1030 Wien
  • Friday 13.05. 09:30 - 11:30 STB/Hörsaal A Campus Vienna Biocenter 5, 1030 Wien
  • Tuesday 17.05. 10:00 - 12:00 STB/Hörsaal A Campus Vienna Biocenter 5, 1030 Wien
  • Friday 20.05. 09:30 - 11:30 STB/Hörsaal A Campus Vienna Biocenter 5, 1030 Wien
  • Tuesday 24.05. 10:00 - 12:00 STB/Hörsaal A Campus Vienna Biocenter 5, 1030 Wien
  • Friday 27.05. 09:30 - 11:30 STB/Hörsaal A Campus Vienna Biocenter 5, 1030 Wien
  • Tuesday 31.05. 10:00 - 12:00 STB/Hörsaal A Campus Vienna Biocenter 5, 1030 Wien
  • Friday 03.06. 09:30 - 11:30 STB/Hörsaal A Campus Vienna Biocenter 5, 1030 Wien
  • Friday 10.06. 09:45 - 11:15 Seminarraum 8, Währinger Straße 29 1.OG
  • Tuesday 14.06. 10:00 - 12:00 STB/Hörsaal A Campus Vienna Biocenter 5, 1030 Wien
  • Friday 17.06. 09:30 - 11:30 STB/Hörsaal A Campus Vienna Biocenter 5, 1030 Wien
  • Tuesday 21.06. 10:00 - 12:00 STB/Hörsaal A Campus Vienna Biocenter 5, 1030 Wien
  • Friday 24.06. 09:45 - 11:15 Seminarraum 3, Währinger Straße 29 1.UG
  • Tuesday 28.06. 10:00 - 12:00 STB/Hörsaal A Campus Vienna Biocenter 5, 1030 Wien

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.
REMARK: The lectures and exercise discussions will take place in presence, hybrid or in distance learning online, depending on the Corona/COVID-19 restrictions valid during the semester.

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: Th 11.05.2023 11:27