Universität Wien

300025 SE Computational methods in microbial ecology (2021S)

3.00 ECTS (2.00 SWS), SPL 30 - Biologie
Prüfungsimmanente Lehrveranstaltung
DIGITAL

An/Abmeldung

Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").

Details

max. 20 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine

The course will be held via distance learning from 13:00 to 16:00 on the following dates:

March 3, 10, 17, 24
April 14,21,28
May 5,12


Information

Ziele, Inhalte und Methode der Lehrveranstaltung

- Mathematical concepts in microbial ecology
- Statistics of high-dimensional data
- Estimating diversity and composition of microbial communities
- Databases and resources in microbial ecology
- DNA sequencing in microbial ecology (amplicon sequencing, shotgun metagenomics, metatranscriptomics)
- Computational pipelines for amplicon sequencing: overview, features, evaluation
- Comparison of microbial communities
- Networks in ecology: correlation vs. interaction

Art der Leistungskontrolle und erlaubte Hilfsmittel

Regular quizzes and homework assignments. Homeworks contribute 75% to the final grade and quizzes contribute 25%. Participants should bring a laptop for in-class exercises. A passing grade is >50% of combined assessments.

Mindestanforderungen und Beurteilungsmaßstab

Minimum requirements: No computer programming knowledge required.

Assessment criteria:
Understanding relevant mathematical and computational methods in microbial ecology. Applying these methods to typical problems in microbial ecology and designing experiments. Performing mathematical and computational experiments using typical software programs. Presenting and interpreting the results of mathematical and computational experiments. Understanding and discussing recent scientific literature.

Prüfungsstoff

This course will consist of theoretical lectures, discussion of selected scientific papers and practical exercises (mainly using the computers of the participants).

Literatur

Will be provided throughout the course on the e-learning platform.

Zuordnung im Vorlesungsverzeichnis

MMEI II-2.2, MMB W-2, MMB W-3,

Letzte Änderung: Mi 05.05.2021 15:49