Universität Wien

300164 UE Advanced bioinformatic analysis of single-cell data (2023S)

5.00 ECTS (3.00 SWS), SPL 30 - Biologie
Prüfungsimmanente Lehrveranstaltung
VOR-ORT
Moodle

An/Abmeldung

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

Details

max. 8 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

  • Montag 06.03. 12:00 - 13:30 Seminarraum 4.1, Biologie Djerassiplatz 1, 4.125, Ebene 4 (Vorbesprechung)
  • Montag 05.06. 08:00 - 14:00 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
  • Dienstag 06.06. 08:00 - 14:00 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
  • Mittwoch 07.06. 09:45 - 13:00 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
  • Freitag 09.06. 09:45 - 14:00 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
  • Montag 12.06. 08:00 - 14:00 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
  • Dienstag 13.06. 08:00 - 14:00 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
  • Mittwoch 14.06. 09:45 - 14:00 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
  • Donnerstag 15.06. 08:00 - 14:00 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
  • Freitag 16.06. 09:45 - 14:00 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
  • Montag 19.06. 08:00 - 14:00 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
  • Mittwoch 21.06. 09:45 - 13:00 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
  • Donnerstag 22.06. 09:45 - 14:00 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1
  • Montag 26.06. 08:00 - 14:00 Seminarraum 1.1 PC, Biologie Djerassiplatz 1, 1.003, Ebene 1

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

Single-cell RNA-sequencing has significantly advanced our understanding of biological systems. It has highlighted unexpected transcriptional heterogeneity in cell populations that were thought to be uniform, discovered hitherto unknown rare cell types, and allowed us to predict cell fates in differentiation. Extracting biological meaning from the sequencing data requires involved in-silico analysis.

This course will use publicly available datasets to attack advanced topics in single-cell RNA-seq analysis, such as actionable clustering, dataset integration, cross-species comparison, and advanced visualisation.

Art der Leistungskontrolle und erlaubte Hilfsmittel

Doesn’t require any previous knowledge in programming or single-cell transcriptomics analysis, though it is strongly recommended. Basic knowledge of molecular biology and a general interest in the field is expected from the students. Knowledge in mathematics and statistics is welcome.

Active participation in the exercises and discussions during the course is required. For final evaluation, students will be asked to repeat the analysis steps on previously unseen data (open book). A short report including the code will be turned in and evaluated. The grade will be determined to 50% by participation, 20% by presentations during the course, and 30% by the final evaluation. For a passing grade all three partial evaluations must be at least passing.

Mindestanforderungen und Beurteilungsmaßstab

Prüfungsstoff

Literatur

Zuordnung im Vorlesungsverzeichnis

MZO W3, MZO4, MBO 7, MAN 3, MEC-9, MZO2, MES5

Letzte Änderung: Fr 02.06.2023 12:08