300164 UE Advanced bioinformatic analysis of single-cell data (2024S)
Prüfungsimmanente Lehrveranstaltung
Labels
VOR-ORT
An/Abmeldung
Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").
- Anmeldung von Do 08.02.2024 14:00 bis Do 22.02.2024 18:00
- Abmeldung bis Fr 15.03.2024 18:00
Details
max. 8 Teilnehmer*innen
Sprache: Englisch
Lehrende
Termine (iCal) - nächster Termin ist mit N markiert
The first course date will also serve as the date for the preliminary discussion (Vorbesprechung).
Montag
04.03.
09:45 - 14:45
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
Dienstag
05.03.
09:45 - 14:45
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
Mittwoch
06.03.
09:45 - 14:45
Seminarraum 1.6, Biologie Djerassiplatz 1, 1.011, Ebene 1
Donnerstag
07.03.
09:45 - 14:45
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
Freitag
08.03.
09:45 - 14:45
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
Montag
11.03.
09:45 - 14:45
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
Donnerstag
14.03.
09:45 - 14:45
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
Freitag
15.03.
09:45 - 14:45
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
Montag
18.03.
09:45 - 14:45
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
Dienstag
19.03.
09:45 - 14:45
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
Mittwoch
20.03.
09:45 - 14:45
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
Donnerstag
21.03.
09:45 - 14:45
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
Freitag
22.03.
09:45 - 14:45
Seminarraum 1.8, Biologie Djerassiplatz 1, 1.007, Ebene 1
Mittwoch
03.04.
08:00 - 14:00
Seminarraum 1.2, Biologie Djerassiplatz 1, 1.004, Ebene 1
Donnerstag
04.04.
08:00 - 14:00
Seminarraum 1.2, Biologie Djerassiplatz 1, 1.004, 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 cell type theory, actionable clustering, dataset integration, cross-species comparison, and advanced visualisation. Recent literature will be used as reference material and discussed in class.
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.Previous students have indicated that the following courses have been helpful:- 300106 UE Analyses of single cell transcriptome data
- 300357 UE Mathematical Basics for Quantitative BiologActive 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.
- 300357 UE Mathematical Basics for Quantitative BiologActive 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
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.
Prüfungsstoff
Literatur
Previous students have been asked to provide feedback and advice for future course attendees. Here are some quotes:- "Best advice for me would be: make sure you have time! Mainly just to make sure to have time after class to review the concepts and codes gone through the day because with this block course format everything piles up pretty quickly."
- "Be prepared for the theory and the philosophy behind the different steps [...]"
- "Be sure to have at least some basic knowledge of coding as it will help very much."
- "Take your time to really understand the fundamental concepts & take your time playing around with the homework."
- "Be prepared for the theory and the philosophy behind the different steps [...]"
- "Be sure to have at least some basic knowledge of coding as it will help very much."
- "Take your time to really understand the fundamental concepts & take your time playing around with the homework."
Zuordnung im Vorlesungsverzeichnis
MZO W3, MZO4, MBO 7, MEC-9, MZO2, MES5
Letzte Änderung: Di 02.04.2024 11:46