270200 PR Multiomics Data Science (2024S)
Continuous assessment of course work
Labels
MIXED
jeden Do. von 12:15-14:15 im Seminarraum 4
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).
- Registration is open from Sa 03.02.2024 08:00 to Mo 26.02.2024 23:59
- Registration is open from We 28.02.2024 13:00 to Mo 04.03.2024 23:59
- Deregistration possible until Mo 04.03.2024 23:59
Details
max. 15 participants
Language: German
Lecturers
Classes (iCal) - next class is marked with N
Scheduling upon discussion in the pre-talk.
Monday
04.03.
10:30 - 16:30
Seminarraum 4 Institut Physikalische Chemie HP Währinger Straße 42
Monday
11.03.
10:30 - 12:30
Seminarraum 4 Institut Physikalische Chemie HP Währinger Straße 42
Monday
18.03.
10:30 - 12:30
Seminarraum 4 Institut Physikalische Chemie HP Währinger Straße 42
Monday
08.04.
10:30 - 12:30
Seminarraum 4 Institut Physikalische Chemie HP Währinger Straße 42
Monday
15.04.
10:30 - 12:30
Seminarraum 4 Institut Physikalische Chemie HP Währinger Straße 42
Monday
22.04.
10:30 - 12:30
Seminarraum 4 Institut Physikalische Chemie HP Währinger Straße 42
Monday
29.04.
10:30 - 12:30
Seminarraum 4 Institut Physikalische Chemie HP Währinger Straße 42
N
Monday
06.05.
10:30 - 12:30
Seminarraum 4 Institut Physikalische Chemie HP Währinger Straße 42
Monday
13.05.
10:30 - 12:30
Seminarraum 4 Institut Physikalische Chemie HP Währinger Straße 42
Monday
27.05.
10:30 - 12:30
Seminarraum 4 Institut Physikalische Chemie HP Währinger Straße 42
Monday
03.06.
10:30 - 12:30
Seminarraum 4 Institut Physikalische Chemie HP Währinger Straße 42
Monday
10.06.
10:30 - 12:30
Seminarraum 4 Institut Physikalische Chemie HP Währinger Straße 42
Monday
17.06.
10:30 - 12:30
Seminarraum 4 Institut Physikalische Chemie HP Währinger Straße 42
Monday
24.06.
10:30 - 12:30
Seminarraum 4 Institut Physikalische Chemie HP Währinger Straße 42
Information
Aims, contents and method of the course
Assessment and permitted materials
Part 1 - Multiomics Data Science with Python
In the practical part of the course, students are presented with practical tasks that are completed on site and then discussed with the internship supervisor.Part 2 - Multiomics Data Science with common software programs
Performance is assessed during the internship (interest, cooperation), as well as on the basis of the report submitted and the knowledge acquired (assessed in a final discussion).Grading is based on a points system resulting from the exercise, the students' interest and a short discussion with the supervisors.
In the practical part of the course, students are presented with practical tasks that are completed on site and then discussed with the internship supervisor.Part 2 - Multiomics Data Science with common software programs
Performance is assessed during the internship (interest, cooperation), as well as on the basis of the report submitted and the knowledge acquired (assessed in a final discussion).Grading is based on a points system resulting from the exercise, the students' interest and a short discussion with the supervisors.
Minimum requirements and assessment criteria
Each partial performance (completion of internship tasks, participation/interest, minutes & final discussion) must be completed in order to successfully complete the course.
Examination topics
Theoretical and practical exercises
Reading list
Python for Chemistry: ISBN: 978-93-5551-797-5
Simultaneous Metabolite, Protein, Lipid Extraction (SIMPLEX): A Combinatorial Multimolecular Omics Approach for Systems Biology https://doi.org/10.1074/mcp.M115.053702
Critical shifts in lipid metabolism promote megakaryocyte differentiation and proplatelet formation https://doi.org/10.1038/s44161-023-00325-8
Multiomics of synaptic junctions reveals altered lipid metabolism and signaling following environmental enrichment https://doi.org/10.1016/j.celrep.2021.109797
"Multi-OMICS: a critical technical perspective on integrative lipidomics approaches" https://doi.org/10.1016/j.bbalip.2017.02.003
Simultaneous Metabolite, Protein, Lipid Extraction (SIMPLEX): A Combinatorial Multimolecular Omics Approach for Systems Biology https://doi.org/10.1074/mcp.M115.053702
Critical shifts in lipid metabolism promote megakaryocyte differentiation and proplatelet formation https://doi.org/10.1038/s44161-023-00325-8
Multiomics of synaptic junctions reveals altered lipid metabolism and signaling following environmental enrichment https://doi.org/10.1016/j.celrep.2021.109797
"Multi-OMICS: a critical technical perspective on integrative lipidomics approaches" https://doi.org/10.1016/j.bbalip.2017.02.003
Association in the course directory
CH-SAS-06
Last modified: Mo 04.03.2024 10:47
Datasets obtained with high-throughput methods cannot be manually analyzed due to the large volume of data. The necessary care in data interpretation must, therefore, be partly delegated to software packages. In fact, many processing steps exist between data acquisition and analysis. A focus of this first part of the course is on introducing the most common programs to support the processing of data from proteomics, transcriptomics, and lipidomics. Each step of data processing, as well as potential optimization of algorithms and required settings, will be analyzed and tested. Another focus is on the use of Python for interpreting these datasets based on biochemical or biomedical criteria.Part 2 - Multiomics Data Science Introduction with Python
Basic topics in the data analysis of multiomics data are covered, including regressions, principal component analyses, clustering, time series analyses, classifications, statistical testing including enrichment analyses. The course begins with an introduction to Python for the usage of the mentioned analysis methods.Part 3 - Data Integration at the Multiomics levelIntegration of data in separated and combined manner to truely integrate omics data in a pathway and data driven fashion.