Lehr- und Forschungseinheit Bioinformatik



NEAP24: Understanding metabolic diseases

We want to understand metabolic disease progression.

Nowadays the creation of multi-modal data sets is becoming increasingly simple: the relevant techniques (e.g. 10X Genomics scRNA-seq, Visium spatial RNA-seq, etc.) are mostly commercially available, and thus easy to use by a wetlab. However, shedding light into the stack of data is extremely complicated.

Student Group 1
In the NEAP summer of 2023 a group of highly dedicated students created a multi-modal data set for atherosclerosis. This year, we want to extend this data set to cardio-vascular diseases (CVDs) in general and create a whole single-cell atlas for CVDs using mainly multi-modal data sets from diseased and normal conditions. Integrative tools, such as SCENIC+, MetaCells or scKINETICS (and others), shall be applied to gain relevant insight into the different diseases.

Student Group 2
Moreover, researchers aim to include different kinds of measurements: transcriptomics, proteomics and metabolomics. While gene expression and protein abundance are meant to be well correlated, the inclusion of metabolomics is a new topic when it comes to analyses. We thus want to explore existing models and shape new analysis methods for analysing multi-modal datasets by combining transcriptomics, proteomics and metabolomics. The overall goal will be the development of a new method which predicts active metabolites and metabolic programs from (single cell) gene expression data only. This is not only an interesting scientific question, but it has been shown that metabolites releases from dying cells are used as "good-bye" signals to actively modulate outcomes in tissues. Thus, understanding which reaction is induced by which metabolite is of high relevance for understanding complex human diseases, such as cardio-vascular diseases.

By combining both projects we want to answer (some of) the following questions: Which CVDs are similar, which ones are very different? In which pathways or gene clusters can these CVDs be differentiated? Which genes correspond with which proteins and which metabolic compounds? Is it possible to describe the different CVDs in terms of different metabolic compositions?

This course is very much research oriented. Experience with sc/sn/spatialRNA-seq analyses is welcome, but not required beforehands.
This practical lab may have some joint presentations with the practical course by Prof. Zimmer.


BetreuerCourse instructor

Allgemeine InformationenGeneral Information
  1. Credits und ArbeitsumfangCredits and work load: 12 ECTS / 10 SWS (10P/Block) = 360 working hours
  2. Meetings: Monday 14-16hc.t.
  3. Amalienstr. 17, Seminarraum A406 Amalienstr. 17, Seminar room A406

LernzieleAims and Learning Goals
Ziele und Lernziele:
Die zu entwickelnden Methoden und Routinen bauen auf verfügbaren hochmodernen Tools für eine effiziente Analyse und komfortable Visualisierung der Ergebnisse unter Verwendung moderner Python und R Programmierumgebungen und -pakete aufbauen. Die Robustheit und Reproduzierbarkeit der Ergebnisse ist eine wichtige Voraussetzung für alle Ihre Implementierungen.
Aims and Learning Goals:
The developed pipeline will build on available state-of-the-art tools for efficient analysis and comfortable visualization of results using modern python and R programming environments and packages. Robustness and reproducibility of results is an important requirement for all implementations.

Bachelor Bioinformatik, insbesondere erfolgreicher Abschluss des GoBi-Moduls. Gute Programmierkenntnisse (Java, Python, Dash, R, Shiny). Interesse an Datenvisualisierung und komplexen menschlichen Krankheiten. Das Praktikum ist sehr forschungsnah. Erfahrung in der Analyse von sc/sn/spatialRNA-seq Data ist willkommen, aber keine Voraussetzung.
Bachelor Bioinformatics, in particular successful completion of the GoBi module. Good programming skills (java and/or python). Interest in data visualization and complex human diseases. This practical is very much research oriented. Experience with sc/sn/spatialRNA-seq analyses is welcome, but not required beforehands.

Struktur/Zeitablauf des PraktikumsStructure/Schedule

Regular synchronization points are planned to take place in-persona in Amalienstr. 17 .
Meetings in-persona will (probably) take place Monday 14:00-16:00 .
The practical can be organized with or without consecutive/block working time.

This practical course will be held with regular joint meetings with the practical organized by Prof. Zimmer. These meetings are intended such that the course topic is presented to and discussed with a broader audience.

Regelmäßige Treffen sind Montags, 14-16 Uhr geplant. Das Praktikum kann sowohl konsekutiv abgehalten werden, als auch mit Blockphase in der vorlesungsfreien Zeit.

Es wird regelmäßige gemeinsame Treffen mit dem Praktikum von Prof. Zimmer geben. Dies soll den Austausch zwischen allen Praktikumsgruppen fördern, und dient dazu, die (Zwischen-)Ergebnisse (mit) einer breiteren Zuhörerschaft zu präsentieren und zu diskutieren.

  • Grundstudium Bioinformatik (Bachelor oder Diplom)Bachelor Bioinformatics
  • Programmierpraktikum BioinformatikBioinformatics programming course
  • Praktikum Genomorientierte BioinformatikPractical Genome-oriented bioinformatics
  • Gute Programmierkenntnisse (Bachelor Level)Good programming skills (bachelor level)


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