Teaching and Collaborative Support

Teaching in Collaborative Research Consortia (CRC / TRR)

We provide specialized bioinformatics training activities across multiple interdisciplinary workshops within various CRC and TRR consortia.

Date	Workshop / Consortium	Duration	Core Topics
October 2024	GB.com Workshop	2 hours	Importing and visualization of count matrices from bulk RNA-seq analysis
May 2024	IMPRS Workshop	1.5 days	Bioinformatics analysis of bulk RNA-seq data
March 2024	IZKF / Life@FAU Graduate Training	1.5 days	Bioinformatics analysis of bulk RNA-seq data
October 2023	IZKF / Life@FAU Graduate Training	1.5 days	Bioinformatics analysis of bulk RNA-seq data
May 2023	GB.com Workshop	1.5 days	Bioinformatics analysis of bulk RNA-seq data
September 2022	ForInter Workshop	1.5 days	Bioinformatics analysis of bulk RNA-seq data
February 2022	CRC1181 Workshop	2 days	Bioinformatics analysis of bulk RNA-seq data; introduction to R; single-cell RNA-seq data analysis

Research Consultation and Support

Bioinformatics Consultation Hours (Sprechstunden)

Individualized guidance on bioinformatics analyses, statistical methods, data visualization, and interpretation of research results.

Topics: Bulk RNA-seq and single-cell RNA-seq data analysis, differential gene expression, statistical analysis, data visualization, interpretation of omics results, and reproducible bioinformatics workflows.

Availability: Every Monday

Target audience: Researchers and members of participating research consortia TRR 417, CASCAID (CRC 1755), DIONE (TRR 369), and GB.Com (KFO 5024).

Responsible contacts: Florin Ratajczak and Alej.

Contact: For consultation requests, please use our Contact page.

Research Data Management for Experimental Omics

Consultation on the planning, organization, documentation, storage, and sharing of experimental omics data throughout the research lifecycle.

Topics: Metadata standards, sample and experimental design documentation, data quality and traceability, reproducible workflows, and FAIR (Findable, Accessible, Interoperable, and Reusable) data principles.

Availability: By arrangement