We are the Integrative Transcriptomics research group at the University of Tübingen, based at the Interfaculty Institute for Bioinformatics and Medical Informatics (IBMI) and led by Prof. Dr. Kay Nieselt.
Our research combines algorithm development, machine learning, and interactive visualization to investigate complex biological systems. We develop computational methods and accessible software for the analysis and interpretation of genomic, transcriptomic, and proteomic data, with a particular interest in microbial biology.
Find out more: Research group · Research projects · Software · Publications
- Microbial genomics and pangenomics — Genome variation, comparative genomics, bacterial evolution, and the reconstruction and analysis of ancient and modern genomes.
- Transcriptomics and gene regulation — Differential gene expression, transcription start sites, non-coding RNAs, and prokaryotic transcriptome architecture.
- Multi-omics and visual analytics — Integrative exploration of heterogeneous biological datasets, functional enrichment, molecular networks, and phylogenetic relationships.
- Machine learning for biological data — Protein function prediction, sequence classification, dimensionality reduction, and uncertainty-aware data analysis.
Explore our GitHub repositories for additional projects, source code, and documentation.
We host and maintain TueVis, a centralized platform for discovering and accessing biomedical data visualization tools developed at the Institute for Bioinformatics and Medical Informatics (IBMI) at the University of Tübingen. The platform brings together interactive software solutions across genomics, transcriptomics, proteomics, multi-omics, phylogenomics, and systems biology. By making research-driven visualization tools easily accessible, TueVis supports the exploration, analysis, and interpretation of complex biological datasets.
