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Quick Start by Role

PhD students & Postdocs — Start with Data Types and Use Cases. For reproducibility, see Workflow Managers and Containers.

PIs & Group Leaders — Review Metadata standards for FAIR compliance and Repositories for data sharing requirements. See also Data Management Plans.

Data Stewards — Use the full navigation below. Key cross-references: File Formats, Git, Infrastructure.

What is Bioinformatics?

Bioinformatics is an interdisciplinary field that combines biology, computer science, mathematics, and statistics to analyze and interpret biological data. At its core, bioinformatics develops methods and software tools to understand complex biological systems, particularly at the molecular level.

The Need for Bioinformatics​

Modern biological research generates massive amounts of data. A single DNA sequencing experiment can produce billions of nucleotide sequences, and analyzing protein structures, gene expression patterns, or metabolic pathways requires sophisticated computational approaches. Bioinformatics provides the framework to:

  • Store and organize large-scale biological datasets
  • Analyze sequences (DNA, RNA, proteins)
  • Predict biological structures and functions
  • Model biological systems and their interactions
  • Integrate multi-omics data for comprehensive understanding

Key Application Areas​

Genomics​

The study of complete genomes, including genome sequencing, assembly, annotation, and comparative genomics to understand genetic variation and evolution.

Transcriptomics​

Analyzing gene expression patterns through RNA sequencing to understand which genes are active under different conditions.

Proteomics​

Studying the complete set of proteins in an organism, including protein structure prediction, post-translational modifications, and protein-protein interactions.

Metabolomics​

Characterizing metabolic pathways and small molecule profiles to understand cellular metabolism.

Systems Biology​

Integrating multiple types of biological data to model and predict the behavior of complex biological systems.

Structural Bioinformatics​

Predicting and analyzing three-dimensional structures of biological macromolecules.

Bioinformatics at TUM​

The Technical University of Munich is home to world-leading research groups in bioinformatics and computational biology. Below is an overview of chairs and research groups working in this field:

Core Bioinformatics and Computational Biology​

Should you find your bioinformatics group missing from the list, please contact us!

Computational Molecular Medicine​

  • Professor: Julien Gagneur
  • Focus: Statistical genomics, regulatory genomics, RNA biology, precision medicine
  • Website: Gagneur Lab

Data Science in Systems Biology​

  • Professor: Markus List
  • Focus: drug repurposing, network bioinformatics, microbiome research
  • Website: DaiSyBio

Computational Biology​

  • Professor: Burkhard Rost
  • Focus: Protein structure and function prediction, machine learning for biological sequences
  • Website: Rostlab

Genome-Oriented Bioinformatics​

  • Professor: Dmitrij Frishman
  • Focus: Genome annotation, functional genomics, systems biology
  • Website: Frishman Group

Mathematical Modeling of Biological Systems​

  • Professor: Fabian Theis
  • Focus: Single-cell genomics, machine learning, systems medicine
  • Website: Professor Website

Bioinformatics (Straubing)​

  • Professor: Dominik Grimm
  • Focus: machine learning, genotype-phenotype relationships, sustainable agriculture
  • Website: GrimmLab

Proteomics and Structural Biology​

Proteomics and Bioanalytics​

  • Professor: Bernhard Küster
  • Focus: Mass spectrometry-based proteomics, cancer research, drug discovery
  • Website: Küster Lab

Computational Mass Spectrometry​

Biomolecular NMR Spectroscopy​

  • Professor: Michael Sattler
  • Focus: Protein structure determination, RNA-protein interactions
  • Website: Sattler Lab

Translational Microbiome Data Integration​

Microbiology and Metagenomics​

Environmental Microbiology​

Biophysics and Quantitative Biology​

Cellular Biophysics​

  • Professor: Andreas Bausch
  • Focus: Single-molecule biophysics, cell-cell-interactions, organoids
  • Website: Bausch Lab

Neurobiological Engineering​

  • Professor: Gil Westmeyer
  • Focus: Molecular imaging, biosensors, cellular dynamics
  • Website: Westmeyer Lab

Plant Sciences and Agricultural Genomics​

Plant Breeding​

  • Professor: Chris-Carolin Schön
  • Focus: Genomic selection, quantitative genetics, crop improvement
  • Website: TUM Plant Breeding

Plant Systems Biology​

  • Professor: Claus Schwechheimer
  • Focus: Plant hormone signaling, systems approaches in plant biology
  • Website: Plant Systems Biology

Computational Plant Biology​

  • Professor: Nadia Kamal
  • Focus: Computational genomics, plant evolution, bioinformatics methods development
  • Website: Computational Plant Biology

Medical and Clinical Bioinformatics​

AI and Informatics in Medicine​

Molecular Oncology and Functional Genomics​

Infrastructure and Support​

TUM researchers have access to:

  • Leibniz Supercomputing Centre (LRZ) - High-performance computing and specialized bioinformatics resources
  • Core Facilities - State-of-the-art equipment for genomics, proteomics, and imaging
  • Munich Data Science Institute (MDSI) - Training, workshops, and collaboration opportunities
  • TUM ForTe - Support for ensuring funding, training and education programs
  • TUM Institute of Life Long Learning - Support for learning skills and for professional development

Training and Education​

TUM offers comprehensive bioinformatics education:

  • BSc & MSc Bioinformatics - Joint program between TUM and LMU Munich
  • Integrated courses - Available through various life science programs
  • Workshops and seminars - Hosted by MDSI and individual chairs

Getting Started​

If you're new to bioinformatics at TUM:

  1. Explore our resources - Check out the Data Types and Use Cases
  2. Access infrastructure - Apply for computing resources at LRZ
  3. Get support - Contact researchdata@tum.de for data management guidance

Collaboration Opportunities​

Many TUM bioinformatics groups welcome collaborations. If you have biological data requiring computational analysis or are developing new methods, reach out to any relevant research groups.

This list is continually updated. If you know of additional bioinformatics or computational biology groups at TUM that should be included, please contact researchdata@tum.de.