Algorithms and computer models for a molecular-level understanding of human health and disease
We have accumulated an enormous amount of clinical and genetic data about human diseases like cancer. However, clinicians cannot interpret on their own this avalanche of data, and the patients are not making an actual profit from all this knowledge
At the Systems Tumour Immunology Laboratory, we develop computer algorithms that help clinicians to make quicker diagnostics and better decisions about cancer therapy. We utilize bioinformatics algorithms, machine learning, and computational models to integrate clinical and molecular data. Our aim is to generate a mechanistic understanding of human health and disease
At the Systems Tumour Immunology Laboratory, we develop computer algorithms that help clinicians to make quicker diagnostics and better decisions about cancer therapy. We utilize bioinformatics algorithms, machine learning, and computational models to integrate clinical and molecular data. Our aim is to generate a mechanistic understanding of human health and disease
Melanoma in the (micro)scope: the testbed for modern cancer immunotherapies
Immunotherapies are a new family of effective cancer therapies that potentiate the natural response of the immune system against cancers. However, a significant fraction of patient does not respond to immunotherapies, while others suffer immune-related side effects in vital body organs
We think that metastatic melanoma is the ideal testbed to improve existing immunotherapies and design new ones. In this process, -omics era profiling of patient samples, bioinformatics algorithms, and computational models will play a pivotal role
We think that metastatic melanoma is the ideal testbed to improve existing immunotherapies and design new ones. In this process, -omics era profiling of patient samples, bioinformatics algorithms, and computational models will play a pivotal role
Key facts about us
- A group of biologists, computer scientists, and clinicians led by a physicist
- DNA-Seq, RNA-Seq, miRNA-Seq, and Nanopore-Seq data analysis
- Expertise in bioinformatics, network biology, and systems biology
- Multi-criteria decision algorithms applied to biomedicine
- German- and EU-level projects in cancer diagnostics and immunotherapy
- Partners in Spain, Finland, Israel, Portugal, Netherlands, Bulgaria, and Australia
- We teach network and systems biology and supervise bachelor and master thesis
- We are part of the Department Dermatology, University Hospital Erlangen and Friedrich-Alexander-University Erlangen-Nürnberg
- We are integrated in the German Centre for Immunotherapy and the Comprehensive Cancer Centre Erlangen
Selected recent publications
Gene network-based and ensemble modeling-based selection of tumor-associated antigens with a predicted low risk of tissue damage for targeted immunotherapy (2024)
Integration of transcriptomics data into agent-based models of solid tumor metastasis (2023)
Melanoma 2.0. Skin cancer as a paradigm for diagnostic technologies, computational modelling and artificial intelligence (2022)
A disease network-based deep learning approach for characterizing melanoma (2021)
Network- and systems-based re-engineering of dendritic cells with non-coding RNAs for cancer immunotherapy (2021)
See our entire list of publications here
Integration of transcriptomics data into agent-based models of solid tumor metastasis (2023)
Melanoma 2.0. Skin cancer as a paradigm for diagnostic technologies, computational modelling and artificial intelligence (2022)
A disease network-based deep learning approach for characterizing melanoma (2021)
Network- and systems-based re-engineering of dendritic cells with non-coding RNAs for cancer immunotherapy (2021)
See our entire list of publications here
|
Our tools
Vcells.net: Comprehensive networks Curatopes.com: Therapeutic Tumor Epitopes Synmirapy.net: Cancer miRNAs Spotlight We are in X Researchgate Latest news
|
|
