The Institute for Computational Cancer Biology (ICCB) at the University Hospital Cologne was founded in 2022 to advance cancer research through computational methods and to train and educate the next generation of computational cancer scientists.
We are part of the Cancer Research Center Cologne Essen (CCCE) funded by the Ministry of Culture and Science of the State of North Rhine-Westphalia.
Our mission is to develop bespoke statistical methods, machine learning approaches, algorithms and models to decipher tumour heterogeneity and cancer evolution and improve our understanding of the wealth of genomic, transcriptomic, epigenomic and imaging data collected in cancer research.
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|▶ Research spotlights
|▶ Work with us
As part of a multidisciplinary team led by the Borchmann Lab the Schwarzlab implemented a publicly available shiny application for MOP-C (Molecular prognostic index for central nervous system lymphomas).
MOP-C provides risk assessment for central nervous system lymphomas based on clinical risk factors, radiographic response and peripheral residual disease measured by circulating tumor DNA (Heger et al. 2023, Blood).
By integrating these clinical and molecular features MOP-C was proven to be highly predictive of outcomes a CNSL cohort with a failure-free survival hazard ratio (HR) per risk group of 6.60.
The Schwarzlab at the ICCB has multiple job openings for PhD students, Postdoctoral Fellows and a Scientific Programmer in multiple national and international projects working on chromosomal instability, copy-number evolution and algorithms for tumour heterogeneity.
We are glad that the Lehmann Lab has joined the ICCB as an associated group.
The Lehmann Lab is interested in the development of approaches that support the molecular characterisation of patient cohorts and in approaches for data integration to gain insights into disease mechanisms. Welcome on board!
Schwarz Lab - Cologne/Berlin
Cancer Genomics and Evolution
Algorithms for inferring and simulating cancer evolution and for understanding tumour heterogeneity, with a special focus on chromosomal instability and somatic copy-number alterations.
Lehmann Lab - Aachen
Molecular Signatures and Data Integration
Approaches that support the molecular characterisation of patient cohorts and reveal disease mechanisms through integration of diverse types of molecular data.
University Hospital and University of Cologne
Cancer Research Center Cologne Essen (CCCE)
funded by the Ministry of Culture and Science of the State of North Rhine-Westphalia.
Berlin Institute for the Foundations of Learning and Data (BIFOLD)
funded by the German Ministry for Research and Education (BMBF).