Computational Cancer Biology
We are interested how alterations of the DNA transform a healthy into a malignant cell. 10,000s of human genomes and epigenomes have been sequenced over the last years. These efforts uncovered a large number of genetic or epigenetic alterations in cancer patients. Given this large number of alterations it is difficult to tell which of those contribute to disease progression.
Cancer development is a process that often takes many years. During this time cancer cells vary, compete and the fittest survive. We are studying the evolutionary principles underlying this process and try to understand how the environment modulates cancer evolution and contributes to the molecular variation between cancers from different tissues.
Another focus of our lab is to understand how genes work together to create complex phenotypes such as cancer. Traditionally, genes have been studied in isolation. We develop methods using tools from network and systems biology to better understand the interplay between different alterations in cancer genomes and epigenomes.
Ultimately, our goal is to understand the impact of genomic and epigenomic varition on patient phenotypes such as survival or drug response. We thereby support the development of diagnostic and personalized therapeutic approaches.
Most Relevant Publications
Cancer genomes tolerate deleterious coding mutations through somatic copy number amplifications of wild-type regions.
Nat Commun, 2023
Location and condition based reconstruction of colon cancer microbiome from human RNA sequencing data.
Genome Med, 2023
Genome Biology, 2023
DNA methylation variation along the cancer epigenome and the identification of novel epigenetic driver events.
Nucleic Acids Res, 2021