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We are interested in how genetic and epigenetic alterations of regulatory DNA elements drive cancer.
Cancer is driven by genetic and epigenetic changes to the DNA. We now know quite well how genetic alterations of genes drive cancer, thanks to extensive mapping efforts. However, we still know very little about the extent and function of genetic and epigenetic alterations at regulatory regions away from genes.
Other than expanding our understanding of gene regulation and dysregulation in cancer, we aim to leverage this knowledge to predict novel therapeutic targets for the development of new drugs, and develop models to predict patient outcome to help guiding treatment plans for cancer patients.
Our scientific approach combines epigenetic profiling, development of computational models and algorithms, and experimental validation. We combine cutting edge experimental techniques with developing new machine learning algorithms and big-data analytical approaches.
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