The Gevaert lab focuses on biomedical data fusion in oncology: the development of machine learning methods for biomedical decision support using multi-scale biomedical data. Previously I pioneered data fusion work using Bayesian and kernel methods studying breast and ovarian cancer. My subsequent work concerned the development of methods for multi-omics data fusion. This resulted in the development of MethylMix, to identify differentially methylation driven genes, and AMARETTO, a computational method to integrate DNA methylation, copy number and gene expression data to identify cancer modules. Additionally, my lab focuses on multi-scale data fusion by linking omics with cellular and tissue-level phenotypes. This led to key contributions in the field of imaging genomics/radiogenomics involving work in lung cancer and brain tumors. Our work in imaging genomics is focused on developing a framework for non-invasive personalized medicine. In summary, my lab has an interdisciplinary focus on developing novel algorithms for multi-scale biomedical data fusion.
Editorial Board Memberships
Olivier is not currently contributing as an editor for any journal or publisher.
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The distribution of the Journal Impact Factors of journals Olivier Gevaert has reviewed for.
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