David Gfeller

Biography

David Gfeller was trained as a physicist and mathematicians. He obtained his PhD in Theoretical Physics at the Swiss Federal Institute of Technology (EPFL) in 2007, working with Prof. Paolo De Los Rios. He then decided to move to Computational Biology and joined the lab of Prof. Gary Bader at University of Toronto where he worked as a post-doc from 2008 to 2010. There, he developed several computational techniques to predict new protein interactions involving a variety of signaling domains, such as PDZ or SH3. In 2010, he joined the group of Prof. Olivier Michielin at SIB as an EMBO fellow to work on in silico approaches to inhibit protein interactions. Among else, he developed the first database of non-natural sidechains and new methods to predict the targets of small molecules. After a 6-month stay at EBI as a visiting scientist, he was recruited at the LICR as an assistant professor in December 2014.      

Research Interest

Our main research interests lie in the field of computational and systems biology and its applications to cancer and immunology research. Combining large-scale data analysis from genomics and proteomics together with modeling approaches, we aim at better understanding how immunogenicity is regulated in cancer and how cancer cells manage to escape immune recognition despite the presence of cancer specific genetic variants. In particular, our research focuses on: Prediction of cancer specific (neo-)epitopes. Modeling of immune infiltration and cell type heterogeneity in tumors. Single-cell RNA-Seq analysis of tumors and immune cell populations. Analysis of amino acid co-evolution in MHC proteins To address these questions, we use and develop machine learning and other statistical methods.