What we do

In the Computational Cancer Biology Group, our aim is to study interactions between cancer and immune cells. We are focusing on molecular and cellular aspects of cancer immune cell interactions. At the molecular level, we have developed tools to predict (neo-)antigen presentation from HLA peptidomics datasets and are currently working on TCR-peptide-HLA interaction predictions. At the cellular level, we are developing novel approaches to characterizing immune infiltrations and the different states of immune cells from (single-cell) gene expression data.

All our tools are available at https://github.com/GfellerLab

Find out more about the Group’s activities

Main publications 2020

  • Carmona S J et al.
    Deciphering the transcriptomic landscape of tumor-infiltrating CD8 lymphocytes in B16 melanoma tumors with single-cell RNA-Seq
    Oncoimmunology, 10.1080/2162402X.2020.1737369
  • Solleder M et al.
    Mass spectrometry based immunopeptidomics leads to robust predictions of phosphorylated HLA class I ligands
    Mol Cell Proteomics, 10.1074/mcp.TIR119.001641
  • Racle J and Gfeller D
    EPIC: A Tool to Estimate the Proportions of Different Cell Types from Bulk Gene Expression Data
    Methods in Mol Bio, 10.1007/978-1-0716-0327-7_17



David Gfeller
Computational Cancer Biology Group
University of Lausanne
Group Webpage

Domain(s) of activity:

  • Proteins and proteomes
  • Immunology
  • Oncology
  • Single-cell biology
  • Transcriptomics

Domain(s) of application:

  • Basic research
  • Medicine and health