What we do

Tumors are molecularly diverse and each tumor is an evolutionary system on its own. The inter- and intra-tumor heterogeneity influence the clinical and biological behavior of cancers and has important implications in tumor progression, metastatic process and therapy resistance. The Oncogenomics lab focuses on developing and applying computational approaches to address challenges in precision oncology. In particular, we are interested in leveraging the abundance of omics data derived from clinically annotated samples in computational frameworks to advance our understanding in tumor cellular dynamics, to discover novel biomarkers and therapeutic targets and to elucidate genotype-to-phenotype associations in cancer.

Find out more about the Group’s activities

Main publications 2021

Montazeri H et al.
Systematic Identification of Novel Cancer Genes through Analysis of Deep shRNA Perturbation Screens
Nucleic Acids Res, 10.1093/nar/gkab627

Coto-Llerena M et al.
Transcriptional Enhancer Factor Domain Family member 4 Exerts an Oncogenic Role in Hepatocellular Carcinoma by Hippo‐Independent Regulation of Heat Shock Protein 70 Family Members
Hepatol Commun, 10.1002/hep4.1656

Gallon J et al.
Epigenetic priming in chronic liver disease impacts the transcriptional and genetic landscapes of hepatocellular carcinoma
Mol Oncol, 10.1002/1878-0261.13154


University bern

Charlotte Ng
University of Bern
Group webpage

Domain(s) of activity:

  • Systems biology
  • Biomarkers
  • Data mining
  • Deep sequencing data
  • DNA Microarrays
  • Machine learning
  • Next generation sequencing
  • Oncology
  • Personalised medicine
  • Proteomics
  • Signaling pathways
  • Single-cell biology
  • Transcriptomics
  • Workflows

Domain(s) of application:

  • Medicine and health