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 2020

De Mattos-Arruda L et al.
Neoantigen prediction and computational perspectives towards clinical benefit: recommendations from the ESMO Precision Medicine Working Group
Ann Oncol., 10.1016/j.annonc.2020.05.008

Bianco G et al.
GATA3 and MDM2 are Synthetic Lethal in Estrogen-receptor Positive Breast Cancers
BioRxiv, 10.1101/2020.05.18.101998

Terracciano LM et al.
Hepatocellular Carcinoma: Pathology and Genetics.
Encyclopedia of Cancer 3rd Edition, 10.1016/B978-0-12-801238-3.65261-3


University bern

Charlotte Ng
University of Bern

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