What we do

The Bioinformatics Core Unit (BCU) supports the research groups at the Institute of Oncology Research (IOR) with computational and statistical services. We focus our research interests on the genetics and biology of cancer with a major emphasis on lymphomas and epithelial cancers, such as prostate, breast and ovarian cancer. Importantly, more than just a supporting role, we proactively identify and develop novel bioinformatics projects that can complement and in many cases drive our biologic research.

Find out about the Group’s activities

Core facility activities

In addition to supporting the research groups at the Institute of Oncology Research (IOR) with computational and statistical services, we develop innovative data analysis tools, visualization software and database resources for genomics research in collaboration with the Dalle Molle Institute of Artificial Intelligence (IDSIA) and the SIB Swiss Institute of Bioinformatics.

Here are some of the key services we provide (also see here):

  • System Biology
  • Biostatistics
  • Drug resistance
  • Machine Learning
  • Transcriptomics
  • Multi-omics data integration

Main publications 2019

  • Laginestra MA et al.
    Whole exome sequencing reveals mutations in FAT1 tumor suppressor gene clinically impacting on peripheral T-cell lymphoma not otherwise specified
    Modern Pathology, doi: 10.1038/s41379-019-0279-8
  • Cascione L et al.
    Novel insights into the genetics and epigenetics of MALT lymphoma unveiled by next generation sequencing analyses
    Haematologica, 10.3324/haematol.2018.214957
  • Cascione L et al.
    Long Non-Coding RNAs as Molecular Signatures for Canine B-Cell Lymphoma Characterization
    Noncoding RNA, doi: 10.3390/ncrna5030047

Find out more about the Group’s activities


Bellinzona institute oncology

Luciano Cascione
Bioinformatics Core Unit
Institute of Oncology Research, Bellinzona
Group Webpage

Domain(s) of activity:

  • Core facility and competence centre
  • Biostatistics
  • Data mining
  • Deep sequencing data
  • Oncology
  • Personalised medicine
  • Transcriptomics

Domain(s) of application:

  • Medicine and health