The Computational Systems Oncology lab integrates algorithmic design, numerical modeling, and molecular biology approaches to address relevant questions in cancer biology and therapeutics.

Our group is embedded within the Department of Computational Biology of the University of Lausanne and a member of the Swiss Institute of Bioinformatics and the Swiss Cancer Center Leman.

Genomic Dependencies

Cancer emerges through the occurrence and selection of molecular alterations. A main goal in our group is to understand if and how alterations present in a cancer cell favor or veto the selection of specific new ones, thus generating non-random patterns of occurrence across tumor populations.

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Actionable Cancer Genetics & Epigenetics

Selected genetic and epigenetic modifications in cancer represent implementations of oncogenic mechanisms and actionable targets for precision treatments. We dissect large-scale genomic datasets to nominate selected events and identify oncogenic signatures informing the design of combination therapies.

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Cancer Evolution

Tumor evolution is typically modeled according to Darwinian principles. By integrating human data with simple models of cancer evolutions, we aim at exploring which features associate and drive tumor intrinsic heterogeneity and to what extent this can be predicted.

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Chromatin Architecture

DNA 3D structures have recently become accessible through Hi-chromatin conformation capture techniques (Hi-C). Our group has become interested in this approach to explore how cancer alterations and gene regulation depend and/or affect the chromatin structure.

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Currently open positions:

  • PhD student positions available in our lab!

    We are currently looking for Ph.D students to join our interdisciplinary team. For these positions, previous experience in cancer genomics and/or analysis of molecular/sequencing data is preferred, although not essential. Solid programming skills are required (R and Python are preferred).

    The prospective student will be enrolled in the UNIL Ph.D. program in Quantitative Biology. Application should be sent through the UNIL-QB website and sent in copy to Giovanni Ciriello.

    IMPORTANT: Apply before October 11th to be eligible for PhD Fellowship @UNIL Appointments are envisioned to start in 2020 (between January and April).