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@CSOgroup

Computational Systems Oncology

CSO lab integrates algorithmic design, numerical modeling, and molecular biology approaches to address relevant questions in cancer biology and therapeutics.

Hello world 👋

  • The Computational Systems Oncology lab integrates algorithmic design, data science, 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 Cancer Center Leman, the Swiss Institute of Bioinformatics, the Center of Precision Oncology of the CHUV and the Swiss Institute for Experimental Cancer Research (ISREC)

Research in brief

  • Cancer Evolutionary Dependencies
    • Cancer emerges through the occurrence and selection of molecular alterations. We aim to understand factors that favor or veto the selection of specific alterations, a.k.a. evolutionary dependencies (EDs). In particular, we focus on a concurrent or mutually exclusive selection of genetic alterations and whether these EDs can inform response to therapy.
  • Cancer Cell Plasticity
    • Cancer cells can change their phenotype or even their identity without modifying their genetic code. We are interested in understanding epigenetic and transcriptional reprogramming programs that underlie cancer cell plasticity. We study features of plastic reprogramming among different patients and within individual tumors, using cutting-edge single-cell and spatial-omics technologies.
  • Chromatin 3D Architecture
    • A key paradigm in biology is that structure determines function. Whether and to what extent this holds true for chromatin 3D architectures remains an open question. Here, we study chromatin structural changes in response to cancer genetic variants and epigenetic reprogramming. Our goal is to decipher chromatin plasticity and determine how it is hijacked in and/or influences tumor phenotypes.

Pinned Loading

  1. cellcharter cellcharter Public

    A Python package for the identification, characterization and comparison of spatial clusters from spatial -omics data.

    Python 99 3

  2. CALDER2 CALDER2 Public

    CALDER is a Hi-C analysis tool that allows: (1) compute chromatin domains from whole chromosome contacts; (2) derive their non-linear hierarchical organization and obtain sub-compartments; (3) comp…

    R 18 2

  3. WGD WGD Public

    Analysis code for "Whole genome doubling drives oncogenic loss of chromatin segregation"

    Python 2

  4. select select Public

    SELECT - Selected Events Linked by Evolutionary Conditions across human Tumors

    R 3

Repositories

Showing 10 of 30 repositories
  • egfr_classes Public

    Repository containing the code for the EGFR classes study.

    CSOgroup/egfr_classes’s past year of commit activity
    R 0 0 0 0 Updated Dec 2, 2024
  • torchgmm Public
    CSOgroup/torchgmm’s past year of commit activity
    Python 3 MIT 0 0 1 Updated Dec 2, 2024
  • select Public

    SELECT - Selected Events Linked by Evolutionary Conditions across human Tumors

    CSOgroup/select’s past year of commit activity
    R 3 LGPL-3.0 0 0 0 Updated Nov 26, 2024
  • CSOgroup/Lymphomoid-IF-pipeline’s past year of commit activity
    Python 1 0 0 1 Updated Nov 22, 2024
  • cellcharter Public

    A Python package for the identification, characterization and comparison of spatial clusters from spatial -omics data.

    CSOgroup/cellcharter’s past year of commit activity
    Python 99 BSD-3-Clause 3 4 0 Updated Nov 22, 2024
  • CSOgroup/HaploC-tools’s past year of commit activity
    Python 0 MIT 0 0 0 Updated Nov 17, 2024
  • SelectSim_analysis Public

    Scripts and supplementary material for SelectSim paper.

    CSOgroup/SelectSim_analysis’s past year of commit activity
    Jupyter Notebook 0 0 0 0 Updated Oct 5, 2024
  • diffComp Public

    Python package for the analysis of differential chromatin compartmentalization

    CSOgroup/diffComp’s past year of commit activity
    Python 0 MIT 0 0 0 Updated Sep 23, 2024
  • SelectSim Public

    This R package implements the SelectSim methodology to infer evolutionary dependencies between functional alterations in cancer.

    CSOgroup/SelectSim’s past year of commit activity
    R 1 0 1 0 Updated Aug 27, 2024
  • CSOgroup/scrnaseq_pipeline’s past year of commit activity
    Python 3 0 0 0 Updated Aug 7, 2024

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