Open Science

Explore our open access publications, data and models

Open code

Code repository associated with the FedECA article.

A Python implementation of the DESeq2 pipeline for bulk RNA-seq DEA.

A Vision Transformer Large pretrained with Dinov2 self-supervised method on PANCAN-XL.

A self-supervised learning model for histopathology trained with iBOT.

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huggingface.co/owkin

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github.com/owkin

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Open projects

AI moonshot to accelerate open science in Glioblastoma

Open access on medical and scientific results

We are seeking innovative lab facilities for wet-lab validation of our GBM targets and computing partners to revolutionize Glioblastoma patient care.

Open-access publications and preprints

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OwkinZero: Accelerating Biological Discovery with AI

Towards Comprehensive Cellular Characterisation of H&E slides

Benjamin Adjadj

FedECA: federated external control arms for causal inference with time-to-event data in distributed settings

Quentin Klopfenstein

Nature Communications

Joint probabilistic modeling of pseudobulk and single-cell transcriptomics enables accurate estimation of cell type composition

Robust sensitivity control in digital pathology via tile score distribution matching

Predicting gene essentiality and drug response from perturbation screens in preclinical cancer models with LEAP: Layered Ensemble of Autoencoders and Predictors

Barbara Bodinier

Distilling foundation models for robust and efficient models in digital pathology

Alexandre Filiot

FedPyDESeq2: a federated framework for bulk RNA-seq differential expression analysis

Transcriptome Analysis of Archived Tumor Tissues by Visium, GeoMx DSP, and Chromium Methods Reveals Inter- and Intra-Patient Heterogeneity

Legitimate ground-truth-free metrics for deep uncertainty classification scoring

Phikon-v2, A large and public feature extractor for biomarker prediction

Alexandre Filiot

A deep learning-based multiscale integration of spatial omics with tumor morphology.

Benoit Schmauch