Julien Mena

The paper identifies an RFX-driven ciliogenic cell state in colorectal cancer that is sensitive to FGFR inhibitors and associated with poor prognosis.

The paper uses multiplexed imaging and deep learning to analyze immune cell phenotypes across human cohorts, revealing associations with age, gender, and health markers.

scROSHI identifies cell types without training data by using pre-existing gene sets and hierarchical relationships, outperforming methods in low-data and high-diversity scenarios.

SCIM matches single-cell measurements across technologies by learning a technology-invariant latent space and applying bipartite matching, achieving high accuracy in real-world datasets.