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The molecular landscape of premature aging diseases defined by multilayer network exploration @cecilebeust Alberto Valdeolivas @AnthBaptista Ozan Özışık @BaudotAnais medrxiv.org/content/10.110…

Finally out a new paper from the lab lead by Remi Trimbour "Molecular mechanisms reconstruction from single-cell multi-omics data with HuMMuS" doi.org/10.1093/bioinf… #singlecell #multilayernetworks

Local heterogeneity of tissues can define their function and predict clinical outcomes. We introduce Kasumi 💻biorxiv.org/content/10.110… to identify spatially localized neighborhoods of intra and intercellular relationships from spatial omics persistent across samples & conditions

If you like MISTy doi.org/10.1186/s13059…, you'll really like Kasumi doi.org/10.1101/2024.0…. Kasumi is a multi-view explainable representation learning approach, capturing localized relationship-based patterns in tissues across conditions aiming towards facilitating translation

Hello! We're seeking an intern or master's student for a 6-month exploratory project in spatial analysis. Please share or apply! 😀 careers.roche.com/global/en/job/…

New publication: The Molecular Landscape of Premature Aging Diseases Defined by Multilayer Network Exploration @cecilebeust Alberto Valdeolivas @AnthBaptista Galadriel Brière, Nicolas Lévy, Ozan Özışık @BaudotAnais doi.org/10.1002/adbi.2…

Paper is out! Deconvolve cellular composition from bulk gene expression nature.com/articles/s4146…

Check the latest DREAMchallenges paper, evaluating methods to deconvolve cellular composition from bulk gene expression, with contributions from our (former) Alberto Valdeolivas & Julio Saez-Rodriguez 👇

Chrysalis, a machine learning-based framework, accurately infers cellular niches and underlying gene expression programs in the tissue from spatial transcriptomics data doi.org/10.1038/s42003… Demeter Turos Sven Rottenberg Alberto Valdeolivas

Super happy to announce that Chrysalis is finally out! Our new reference-free method identifies cellular niches in #spatialtranscriptomics with robust performance. Paper: nature.com/articles/s4200… 🧵 (1/7)

Excited to share our new #biorxiv preprint! X-Pression combines deep learning with micro-CT to reconstruct 3D #spatialtranscriptomics from a single 2D section. A powerful, cost-effective way to explore tissues in 3D! Link: biorxiv.org/content/10.110… #SARSCoV2-infected lung below!

Take a look inside a SARS-CoV-2-infected mouse lung with X-Pression! Our 3D reconstructions reveal changes in gene expression programs across the entire organ, leveraging ST and micro-CT. Check out the details in our preprint: biorxiv.org/content/10.110… #SpatialTranscriptomics

Excited to share our new preprint! We map the spatiotemporal dynamics of therapy response & minimal residual disease in BRCA1;p53-deficient breast #cancer using #MultiOmics. We identify drug-tolerant EMT cancer cells, offering new therapeutic targets. 🔗biorxiv.org/content/10.110…