This preprint closes a long development phase…
but opens a new frontier: morphology as a quantitative, molecularly anchored measurement modality.
If this resonates with your work, we’d love to connect.
Thanks again to the entire team and looking forward to exciting new IRIS adventures 🚀!
(1/13) Excited to share the outcome of the IBIS Challenge! The IBIS challenge united dozens of teams across the world in tackling the problem of modeling transcription factor (TF) binding specificity using a diverse collection of experimental datasets for understudied human TFs.
We uncovered phase-specific TF activity, revealing how DREAM complex repression, FUCCI intensity, and cell-cycle speed are linked. IRIS detects quiescence-primed vs fully quiescent states & shows that slowly cycling cells display stronger DREAM-mediated repression, insights missed by RNA-only tools.
We just released IRIS (7+yrs project), a tech we believe will transform cell biology by pairing high-resolution cell images with matched #scRNAseq, letting us interpret cellular form by its molecular ground truth.
Huge tx to @JohannesBues, @JoernPezoldt, @CamilleLambert et al.
shorturl.at/zgY8Z
We also show that IRIS enables prediction of transcriptomes directly from images (#ML). Models trained on IRIS data recover gene-level variation, cell-cycle phase, and cell identity from morphology alone.
As a 1st application, we used IRIS to profile >5k FUCCI-3T3 cells, reconstructing the full continuous #cell-cycle from morphology + RNA; identifying 670 cycling genes. IRIS’s morphology-anchored cell-cycle angle aligns with Seurat/Tricycle but provides smoother, higher-resolution structure.
Excited to announce the EPFL Latsis Symposium 2026: Decoding the Cell: Modeling, Predicting, and Engineering Cellular States
📅 Oct 29–30, 2026
📍 Olympic Museum, Lausanne 🇨🇭
Registration: latsis2026.epfl.ch/event/1/
#SingleCell #SystemsBiology #SyntheticBiology #AI #Multiomics #CellEngineering
IRIS solves a long-standing gap: #imaging and droplet-based sequencing were never truly connected at single-cell resolution. Here, every cell is imaged first (BF + 4 fluorescent channels) → then deterministically barcoded → then sequenced, enabling single cell #phenomics.
IRIS also revealed that subtle nuclear morphologies correspond to distinct molecular states, including the previously puzzling T cell stripy nuclear phenotype (collab. w/ @BerendSnijder's lab; Hale et al., Science, 2024), now shown to map to a specific transcriptomic program.
