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 A Deep Learning approach for time-consistent cell cyclephase prediction from microscopy data
  • Articles scientifiques
A Deep Learning approach for time-consistent cell cyclephase prediction from microscopy data
Thomas Walter // The cell cycle consists of four phases and impacts most cellular processes. In imaging assays, the cycle phase can be identified using dedicated cell-cycle markers. However, such markers occupy fluorescent channels that may be needed for other reporters. Here, we propose to address this limitation by inferring the phase from a widely used fluorescent reporter: SiR-DNA.
14 novembre 2025
 STORIES: learning cell fate landscapes from spatial transcriptomics using optimal transport
  • Articles scientifiques
STORIES: learning cell fate landscapes from spatial transcriptomics using optimal transport
Laura Cantini // In dynamic biological processes such as development, spatial transcriptomics is revolutionizing the study of the mechanisms underlying spatial organization within tissues. Inferring cell fate trajectories from spatial transcriptomics profiled at several time points has thus emerged as a critical goal, requiring novel computational methods.
14 novembre 2025
 Loop extrusion provides mechanical robustness to chromatin
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Loop extrusion provides mechanical robustness to chromatin
Hossein Salari, Daniel Jost // Chromosomes are complex biopolymers folded into dynamic loops via a loop extrusion process and may experience various mechanical forces in vivo. We develop a force-dependent model of chromatin loop extrusion and investigate its mechanical consequences on chromosome organization using simulations and analytical theory. We show that loop extrusion alters the force–extension behavior of DNA in a non-monotonic manner: extrusion stiffens the chain at low forces but softens it at intermediate and high forces.
14 novembre 2025
 FAIR sharing of Chromatin Tracing datasets using the newly developed 4DN FISH Omics Format
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FAIR sharing of Chromatin Tracing datasets using the newly developed 4DN FISH Omics Format
Marcelo Nollmann // A key output of the NIH-Common Fund 4D Nucleome (4DN) project 1,2 is the open publication of datasets related to the structure of the human cell nucleus and the genome. Recent years have seen a rapid expansion of multiplexed Fluorescence In Situ Hybridization (FISH) or FISH-omics methods, which quantify the spatial organization of chromatin in single cells, sometimes together with RNA and protein measurements, and provide an expanded understanding of how 3D higher-order chromosome structure relates to transcriptional activity and cell development in both health and disease.
13 novembre 2025

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