Experiments
Searchable full-text extractions: founding hypothesis, core claims, experimental setups, key results and statistics — pulled out of each paper as structure. Search a cell line, an assay or an entity (e.g. HUH7) and find every paper that worked with it. This corpus stands on its own: most entries carry no reproduction assessment (yet).
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Tensor-cell2cell v2 unravels coordinated dynamics of protein- and metabolite-mediated cell-cell communication.
PMID 41719185 · PMC12937581 · Bioinformatics (Oxford, England) · 2026 · 8 claims · 4 setups
Tensor-cell2cell v2 implements a non-negative coupled tensor component analysis (CTCA) that jointly factorizes protein- and metabolite-mediated communication tensors sharing context, sender, and receiver dimensions while keeping ligand-type-specific (private) dimensions separate.
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S3RL: Enhancing Spatial Single-Cell Transcriptomics With Separable Representation Learning.
PMID 41556263 · PMC13042551 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026 · 8 claims · 8 setups
S3RL is a separable representation learning framework that denoises sparse spatial transcriptomic data and enhances biologically relevant signals by integrating gene expression, spatial coordinates, and histological image features.