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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High-quality acinar cell isolation enables single-cell analysis of healthy and injured pancreas.
PMID 42013858 · PMC13198085 · Cell reports methods · 2026 · 8 claims · 7 setups
The DCTC protocol isolates up to 90% acinar cells from healthy wild-type pancreatic tissue without cell fixation or dead-cell removal kits
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singIST: An integrative method for comparative single-cell transcriptomics between disease models and humans.
PMID 41838773 · PMC13008255 · PLoS computational biology · 2026 · 8 claims · 7 setups
singIST provides explainable quantitative measures of disease model similarity to a human reference at the pathway, cell type, and gene levels
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Trajectory-guided dimensionality reduction for multi-sample single-cell RNA-seq data reveals biologically relevant sample-level heterogeneity.
PMID 42024616 · PMC13188987 · Bioinformatics (Oxford, England) · 2026 · 8 claims · 6 setups
MUSTARD is a trajectory-guided dimensionality reduction method for multi-sample, multi-condition scRNA-seq data that simultaneously captures gene expression variation along pseudotime and across samples
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Development of a pediatric immune cell atlas and characterization of CD4+ T cells in food allergy.
PMID 42025535 · PMC13105851 · Pediatric allergy and immunology : official publication of the European Society of Pediatric Allergy and Immunology · 2026 · 8 claims · 8 setups
A pediatric single-cell PBMC reference atlas was developed from 57 healthy children across 8 public scRNA-seq studies.
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Deconvolving cell-type-specific gene expression profiles from bulk RNA-seq samples.
PMID 41886524 · PMC13038110 · PLoS computational biology · 2026 · 8 claims · 6 setups
BLUE, a U-Net-based deep learning model with dual branches (U-Net for GEPs, MLP for proportions), accurately predicts cell-type proportions and cell-type-specific gene expression profiles from bulk RNA-seq.
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Single-cell transcriptomics identifies regulatory T cell heterogeneity in gestational diabetes mellitus.
PMID 41933176 · PMC13223204 · Communications medicine · 2026 · 8 claims · 8 setups
Treg cluster proportions do not significantly differ between GDM and healthy control patients