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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PSGRN: Gene regulatory network inference from single-cell perturbational data through self-training with synthetic gold standards.
PMID 42054465 · PMC13127566 · Science advances · 2026 · 8 claims · 4 setups
PSGRN infers GRNs by generating pseudoannotations from gene-gene correlations and iteratively refining them via a self-training classifier using pre/post-intervention expression features.
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Characterizing gene perturbations in single cells via network divergence analysis.
PMID 41965857 · PMC13249949 · Nature communications · 2026 · 8 claims · 8 setups
scDNS quantifies gene-specific functional perturbations by measuring Jensen-Shannon divergence between condition-specific gene interaction network configurations
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The proteomic landscape and temporal dynamics of human and mouse gastruloid development.
PMID 42032312 · PMC13179132 · Nature cell biology · 2026 · 8 claims · 8 setups
Generated a quantitative proteomic, phosphoproteomic, and matched transcriptomic resource across four stages of human and mouse gastruloid development
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Multiomics and deep learning dissect regulatory syntax in human development.
PMID 41951735 · PMC13216069 · Nature · 2026 · 8 claims · 8 setups
The Human Development Multiomic Atlas (HDMA) is a single-cell atlas of chromatin accessibility and gene expression from 817,740 fetal cells across 12 organs, spanning 203 cell types
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CellPolaris: Transfer Learning for Gene Regulatory Network Construction to Guide Cell State Transitions.
PMID 41498638 · PMC12948241 · Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026 · 8 claims · 8 setups
CellPolaris is a unified computational framework performing TF-centered GRN construction, master TF identification, and TF perturbation simulation
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EPInformer: scalable and integrative prediction of gene expression from promoter-enhancer sequences with multimodal epigenomic profiles.
PMID 41832145 · PMC13133354 · Nature communications · 2026 · 8 claims · 7 setups
EPInformer outperforms existing gene expression prediction models (Xpresso, CREaTor, Seq-GraphReg, Enformer, Borzoi) in rigorous 12-fold cross-chromosome validation for both RNA-seq and CAGE expression prediction