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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Ultra-precision deconvolution of spatial transcriptomics decodes immune heterogeneity and fate-defining programs in tissues.
PMID 41862467 · PMC13168514 · Nature communications · 2026 · 8 claims · 8 setups
UCASpatial is a novel deconvolution algorithm that uses Shannon entropy-based gene weighting combined with weighted non-negative least squares to estimate cell-type composition from spatial transcriptomics data
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pmid-41916307
PMID 41916307 · PMC13107060 · 7 claims · 4 setups
TOAST extends the classical FGW objective by adding a spatial coherence term and a neighborhood consistency term to model local spatial organization and molecular heterogeneity.
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SA2E: spatial-aware auto-encoder for cell type deconvolution of spatial transcriptomics data.
PMID 41863296 · PMC13070677 · Bioinformatics (Oxford, England) · 2026 · 8 claims · 5 setups
SA2E is a spatial-aware auto-encoder framework for cell-type deconvolution that does not require predefined cell-type biomarkers
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scComm: a contrastive learning framework for deciphering cell-cell communications at single-cell resolution.
PMID 41877186 · PMC13134144 · Genome biology · 2026 · 8 claims · 7 setups
scComm infers cell-cell communications at single-cell resolution using a data-adaptive L-R weighting module and supervised contrastive learning (SupCon loss) to distinguish significant CCC events from background noise
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SMART: spatial multi-omic aggregation using graph neural networks and metric learning.
PMID 41896208 · PMC13031631 · Nature communications · 2026 · 8 claims · 5 setups
SMART accurately identifies spatial regions of anatomical structures and is compatible with spatial datasets of any type and number of omics layers
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scSurv: a deep generative model for single-cell survival analysis.
PMID 41429574 · PMC12797213 · Bioinformatics (Oxford, England) · 2026 · 8 claims · 6 setups
scSurv combines a Cox proportional hazards model with a deep generative model (VAE) of single-cell transcriptomes to estimate individual cellular contributions to clinical outcomes
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Has reproduction · 100
Computational modeling demonstrates that glioblastoma cells can survive spatial environmental challenges through exploratory adaptation.
PMID 31836713 · PMC6911112 · Nature communications · 2019 · 8 claims · 6 setups
Exploratory adaptation (stochastic gene-regulatory network perturbation) explains how GBM cells adapt phenotypically across spatially distinct tumor regions
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Has reproduction · 42
CanCellCap: robust cancer cell capture across tissue types on single-cell RNA-seq data by multi-domain learning.
PMID 40739511 · PMC12312500 · BMC biology · 2025 · 8 claims · 7 setups
CanCellCap identifies cancer cells in scRNA-seq data across 13 tissue types, 23 cancer types, and 7 sequencing platforms with 0.977 average accuracy
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pmid-41912521
PMID 41912521 · PMC13199379 · 8 claims · 8 setups
RareQ is a framework that quantifies neighborhood connectivity (Q), a cell-specific measure of kNN-graph cliquishness, to detect rare cell populations from single-cell and spatial omics data
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Standing on the shoulders of microbes: microbiome thermal priming buffers the effects of heatwaves on clams by preventing stress overreaction.
PMID 41987828 · PMC13077298 · ISME communications · 2026 · 8 claims · 5 setups
Transplantation of a microbiome from heat-primed donor clams into non-acclimated recipients is sufficient to enhance host resilience during a subsequent simulated heatwave.
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sCellST predicts single-cell gene expression from H& E images.
PMID 41513659 · PMC12858858 · Nature communications · 2026 · 7 claims · 6 setups
sCellST is a weakly supervised (Multiple Instance Learning) deep learning framework that predicts single-cell gene expression from H&E images alone, trained using paired spatial transcriptomics (Visium) and H&E slides
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HRCHY-CytoCommunity identifies hierarchical tissue organization in cell-type spatial maps.
PMID 41764165 · PMC13065825 · Nature communications · 2026 · 8 claims · 5 setups
HRCHY-CytoCommunity is an end-to-end graph neural network framework that jointly identifies multi-level (coarse tissue compartment and fine cellular neighborhood) tissue structures from cell-type spatial maps using differentiable graph pooling, adaptive edge pruning, and consistency/balance regularization.
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Visualizing stability: a sensitivity analysis framework for t-SNE embeddings.
PMID 41552665 · PMC12808344 · Frontiers in bioinformatics · 2025 · 8 claims · 5 setups
The Implicit Function Theorem, combined with automatic differentiation, can be used to efficiently compute the complete sensitivity Jacobian of a converged t-SNE embedding with respect to the input data, avoiding differentiation through the full iterative optimizer.
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Has reproduction · 95
Increased prevalence of hybrid epithelial/mesenchymal state and enhanced phenotypic heterogeneity in basal breast cancer.
PMID 38974967 · PMC11225361 · iScience · 2024 · 7 claims · 7 setups
Luminal breast cancer gene expression signature is closely/positively associated with an epithelial signature