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).

• CLUES A Comprehensive Workflow for Integrating Geospatial Data in Biomedical Research.

  PMID 42128886 · PMC13172076 · Nature communications · 2026 · 8 claims · 5 setups

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  CLUES is an open-source, end-to-end workflow that automates selection, download, harmonization, and linkage of open-access geospatial environmental data to individual-level biomedical data without requiring geospatial expertise.

  national copernicus digital norwegian large-scale download spatial

• SpaGene: A Deep Adversarial Framework for Spatial Gene Imputation.

  PMID 42146899 · PMC13176606 · Computational and structural biotechnology journal · 2026 · 8 claims · 6 setups

  Has reproduction · 74

  SpaGene improves average PCC and SSIM and reduces RMSE compared to 6 baseline methods (SpaGE, gimVI, Tangram, VISTA, spRefine, stDiff) across 8 diverse ST-SC dataset pairs under gene-holdout evaluation.

  pairs nanostring st-sc osmfish_zeisel st-sc 5-fold spatially

• PreTSA: computationally efficient modeling of temporal and spatial gene expression patterns.

  PMID 41673899 · PMC12998178 · Genome biology · 2026 · 7 claims · 8 setups

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  PreTSA dramatically reduces computational time and memory versus GAM (Monocle, TSCAN) and PseudotimeDE for identifying temporally variable genes (TVGs) while producing highly similar results

  simulated null pbmc pancreas pseudotime tvg false-positive

• TiRank prioritizes phenotypic niches in tumor microenvironment for clinical biomarker discovery.

  PMID 41689080 · PMC12910759 · Genome medicine · 2026 · 7 claims · 4 setups

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  TiRank is a framework that integrates scRNA-seq, ST, and bulk transcriptomes using an REO-transformation module and multitask transfer learning to align data into a unified embedding space for prioritizing clinically relevant spatial niches

  benchmark pan-cancer gastric independent scrna-seq bulk spatial

• Spatial information matters: are traditional imputation methods effective for spatial transcriptomics data?

  PMID 41627342 · PMC12862982 · Briefings in bioinformatics · 2026 · 7 claims · 3 setups

  Has reproduction · 89

  No single existing SOTA imputation method consistently performs well across newer SRT platforms/datasets

  datasets srt same computational proposed

• VISTA uncovers missing gene expression and spatial-induced information for spatial transcriptomic data analysis.

  PMID 41507434 · PMC12891734 · Communications biology · 2026 · 8 claims · 6 setups

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  VISTA predicts unmeasured gene expression in subcellular spatial transcriptomic data by integrating scRNA-seq and SST through variational inference and geometric deep learning with built-in uncertainty quantification

  brain breast embryo muscle imaging-based sequencing spot-based

• 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

  Has reproduction · 42

  CanCellCap identifies cancer cells in scRNA-seq data across 13 tissue types, 23 cancer types, and 7 sequencing platforms with 0.977 average accuracy

  cancer testing sequencing unseen scrna-seq spatial

• sCellST predicts single-cell gene expression from H& E images.

  PMID 41513659 · PMC12858858 · Nature communications · 2026 · 7 claims · 6 setups

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  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

  ovarian kidney prostate breast simulation spot-level nucleus

• Benchmarking LLM-based agents for single-cell omics analysis.

  PMID 41742311 · PMC13064268 · Genome biology · 2026 · 8 claims · 8 setups

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  Introduces a comprehensive benchmarking evaluation system comprising an open-source agent platform, 18 evaluation metrics across four dimensions, and 50 real-world single-cell omics tasks

  agent single-cell spatial scatac-seq llm-agent scrna-seq spatial