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).

• FineST: contrastive learning integrates histology and spatial transcriptomics for nuclei-resolved ligand-receptor analysis.

  PMID 41839892 · PMC13201544 · Nature communications · 2026 · 8 claims · 6 setups

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  FineST, a bimodal contrastive learning model integrating histology (Virchow2 ViT features) and spatial gene expression, enables nuclei-resolved high-resolution RNA imputation.

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• Systematic background selection with BasCoD enhances contrastive dimension reduction in single cell genomics.

  PMID 41844632 · PMC13144610 · Nature communications · 2026 · 8 claims · 7 setups

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  BasCoD is a statistical testing framework using spectral subspace inclusion theory to evaluate whether a candidate background dataset is suitable for contrastive dimension reduction of a target dataset

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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

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  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.

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