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).

• 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.

  dorsolateral dlpfc nanostring spatial cell-type multi-platform

• Interpretable, flexible and spatially aware integration of multiple spatial transcriptomics datasets from diverse sources.

  PMID 42045691 · PMC13175893 · Nature genetics · 2026 · 6 claims · 7 setups

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  INSPIRE is a deep-learning method that unifies adversarial learning with a GNN-based encoder and integrated NMF to interpretably integrate multiple spatial transcriptomics datasets

  synthetic dorsolateral brain cortex simulated visium spatial

• NeMO Analytics: a compendium of transcriptomic data for the exploration of neocortical development.

  PMID 41882195 · PMC13061640 · Nature neuroscience · 2026 · 8 claims · 8 setups

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  NeMO Analytics is a curated compendium assembling gene-level transcriptomic (and other multiomic) data from ~200 studies of neocortical development and in vitro models for interrogation by non-coding biologists

  midgestational macaque fetal radial scrna-seq bulk spatial