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).

• 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

• An AI-Enabled Single-Cell Transcriptomic Analysis Pipeline for Gene Signature Discovery in Natural Killer Cells Linked to Remission Outcomes in Chronic Myeloid Leukemia.

  PMID 41972591 · PMC13072394 · Biology · 2026 · 8 claims · 7 setups

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  GAFA integrates latent-space representation, pseudotime trajectory modeling, GRN inference, and machine learning-based gene panel discovery into a single coherent pipeline, unlike existing workflows that treat these steps independently.

  peripheral subset immune assigned scrna-seq latent-space automated

• A multi-modal diffusion model with dual-cross-attention for multi-omics data generation and translation.

  PMID 41980989 · PMC13253844 · Nature communications · 2026 · 8 claims · 7 setups

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  scDiffusion-X is a multi-modal latent denoising diffusion probabilistic model for single-cell multi-omics data generation, translation, and interpretation.

  openproblem 10x babel miniatlas paired modality augmentation

• AICellType: a large language model-based platform for accurate cell type annotation.

  PMID 42001469 · PMC13092268 · Briefings in bioinformatics · 2026 · 8 claims · 8 setups

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  Claude 3.5 Sonnet achieved the best overall performance among 79 benchmarked LLMs for cell type annotation, balancing accuracy, robustness, speed, and cost-efficiency

  single-cell immune pbmc in-house llm-based scrna-seq spatial