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).

• 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

• PFOS and PFOA exposure induces liver injury and sex-dependent immune effects in C57BL/6 mice.

  PMID 41641100 · PMC12865548 · iScience · 2026 · 7 claims · 7 setups

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  PFOA and PFOS exposure induces hepatotoxicity, including hepatomegaly and elevated serum liver injury biomarkers (ALP, ALT), across sexes and durations

  plasma liver serum thymus lc-ms organ serum

• ICE: robust detection of cellular senescence from weak single-cell signatures using imputation-based marker refinement.

  PMID 41668152 · PMC12990438 · Genome biology · 2026 · 8 claims · 7 setups

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  Senescence-associated marker genes show weak, non-specific expression across human tissues and cell types compared to canonical tissue/cell-type markers

  tissues pancreas pancreatic brain bulk scrna-seq train

• CellPredX, a computational framework for cross-data type, cross-sample, and cross-protocol cell type annotation through domain adaptation and deep metric learning.

  PMID 41481570 · PMC12758788 · PLoS computational biology · 2026 · 8 claims · 7 setups

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  CellPredX is a unified semi-supervised framework integrating domain adaptation and deep metric learning to align heterogeneous embeddings for cross-modality cell type annotation.

  pbmc fetal pancreas gse149683 matched unmatched cross-protocol

• 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