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).

• Motif discovery in promoters of genes co-localized and co-expressed during myeloid cells differentiation.

  PMID 19059999 · PMC2632922 · Nucleic acids research · 2009 · 6 claims · 8 setups

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  A novel multi-step computational method (built on approximate pattern enumeration, binomial over-representation scoring with FDR correction, and k-medoids clustering) can identify over-represented motifs in a selected set of promoters relative to a background promoter set.

  myeloid reference selected genome-localized microarray promoter k-medoids

• Bulk and single-cell characterisation of the immune heterogeneity of atherosclerosis identifies novel targets for immunotherapy.

  PMID 36855107 · PMC9974063 · BMC biology · 2023 · 8 claims · 8 setups

  Has reproduction · 70

  Integration of scRNA-seq datasets from human atherosclerosis samples identifies 28 distinct immune cell subpopulations with heterogeneity in tissue preference, genetics, function, immune dynamics, transcriptional regulators, metabolism, and cell communication.

  immune atherosclerotic cd4+ cd8+ scrna-seq gsea pseudotime

• Technical challenges in using human induced pluripotent stem cells to model disease.

  PMID 19951687 · PMC2921621 · Cell stem cell · 2009 · 8 claims · 8 setups

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  hiPSCs generated from patient somatic cells (skin, blood) can be differentiated into disease-relevant cell types to model disease pathogenesis in vitro

  ipscs humanized hemophilia parkinsonian tetraploid transplantation neuronal

• Correcting scale distortion in RNA sequencing data.

  PMID 39875825 · PMC11776150 · BMC bioinformatics · 2025 · 8 claims · 8 setups

  Has reproduction · 76

  Local averaging reveals expression-level-dependent biases that differ from sample to sample across all RNA-seq datasets studied, and are not corrected by conventional normalization (TPM/FPKM)

  tcga su2c gse47774 gtex bulk computational d'agostino

• Digital sorting of complex tissues for cell type-specific gene expression profiles.

  PMID 23497278 · PMC3626856 · BMC bioinformatics · 2013 · 8 claims · 8 setups

  Has reproduction · 85

  The Digital Sorting Algorithm (DSA) deconvolves mixed tissue expression into cell type-specific profiles using only marker genes, without requiring prior knowledge of cell type frequencies or in vitro pure-cell profiles.

  liver im-9 immune deconvolved microarray simulation roc