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).
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Has reproduction · 67
Heterogeneity and Differentiation Trajectories of Infiltrating CD8+ T Cells in Lung Adenocarcinoma.
PMID 36358600 · PMC9658355 · Cancers · 2022 · 7 claims · 8 setups
Infiltrating CD8+ T cells in LUAD can be divided into ten transcriptionally distinct subsets: eight cytotoxic (CTL) subsets, one naive-like (NTL) subset, and one exhausted (ETL) subset.
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Has reproduction · 50
Integrative analysis of transcriptomic data reveals a predictive gene signature for chemoradiotherapy response in rectal cancer.
PMID 41550766 · PMC12803930 · iScience · 2026 · 8 claims · 5 setups
A 186-gene signature derived from six GEO transcriptomic datasets predicts nCRT response in LARC with AUC 0.80 in cross-validation
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Has reproduction · 100
Identification of a PRDM1-regulated T cell network to regulate atherosclerotic plaque inflammation.
PMID 41039608 · PMC12490039 · Genome medicine · 2025 · 6 claims · 7 setups
A distinct gene co-expression module with a prominent T cell signature is enriched in unstable plaques and distinguishes high-risk from low-risk lesions.
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Has reproduction · 70
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
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.
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Has reproduction · 78
Evaluating Distribution and Prognostic Value of New Tumor-Infiltrating Lymphocytes in HCC Based on a scRNA-Seq Study With CIBERSORTx.
PMID 33043022 · PMC7527443 · Frontiers in medicine · 2020 · 5 claims · 6 setups
CIBERSORTx can combine scRNA-seq-derived signatures with bulk HCC transcriptomes to estimate proportions of 11 TIL subsets and infer cell-type-specific gene expression.
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Full-text index only
Effects of HIV type-1 immune selection on susceptability to integrase inhibitor resistance.
PMID 19918099 · PMC4155129 · Antiviral therapy · 2009 · 8 claims · 6 setups
Primary integrase inhibitor resistance mutations (T66I, E92Q, G140S, Y143C/H/R, Q148H/R/K, N155S/H) were absent in 342 drug-naive individuals, indicating these sites are highly constrained.
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Has reproduction · 94
iBRIDGE: A Data Integration Method to Identify Inflamed Tumors from Single-cell RNA-Seq Data and Differentiate Cell Type-Specific Markers of Immune-Cell Infiltration.
PMID 37023414 · PMC10236149 · Cancer immunology research · 2023 · 8 claims · 8 setups
Malignant cells cluster by patient in scRNA-seq data while immune and stromal cells cluster by cell type, making malignant cells uniquely suited to carry patient-level inflamed/cold signal
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Has reproduction · 50
Heterogeneity of cancer-associated fibroblasts in head and neck squamous cell carcinoma.
PMID 37320872 · PMC10277597 · Translational oncology · 2023 · 8 claims · 9 setups
Seven distinct CAF subsets exist in HNSCC, identified via integration of scRNA-seq, bulk transcriptomic, and spatial transcriptomic data.
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Has reproduction · 83
Multimodal data integration for biologically-relevant artificial intelligence to guide adjuvant chemotherapy in stage II colorectal cancer.
PMID 40472802 · PMC12171563 · EBioMedicine · 2025 · 6 claims · 7 setups
AI-derived radiological clustering identifies stage II CRC patients with significantly different survival benefit from adjuvant chemotherapy
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Has reproduction · 96
Scalable Prediction of Acute Myeloid Leukemia Using High-Dimensional Machine Learning and Blood Transcriptomics.
PMID 31918046 · PMC6992905 · iScience · 2020 · 8 claims · 8 setups
Data-driven, high-dimensional ML approaches that learn multivariate signatures directly from genome-wide transcriptomic data (no prior gene selection) yield accurate and robust AML classifiers.