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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A cellular epigenetic classification system for glioblastoma.
PMID 41499453 · PMC13128495 · Neuro-oncology · 2026 · 8 claims · 8 setups
ITHresolveGBM, a hierarchical two-step NMF method, deconvolutes bulk GBM DNA methylation profiles into three non-malignant (immune, glial, neuronal) and three malignant components
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A generic reference defined by consensus peaks for single-cell ATAC-seq data analysis.
PMID 41663439 · PMC12996591 · Nature communications · 2026 · 7 claims · 7 setups
Aggregating peaks from 624 high-quality bulk ATAC-seq datasets defines ~1.4 million observed consensus peaks (cPeaks) covering ~30% of the genome.
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scTWAS: a powerful statistical framework for single-cell transcriptome-wide association studies.
PMID 41820391 · PMC13121454 · Nature communications · 2026 · 8 claims · 5 setups
scTWAS uses a latent-variable expression-measurement model combined with a moment-based regression to more accurately estimate genetic regulation of gene expression from single-cell data, improving GReX prediction across cell types and datasets
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Prediction of myeloid malignant cells in Fanconi anemia using machine learning.
PMID 41557613 · PMC12818649 · PloS one · 2026 · 6 claims · 7 setups
A DNN classifier trained on AML scRNA-seq data accurately predicts AML-like transcriptional profiles at single-cell resolution
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omnideconv: a unifying framework for using and benchmarking single-cell-informed deconvolution of bulk RNA-seq data.
PMID 41582216 · PMC12837286 · Genome biology · 2026 · 8 claims · 6 setups
omnideconv is an R package providing a unified interface to twelve second-generation deconvolution methods (AutoGeneS, BayesPrism, Bseq-SC, Bisque, CDseq, CIBERSORTx, CPM, DWLS, MOMF, MuSiC, SCDC, Scaden)
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LIMPACAT: Multi-omics attention transformer for immune prediction in liver cancer using whole-slide imaging.
PMID 41511965 · PMC12788640 · PloS one · 2026 · 8 claims · 6 setups
LIMPACAT, a multiple instance learning attention transformer, predicts immune cell levels relevant to HCC prognosis directly from whole-slide images