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 · 84
randPedPCA: rapid approximation of principal components from large pedigrees.
PMID 40877802 · PMC12392600 · Genetics, selection, evolution : GSE · 2025 · 7 claims · 2 setups
Matrix-vector multiplication with the dense additive relationship matrix A can be performed implicitly and efficiently via forward/backward substitution using the sparse inverse relationship (Cholesky) factor L^-1, avoiding explicit construction of A.
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Has reproduction · 32
Developing prognostic gene panel of survival time in lung adenocarcinoma patients using machine learning.
PMID 35117753 · PMC8799101 · Translational cancer research · 2020 · 8 claims · 5 setups
Naïve Bayes using a 22-gene panel is the best-performing and most stable machine learning model for predicting LUAD survival time (>3 vs <3 years)
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ADaCGH: A parallelized web-based application and R package for the analysis of aCGH data.
PMID 17710137 · PMC1940324 · PloS one · 2007 · 8 claims · 4 setups
ADaCGH implements eight CNA detection methods, including the best-performing ones from recent reviews (CBS, GLAD, CGHseg, HMM)
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Has reproduction · 76
Bayesian prediction of microbial oxygen requirement.
PMID 26913185 · PMC4743139 · F1000Research · 2013 · 7 claims · 8 setups
A naive Bayesian classifier based on presence/absence of class-associated Pfam-A domains can distinguish three oxygen requirement classes (aerobe, anaerobe, facultative anaerobe) from genome sequence, unlike prior studies that only made pairwise distinctions.
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Has reproduction · 85
Digital sorting of complex tissues for cell type-specific gene expression profiles.
PMID 23497278 · PMC3626856 · BMC bioinformatics · 2013 · 8 claims · 8 setups
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.
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OTMODE: an optimal transport theory-based framework for identifying differential features in single-cell multi-omics data.
PMID 41335419 · PMC12766913 · Bioinformatics (Oxford, England) · 2026 · 8 claims · 8 setups
OTMODE, using an unbalanced Sinkhorn algorithm and Wald test, improves differential feature identification in single-cell multi-omics data