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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Full-text index only
APC promoter methylation and protein expression in hepatocellular carcinoma.
PMID 17973119 · PMC2757596 · Journal of cancer research and clinical oncology · 2008 · 6 claims · 7 setups
APC promoter methylation is significantly higher in HCC compared to non-cancerous liver tissue
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Has reproduction · 87
Identification of a novel lncRNA prognostic signature and analysis of functional lncRNA AC115619.1 in hepatocellular carcinoma.
PMID 37614318 · PMC10442647 · Frontiers in pharmacology · 2023 · 8 claims · 8 setups
A six-lncRNA prognostic signature (LINC02428, LINC02163, AC008549.1, AC115619.1, CASC9, LINC02362) predicts overall survival in HCC patients
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Full-text index only
p53 mutation is a poor prognostic indicator for survival in patients with hepatocellular carcinoma undergoing surgical tumour ablation.
PMID 9514057 · PMC2149958 · British journal of cancer · 1998 · 8 claims · 6 setups
p53 mutations were found in 8 of 12 HCCs with cirrhosis due to viral hepatitis and in both patients with sarcomatoid change
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Has reproduction · 51
Unveiling prognostics biomarkers of tyrosine metabolism reprogramming in liver cancer by cross-platform gene expression analyses.
PMID 32542016 · PMC7295234 · PloS one · 2020 · 6 claims · 8 setups
Five tyrosine catabolic enzymes (TAT, HPD, HGD, GSTZ1, FAH) are downregulated in HCC versus normal liver at mRNA and protein levels
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Has reproduction · 84
DeepProg: an ensemble of deep-learning and machine-learning models for prognosis prediction using multi-omics data.
PMID 34261540 · PMC8281595 · Genome medicine · 2021 · 6 claims · 7 setups
DeepProg, an ensemble of deep-learning and machine-learning models, robustly predicts patient survival subtypes from multi-omics data and explicitly models survival as the objective while predicting new patient risks
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Has reproduction
Using random walks to identify cancer-associated modules in expression data.
PMID 24128261 · PMC4015830 · BioData mining · 2013 · 8 claims · 8 setups
Walktrap-GM, a random-walk community detection algorithm adapted with stopping criteria (maximum modularity, maximum size, maximum module score), identifies modules significantly enriched with cancer genes in expression-weighted interaction networks.