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 · 69
Machine learning-based identification of an immunotherapy-related signature to enhance outcomes and immunotherapy responses in melanoma.
PMID 39355255 · PMC11442245 · Frontiers in immunology · 2024 · 8 claims · 8 setups
66 consensus immunotherapy prognostic genes (CITPGs) were identified from the intersection of WGCNA modules, immunotherapy responder-vs-non-responder DEGs, and tumor-vs-normal DEGs
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Has reproduction · 71
Interpretable artificial intelligence based on immunoregulation-related genes predicts prognosis and immunotherapy response in lung adenocarcinoma.
PMID 41048340 · PMC12491262 · Frontiers in bioinformatics · 2025 · 8 claims · 8 setups
LUAD samples cluster into IRG-high and IRG-low groups, with the IRG-high group showing significantly better survival and greater immune cell infiltration.
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Has reproduction · 80
Comprehensive analysis of transcriptomics and radiomics revealed the potential of TEDC2 as a diagnostic marker for lung adenocarcinoma.
PMID 39553728 · PMC11569783 · PeerJ · 2024 · 8 claims · 8 setups
WGCNA identified 214 key genes in the blue module most correlated with LUAD
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Has reproduction · 42
Machine learning-based identification of biomarkers and drugs in immunologically cold and hot pancreatic adenocarcinomas.
PMID 39152432 · PMC11328457 · Journal of translational medicine · 2024 · 7 claims · 8 setups
PAAD tumors can be consensus-clustered into immunologically hot and cold subtypes based on CIBERSORT-derived immune cell fractions, with significantly different survival outcomes.
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Has reproduction · 78
Enhancing chemotherapy response prediction via matched colorectal tumor-organoid gene expression analysis and network-based biomarker selection.
PMID 39754813 · PMC11754497 · Translational oncology · 2025 · 6 claims · 8 setups
A consensus WGCNA approach combining matched tumor-organoid and independent organoid drug-response expression data identifies gene modules and hub genes predictive of 5-FU chemotherapy response
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Has reproduction · 59
Application of Machine Learning in Predicting Hepatic Metastasis or Primary Site in Gastroenteropancreatic Neuroendocrine Tumors.
PMID 37887568 · PMC10605255 · Current oncology (Toronto, Ont.) · 2023 · 8 claims · 7 setups
Multi-gene random forest models classify primary tumor vs. liver metastasis samples with 100% accuracy in training/test cohorts and >90% accuracy in an independent validation cohort
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Has reproduction · 71
Single-Cell Transcriptomic Landscape of Right-Sided Colon Cancer Reveals Cellular and Molecular Features of Metastatic Potential.
PMID 41898210 · PMC13024220 · Biomedicines · 2026 · 8 claims · 8 setups
Liver metastatic potential in RCC is marked by stem-like tumor states, metabolic plasticity, and microenvironmental remodeling.
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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.
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Has reproduction · 49
Integrative transcriptomics and single-cell transcriptomics analyses reveal potential biomarkers and mechanisms of action in papillary thyroid carcinoma.
PMID 40520228 · PMC12162626 · Frontiers in genetics · 2025 · 8 claims · 8 setups
ENTPD1, SERPINA1, and TACSTD2 are potential transcriptomic biomarkers for PTC
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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 · 8 setups
A 186-gene signature predictive of nCRT response was derived from integrating six GEO transcriptomic datasets using machine learning.