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 · 73
Integrated multiomic analysis reveals disulfidptosis subtypes in glioblastoma: implications for immunotherapy, targeted therapy, and chemotherapy.
PMID 38504986 · PMC10950096 · Frontiers in immunology · 2024 · 8 claims · 8 setups
Consensus clustering on 32 disulfidptosis-associated genes stratifies GBM patients into two subtypes, DRGcluster A and B, with distinct survival outcomes.
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Has reproduction
Fast, accurate, and racially unbiased pan-cancer tumor-only variant calling with tabular machine learning.
PMID 36611079 · PMC9825621 · NPJ precision oncology · 2023 · 7 claims · 8 setups
Tabular ML classifiers (TabNet, XGBoost, LightGBM) trained on tumor-only-derived features achieve state-of-the-art somatic vs germline classification, with AUC>94% on TCGA holdout and AUC>85% on metastatic melanoma.
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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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Full-text index only
Cancer-specific high-throughput annotation of somatic mutations: computational prediction of driver missense mutations.
PMID 19654296 · PMC2763410 · Cancer research · 2009 · 7 claims · 7 setups
CHASM, a Random Forest-based computational method, was developed to identify and prioritize missense mutations likely to be functional drivers of tumor cell proliferation.