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).

• 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

  Has reproduction · 59

  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

  pancreatic rna-seq liver tumor bulk machine multi-label

• Qualitative Transcriptional Signature for the Pathological Diagnosis of Pancreatic Cancer.

  PMID 33173782 · PMC7538791 · Frontiers in molecular biosciences · 2020 · 8 claims · 7 setups

  Has reproduction · 71

  A 12-gene-pair (17-gene) REO-based signature discriminates PC and cancer-adjacent normal tissue from non-tumor (healthy/pancreatitis) pancreatic tissue.

  pancreatic normal pooled microarray rna-sequencing roc

• Wiggle-predicting functionally flexible regions from primary sequence.

  PMID 16839194 · PMC1500818 · PLoS computational biology · 2006 · 7 claims · 6 setups

  Full-text index only

  A GNM-derived, correlation-weighted 'FF score' can objectively define functionally flexible regions (FFRs) that match experimentally confirmed flexible/functional regions (hinges, recognition loops, catalytic loops).

  hiv bovine calmodulin nonredundant gaussian gnm support

• Cancer-specific high-throughput annotation of somatic mutations: computational prediction of driver missense mutations.

  PMID 19654296 · PMC2763410 · Cancer research · 2009 · 7 claims · 7 setups

  Full-text index only

  CHASM, a Random Forest-based computational method, was developed to identify and prioritize missense mutations likely to be functional drivers of tumor cell proliferation.

  missense same synthetic tp53 random support principal

• scATD: a high-throughput and interpretable framework for single-cell cancer drug resistance prediction and biomarker identification.

  PMID 40501071 · PMC12159290 · Briefings in bioinformatics · 2025 · 8 claims · 6 setups

  Has reproduction · 62

  scATD enables high-throughput single-cell drug sensitivity prediction for new patients without model parameter retraining via bidirectional Bi-AdaIN style transfer

  panglaodb cancer geo gse137829 single-cell bulk