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).

• 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

  Has reproduction · 73

  Consensus clustering on 32 disulfidptosis-associated genes stratifies GBM patients into two subtypes, DRGcluster A and B, with distinct survival outcomes.

  fresh tcga gbm bulk rna-seq consensus

• An integrated genomic analysis of human glioblastoma multiforme.

  PMID 18772396 · PMC2820389 · Science (New York, N.Y.) · 2008 · 8 claims · 7 setups

  Full-text index only

  IDH1 is recurrently mutated at its active site (R132) in 12% of GBM patients, a previously unrecognized alteration in GBM.

  gbm additional missense exome targeted snp

• 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

• Spatial-reprogramming derived GPNMB(+) macrophages interact with COL6A3(+) fibroblasts to enhance vascular fibrosis in glioblastoma.

  PMID 41174767 · PMC12577258 · Genome medicine · 2025 · 7 claims · 8 setups

  Has reproduction · 64

  A distinct subset of COL6A3+ tumor-associated fibroblasts (TAFs) with matrix-fibroblast characteristics exists in GBM and is significantly enriched in non-responders to neoadjuvant combination therapy.

  newly glioma ffpe tafs single-cell spatial bulk

• 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