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

• 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

• RNASEQR--a streamlined and accurate RNA-seq sequence analysis program.

  PMID 22199257 · PMC3315322 · Nucleic acids research · 2012 · 8 claims · 7 setups

  Has reproduction · 86

  RNASEQR is a new RNA-seq mapper/aligner that combines a BWT-based (Bowtie) transcriptomic/genomic alignment with hash-based BLAT local alignment in three sequential steps: transcriptome mapping, novel exon detection, and anchor-and-align novel splice junction identification.

  ccds glioblastoma experimental simulated simulated bulk quality

• 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