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).

• Parsimonious Gene Correlation Network Analysis (PGCNA): a tool to define modular gene co-expression for refined molecular stratification in cancer.

  PMID 30993001 · PMC6459838 · NPJ systems biology and applications · 2019 · 8 claims · 7 setups

  Has reproduction · 71

  Retaining only the top ~3 most correlated edges per gene (EPG3) combined with FastUnfold clustering (termed PGCNA) produces gene co-expression modules with significantly better separation and enrichment of known biology than using all edges or other clustering methods.

  breast colorectal brca representative gene comparative multi-omic

• Colorectal Cancer Prediction Based on Weighted Gene Co-Expression Network Analysis and Variational Auto-Encoder.

  PMID 32825264 · PMC7563725 · Biomolecules · 2020 · 6 claims · 7 setups

  Has reproduction · 80

  Combining WGCNA hub genes and VAE 10-dimensional representation as features for an SVM classifier achieves high accuracy in predicting CRC

  colorectal same combined meturquoise microarray differential batch

• Cancer-wide in silico analyses using differentially expressed genes demonstrate the functions and clinical relevance of JAG, DLL, and NOTCH.

  PMID 39074091 · PMC11285958 · PloS one · 2024 · 7 claims · 8 setups

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  JAG, DLL, and NOTCH family gene/protein expression varies diversely across 15 cancer types relative to normal tissue, sometimes discordant between mRNA and protein levels.

  tumor degs cancer jag bulk proteomics gene