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).

• Using random walks to identify cancer-associated modules in expression data.

  PMID 24128261 · PMC4015830 · BioData mining · 2013 · 8 claims · 8 setups

  Has reproduction

  Walktrap-GM, a random-walk community detection algorithm adapted with stopping criteria (maximum modularity, maximum size, maximum module score), identifies modules significantly enriched with cancer genes in expression-weighted interaction networks.

  hepatocellular breast sporadic geo gene differential interaction

• Network properties of complex human disease genes identified through genome-wide association studies.

  PMID 19956617 · PMC2779513 · PloS one · 2009 · 7 claims · 6 setups

  Full-text index only

  Complex disease genes are significantly less central (lower degree/closeness, higher eccentricity) in the human interactome than essential and monogenic disease genes, occupying an intermediate niche between monogenic disease genes and non-disease genes

  complex interactome gene disease-sharing gene protein-protein

• Severe COVID-19 Shares a Common Neutrophil Activation Signature with Other Acute Inflammatory States.

  PMID 35269470 · PMC8909161 · Cells · 2022 · 7 claims · 7 setups

  Has reproduction · 88

  COVID-19 and HLH share immunological pathways, yielding 237 common up-regulated DEGs dominated by cytokine/chemokine signaling and neutrophil-mediated immune responses.

  peripheral leukocytes plasma degs bulk single-cell plasma

• Prioritization of candidate cancer genes--an aid to oncogenomic studies.

  PMID 18710882 · PMC2566894 · Nucleic acids research · 2008 · 8 claims · 8 setups

  Full-text index only

  Computational classifiers using combinations of protein conservation, gene structure, protein domains, protein interactions, and regulatory data can distinguish known cancer genes (CD/CR) from unlabelled human genes

  genes cancer interpro interactome averaged cross-validation domain