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).

• Combining evidence of preferential gene-tissue relationships from multiple sources.

  PMID 23950964 · PMC3741196 · PloS one · 2013 · 8 claims · 8 setups

  Has reproduction · 53

  A high-level integration approach combining three methods across four human microarray datasets, merged by consensus voting and a rule-based inner/total score, predicts preferentially expressed genes while reducing method- and study-specific bias.

  normal four microarray genes microarray computational bayes

• 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-derived hub genes with a VAE-derived 10-dimensional representation as features for an SVM classifier achieves high accuracy (0.9692) and AUC (0.9981) for colorectal cancer prediction.

  colorectal combined differentially crc microarray differential weighted

• SePaCS--a web-based application for classification of seroreactivity profiles.

  PMID 17478503 · PMC1933220 · Nucleic acids research · 2007 · 8 claims · 4 setups

  Full-text index only

  SePaCS is a freely available web-based tool that trains and applies multiple classification methods (4 Naive Bayes variants, SVM with RBF kernel, LDA, DLDA) to seroreactivity profiles and outputs results as a summary table plus a detailed PDF report

  blood computational seroreactivity supervised mutual

• Bayesian model accounting for within-class biological variability in Serial Analysis of Gene Expression (SAGE).

  PMID 15339345 · PMC517707 · BMC bioinformatics · 2004 · 7 claims · 5 setups

  Full-text index only

  A Bayesian mixture model is proposed to account for within-class biological variability in SAGE/Digital-Northern/MPSS tag counting data.

  astrocytoma same sage classical beta-binomial

• 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