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).

• SPEAQeasy: a scalable pipeline for expression analysis and quantification for R/bioconductor-powered RNA-seq analyses.

  PMID 33932985 · PMC8088074 · BMC bioinformatics · 2021 · 8 claims · 5 setups

  Has reproduction · 65

  SPEAQeasy is a portable, easy-to-install, Nextflow-powered RNA-seq processing pipeline that lowers the computational entry barrier for biologists/clinicians

  provided amygdala rna-seq differentially pipeline bulk rna-based

• Testing whether genetic variation explains correlation of quantitative measures of gene expression, and application to genetic network analysis.

  PMID 18444230 · PMC2729096 · Statistics in medicine · 2008 · 8 claims · 3 setups

  Full-text index only

  A statistical test (delta method and Steiger-Browne optimal linear composites) is developed to test equality of the marginal correlation and the partial correlation of two gene expression traits conditional on a set of covariates.

  simulated real analytical simulation application

• Emergent dynamics of underlying regulatory network links EMT and androgen receptor-dependent resistance in prostate cancer.

  PMID 36851919 · PMC9957767 · Computational and structural biotechnology journal · 2023 · 8 claims · 7 setups

  Has reproduction · 78

  Simulations of the EMT-AR crosstalk network reveal four possible phenotypes: epithelial-sensitive (ES), epithelial-resistant (ER), mesenchymal-resistant (MR), and mesenchymal-sensitive (MS), with MS occurring rarely

  gene racipe clinical tcga racipe influence principal

• Single-Cell Differential Network Analysis with Sparse Bayesian Factor Models.

  PMID 35186014 · PMC8855158 · Frontiers in genetics · 2021 · 8 claims · 2 setups

  Has reproduction · 85

  A hierarchical Bayesian factor model using treatment-dependent latent factor loadings can construct gene co-expression networks from scRNA-seq data and identify differences in network structure between two (or more) biological conditions.

  simulated sars-cov-2 scrna-seq