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).
-
Has reproduction · 56
Identification of key genes in chickpea transcriptomics and the development of ChickpeaOmicsR as a comprehensive resource to advance breeding and genomic studies.
PMID 41909810 · PMC13022592 · Frontiers in bioinformatics · 2026 · 8 claims · 8 setups
ChickpeaOmicsR is the first comprehensive R package that integrates transcriptomic, genomic, and proteomic chickpea data, automates DEG/PPI/GWAS analyses, and standardizes fragmented chickpea gene nomenclature
-
Has reproduction · 51
Cell type-specific eQTL analysis of COVID-19 based on single-cell transcriptomic data.
PMID 41064594 · PMC12501775 · NAR genomics and bioinformatics · 2025 · 8 claims · 8 setups
Single-cell eQTL analysis across eight immune cell types identified 2593 genes whose expression is significantly associated with common genetic polymorphisms, with most genes showing cell type-specific effects
-
Has reproduction · 100
Gene co-expression network analysis in human spinal cord highlights mechanisms underlying amyotrophic lateral sclerosis susceptibility.
PMID 33707641 · PMC7970949 · Scientific reports · 2021 · 8 claims · 8 setups
WGCNA on control human cervical spinal cord RNA-seq identifies 13 co-expression modules (SC.M1-M13), each representing distinct biological processes or cell types.
-
Full-text index only
Multi-organ expression profiling uncovers a gene module in coronary artery disease involving transendothelial migration of leukocytes and LIM domain binding 2: the Stockholm Atherosclerosis Gene Expression (STAGE) study.
PMID 19997623 · PMC2780352 · PLoS genetics · 2009 · 8 claims · 6 setups
Functionally associated gene modules, not individual genes, underlie CAD development and can be identified via multi-organ expression clustering