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).
-
Full-text index only
Characterisation of the genetic diversity of Brucella by multilocus sequencing.
PMID 17448232 · PMC1877810 · BMC microbiology · 2007 · 8 claims · 5 setups
Brucella isolates show low overall genetic diversity (1.5%) across nine sequenced loci, confirming the genus is genetically conserved.
-
Has reproduction · 89
DFAST and DAGA: web-based integrated genome annotation tools and resources.
PMID 27867804 · PMC5107635 · Bioscience of microbiota, food and health · 2016 · 8 claims · 7 setups
DFAST is a web-based genome annotation pipeline with integrated quality assessment (CheckM) and taxonomic assessment (ANI) that produces DDBJ submission-ready files
-
Has reproduction · 87
Mutually exclusive teams-like patterns of gene regulation characterize phenotypic heterogeneity along the noradrenergic-mesenchymal axis in neuroblastoma.
PMID 38230570 · PMC10795782 · Cancer biology & therapy · 2024 · 8 claims · 6 setups
NOR-specific and MES-specific gene expression patterns are largely mutually exclusive, exhibiting a teams-like behavior across multiple bulk NB transcriptomic datasets
-
Has reproduction · 50
The molecular landscape of sepsis severity in infants: enhanced coagulation, innate immunity, and T cell repression.
PMID 38817614 · PMC11137207 · Frontiers in immunology · 2024 · 8 claims · 8 setups
Only two of seven published sepsis gene signatures (derived from adult/pediatric/geriatric cohorts) showed good concordance (>80% accuracy) when applied to infant sepsis, showing limited generalizability of non-infant signatures.
-
Has reproduction · 67
Optimal scaling of digital transcriptomes.
PMID 24223126 · PMC3819321 · PloS one · 2013 · 8 claims · 8 setups
Fifteen existing and novel transcript-count normalization algorithms can be compared with two novel, mutually independent metrics: the number of "uniform" genes (sufficiently low coefficient of variation after normalization) and low average Spearman correlation between normalized expression profiles of gene pairs.