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 · 59
Refining breast cancer biomarker discovery and drug targeting through an advanced data-driven approach.
PMID 38253993 · PMC10810249 · BMC bioinformatics · 2024 · 8 claims · 8 setups
The BGWO_SA_Ens algorithm (hybrid BGWO + simulated annealing with an ensemble classifier objective function) selects predictive breast cancer biomarker genes with high classification performance
-
Full-text index only
High-resolution aCGH and expression profiling identifies a novel genomic subtype of ER negative breast cancer.
PMID 17925008 · PMC2246289 · Genome biology · 2007 · 7 claims · 8 setups
A novel subtype of high-grade ER-negative breast cancer exists, characterized by a low genomic instability index (GII)
-
Has reproduction · 79
TSUNAMI: Translational Bioinformatics Tool Suite for Network Analysis and Mining.
PMID 33705981 · PMC9403021 · Genomics, proteomics & bioinformatics · 2021 · 8 claims · 6 setups
TSUNAMI is a freely accessible web-based tool suite that mines gene co-expression network (GCN) modules from public (GEO, TCGA) or user-uploaded numerical omics data and performs downstream gene set enrichment analysis.
-
Full-text index only
Comparing protein abundance and mRNA expression levels on a genomic scale.
PMID 12952525 · PMC193646 · Genome biology · 2003 · 8 claims · 8 setups
Correlations between mRNA expression and protein abundance are generally poor or limited across most studies reviewed, including in yeast and human cancers
-
Has reproduction · 73
Vespucci: a system for building annotated databases of nascent transcripts.
PMID 24304890 · PMC3936758 · Nucleic acids research · 2014 · 8 claims · 7 setups
Existing ChIP-seq and RNA-seq analysis platforms (e.g. Cufflinks, peak callers) are unsuited to GRO-seq because they assume spliced/exonic reads, uniform density and paired-end data, and cannot identify transcriptional units de novo across the whole genome.