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).
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Has reproduction · 74
Transcriptome profiling of Giardia intestinalis using strand-specific RNA-seq.
PMID 23555231 · PMC3610916 · PLoS computational biology · 2013 · 8 claims · 8 setups
Most of the G. intestinalis genome is transcribed in in vitro-grown trophozoites, but at vastly different expression levels.
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Association of poly-purine/poly-pyrimidine sequences with meiotic recombination hot spots.
PMID 16846522 · PMC1543642 · BMC genomics · 2006 · 7 claims · 6 setups
PPT frequency is significantly elevated in yeast meiotic recombination hot spots compared with cold spots
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SECIS elements in the coding regions of selenoprotein transcripts are functional in higher eukaryotes.
PMID 17169995 · PMC1802603 · Nucleic acids research · 2007 · 8 claims · 5 setups
SECIS elements located within coding regions of selenoprotein mRNAs support functional Sec insertion in mammalian cells
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Has reproduction · 62
Bayesian prediction of RNA translation from ribosome profiling.
PMID 28126919 · PMC5389577 · Nucleic acids research · 2017 · 8 claims · 4 setups
Rp-Bp is an unsupervised Bayesian approach that uses a two-component 'high-low-low' mixture model to predict translated ORFs from ribosome profiles
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Automated recognition of retroviral sequences in genomic data--RetroTector.
PMID 17636050 · PMC1976444 · Nucleic acids research · 2007 · 8 claims · 8 setups
RetroTector uses 'fragment threading' (detection of chains of conserved retroviral motifs satisfying distance constraints) combined with LTR detection and protein reconstruction to identify ERVs in genomic sequences
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Has reproduction · 81
Comparing the utility of in vivo transposon mutagenesis approaches in yeast species to infer gene essentiality.
PMID 32681306 · PMC7599172 · Current genetics · 2020 · 7 claims · 7 setups
A Random Forest machine-learning approach can predict gene essentiality from in vivo transposon insertion data across multiple yeast species and transposon systems