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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The association of Alu repeats with the generation of potential AU-rich elements (ARE) at 3' untranslated regions.
PMID 15610565 · PMC544599 · BMC genomics · 2004 · 6 claims · 4 setups
Alu repeats are a source of AREs at 3' UTRs of human mRNA, via poly-A regions of Alu generating complementary poly-T/poly-U regions that acquire regular adenine insertions to form ARE motifs.
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Has reproduction · 71
Protein structure quality assessment based on the distance profiles of consecutive backbone Cα atoms.
PMID 24555103 · PMC3892923 · F1000Research · 2013 · 8 claims · 8 setups
The distance between consecutive backbone Cα atoms in high-quality structures is normally distributed with mean 3.8 Å and standard deviation 0.04 Å, justifying a reference state in which all consecutive Cα atoms are 3.8 Å apart.
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LMPD: LIPID MAPS proteome database.
PMID 16381922 · PMC1347484 · Nucleic acids research · 2006 · 8 claims · 5 setups
LMPD is an object-relational database of lipid-associated protein sequences and annotations, publicly available from the LIPID MAPS Consortium website.
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In silico discovery of gene-coding variants in murine quantitative trait loci using strain-specific genome sequence databases.
PMID 12537567 · PMC151180 · Genome biology · 2002 · 6 claims · 4 setups
Strain-specific mouse genome sequence databases can be used in a high-throughput in silico pipeline to discover gene-coding variants within murine QTLs, without de novo sequencing.
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Has reproduction · 53
Combining evidence of preferential gene-tissue relationships from multiple sources.
PMID 23950964 · PMC3741196 · PloS one · 2013 · 8 claims · 8 setups
A high-level integration approach combining three methods across four human microarray datasets, merged by consensus voting and a rule-based inner/total score, predicts preferentially expressed genes while reducing method- and study-specific bias.