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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Alexander Meissner: learning the reprogramming code.
PMID 19704017 · PMC2733751 · The Journal of cell biology · 2009 · 8 claims · 6 setups
A defined set of factors present in oocytes and embryonic stem (ES) cells can reprogram a somatic cell to pluripotency, as shown by nuclear transfer and ES cell/somatic cell fusion experiments
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Has reproduction · 89
TrEMOLO: accurate transposable element allele frequency estimation using long-read sequencing data combining assembly and mapping-based approaches.
PMID 37013657 · PMC10069131 · Genome biology · 2023 · 6 claims · 6 setups
TrEMOLO combines an assembly-based INSIDER module and a mapping-based OUTSIDER module to detect TE insertions/deletions from long-read sequencing data and estimate their allele frequency
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Activation-induced cytidine deaminase acts as a mutator in BCR-ABL1-transformed acute lymphoblastic leukemia cells.
PMID 17485517 · PMC2118573 · The Journal of experimental medicine · 2007 · 8 claims · 8 setups
AID mRNA is aberrantly expressed in Ph+ ALL but largely absent in Ph- ALL
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The field of tissue injury in the lung and airway.
PMID 19138985 · PMC2705781 · Cancer prevention research (Philadelphia, Pa.) · 2008 · 8 claims · 8 setups
Field cancerization and the field of injury reflect molecular changes (genomic, epigenomic, transcriptomic, proteomic) present in histologically normal-appearing tissue distant from and independent of a tumor, throughout the carcinogen-exposed respiratory epithelium
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Extraction of human kinase mutations from literature, databases and genotyping studies.
PMID 19758464 · PMC2745582 · BMC bioinformatics · 2009 · 7 claims · 6 setups
A literature mining pipeline combining MutationFinder, false-positive filtering, and SVM-based classification can extract and disambiguate single-point mutation mentions from abstracts and full text