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 · 95
Increased prevalence of hybrid epithelial/mesenchymal state and enhanced phenotypic heterogeneity in basal breast cancer.
PMID 38974967 · PMC11225361 · iScience · 2024 · 7 claims · 7 setups
Luminal breast cancer gene expression signature is closely/positively associated with an epithelial signature
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Has reproduction · 77
PredTAD: A machine learning framework that models 3D chromatin organization alterations leading to oncogene dysregulation in breast cancer cell lines.
PMID 34093998 · PMC8142020 · Computational and structural biotechnology journal · 2021 · 7 claims · 8 setups
PredTAD, a Gradient Boosting Machine model using epigenomic and genomic features plus neighboring-bin information, classifies 10 kb genomic regions as TAD boundary or non-boundary across normal and breast cancer cell lines.
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Full-text index only
Probing the cancer genome.
PMID 18492227 · PMC2441462 · Genome biology · 2008 · 8 claims · 8 setups
Combined Sanger and 454 pyrosequencing of MCF-7 BAC clones identified 157 PCR-confirmed translocation breakpoint junctions, including 10 in-frame junctions confirmed at the transcript level
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Full-text index only
Nutritional genomics, polyphenols, diets, and their impact on dietetics.
PMID 18954579 · PMC2692306 · Journal of the American Dietetic Association · 2008 · 8 claims · 8 setups
Nutrient-gene interactions, exemplified by the MTHFR C677T polymorphism, modulate individual metabolic responses (e.g., homocysteine metabolism) and can be offset by adjusting nutrient intake such as folate
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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.