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 · 83
Gene-expression patterns in peripheral blood classify familial breast cancer susceptibility.
PMID 26538066 · PMC4634735 · BMC medical genomics · 2015 · 8 claims · 7 setups
A multigene expression biomarker from PBMCs accurately classifies familial breast cancer (FBC) status
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Spatiotemporal dynamics of spermatogenesis: insights from high-resolution spatial transcriptomics and pseudotime trajectories in mouse testes.
PMID 41602862 · PMC12832764 · Frontiers in reproductive health · 2025 · 8 claims · 7 setups
Salus-STS (1 μm resolution) combined with the Salus Cellbins Algorithm enables accurate subcellular segmentation of individual testicular cells in dense tissue
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Has reproduction · 97
CellFishing.jl: an ultrafast and scalable cell search method for single-cell RNA sequencing.
PMID 30744683 · PMC6371477 · Genome biology · 2019 · 8 claims · 5 setups
CellFishing.jl achieves accuracy comparable to state-of-the-art software (scmap-cell) but is markedly faster
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Identification of candidate disease genes by integrating Gene Ontologies and protein-interaction networks: case study of primary immunodeficiencies.
PMID 19073697 · PMC2632920 · Nucleic acids research · 2009 · 8 claims · 5 setups
Combining high protein-interaction network scores with significant PID-related GO terms identifies novel PID candidate genes
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Has reproduction · 83
Hierarchical classification-based pan-cancer methylation analysis to classify primary cancer.
PMID 38066424 · PMC10709847 · BMC bioinformatics · 2023 · 8 claims · 8 setups
CHCT, a two-tier hierarchical classification tool built from methylation data, accurately classifies primary cancer type across 30 cancer types.
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Genome-wide prioritization of disease genes and identification of disease-disease associations from an integrated human functional linkage network.
PMID 19728866 · PMC2768980 · Genome biology · 2009 · 6 claims · 6 setups
Integrating 16 genomic features (32 sub-features) via a naïve Bayes classifier produces a genome-scale FLN of 21,657 human genes and 22,388,609 weighted links that outperforms any individual data source for inferring functional linkages.
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Identification of a pediatric acute hypoxemic respiratory failure signature in peripheral blood leukocytes at 24 hours post-ICU admission with machine learning.
PMID 37009294 · PMC10063855 · Frontiers in pediatrics · 2023 · 7 claims · 5 setups
A machine learning stability selection approach (bootstrapped logistic regression, 100 simulations) can identify genes associated with PaO2/FiO2 < 200 vs ≥200 when standard differential expression with FDR correction shows no overlap between cohorts.
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Has reproduction · 62
Application of alternative de novo motif recognition models for analysis of structural heterogeneity of transcription factor binding sites: a case study of FOXA2 binding sites.
PMID 34547062 · PMC8408018 · Vavilovskii zhurnal genetiki i selektsii · 2021 · 8 claims · 4 setups
MultiDeNA pipeline combines PWM, diPWM, BaMM and InMoDe models to train, evaluate, threshold, and classify ChIP-seq peaks for TFBS structural heterogeneity
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Genomic variation in myeloma: design, content, and initial application of the Bank On A Cure SNP Panel to detect associations with progression-free survival.
PMID 18778477 · PMC2553089 · BMC medicine · 2008 · 7 claims · 7 setups
A custom BOAC SNP panel of 3404 SNPs in 983 genes was developed using the Affymetrix GeneChip Targeted Genotyping Platform, focused on non-synonymous coding SNPs and regulatory-region SNPs in candidate genes.
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Cancer-specific high-throughput annotation of somatic mutations: computational prediction of driver missense mutations.
PMID 19654296 · PMC2763410 · Cancer research · 2009 · 7 claims · 7 setups
CHASM, a Random Forest-based computational method, was developed to identify and prioritize missense mutations likely to be functional drivers of tumor cell proliferation.