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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A modified T-test feature selection method and its application on the HapMap genotype data.
PMID 18267305 · PMC5054219 · Genomics, proteomics & bioinformatics · 2007 · 7 claims · 4 setups
A modified t-test ranking measure, extended to handle nominal SNP genotype data via vector transformation, can effectively rank SNPs by their discriminative capability for population classification.
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Has reproduction · 62
Predicting Bone Metastasis Using Gene Expression-Based Machine Learning Models.
PMID 34858485 · PMC8631472 · Frontiers in genetics · 2021 · 8 claims · 5 setups
A DNN model built on 34 top-ranked hub genes achieves the highest prediction accuracy (AUC 92.11%) for distinguishing primary from bone-metastasized tumors
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Has reproduction · 96
Deep learning based protocol to construct an immune-related gene network of host-pathogen interactions in plants.
PMID 36525344 · PMC9791427 · STAR protocols · 2023 · 7 claims · 6 setups
DLNet algorithm ranks genes based on their contribution to classifying treatment vs. control expression data
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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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Mapping proteins to disease terminologies: from UniProt to MeSH.
PMID 18460185 · PMC2367626 · BMC bioinformatics · 2008 · 8 claims · 7 setups
Developed a three-step procedure (disease name extraction, exact matching, partial/similarity-based matching) to map UniProtKB/Swiss-Prot disease names to MeSH terms