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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A comprehensive sensitivity analysis of microarray breast cancer classification under feature variability.
PMID 19941644 · PMC2789744 · BMC bioinformatics · 2009 · 7 claims · 4 setups
Feature variability strongly influences breast cancer signature composition even when array platform and patient stratification are identical.
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Prioritization of candidate cancer genes--an aid to oncogenomic studies.
PMID 18710882 · PMC2566894 · Nucleic acids research · 2008 · 8 claims · 8 setups
Computational classifiers using combinations of protein conservation, gene structure, protein domains, protein interactions, and regulatory data can distinguish known cancer genes (CD/CR) from unlabelled human genes
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Has reproduction · 44
Dynamic Gene Attention Focus (DyGAF): Enhancing Biomarker Identification Through Dual-Model Attention Networks.
PMID 40160891 · PMC11951896 · Bioinformatics and biology insights · 2025 · 6 claims · 5 setups
DyGAF, a dual-model attention neural network (independent Model A + dependent Model B), identifies and ranks genes by significance for COVID-19 biomarker discovery more effectively than differential expression analysis (DEA) and random forest (RF) feature selection
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Boosting accuracy of automated classification of fluorescence microscope images for location proteomics.
PMID 15207009 · PMC449699 · BMC bioinformatics · 2004 · 8 claims · 8 setups
New classifiers (SVMs, ensembles) and new wavelet-derived (Gabor, Daubechies) features improve recognition of protein subcellular location patterns over the previous neural network approach
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Has reproduction · 48
Comparative analysis of molecular signatures reveals a hybrid approach in breast cancer: Combining the Nottingham Prognostic Index with gene expressions into a hybrid signature.
PMID 35143511 · PMC8830616 · PloS one · 2022 · 8 claims · 6 setups
A hybrid signature combining the Nottingham Prognostic Index with SIS-selected gene expressions can be built in a data-driven fashion (NPI treated as a gene expression during feature selection).
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Has reproduction · 49
Integration of Transcriptomics With Interpretable Artificial Intelligence for Identifying Molecular Signatures of Physiological Stress in Sleep Deprivation.
PMID 42216239 · PMC13240488 · Journal of cellular and molecular medicine · 2026 · 8 claims · 8 setups
S100A3 is a robust candidate biomarker showing consistent discriminatory performance across the acute sleep deprivation training cohort, an independent sleep deprivation cohort, and a chronic insomnia cohort.
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Has reproduction · 85
Predicting the pathogenicity of missense variants using features derived from AlphaFold2.
PMID 37084271 · PMC10203375 · Bioinformatics (Oxford, England) · 2023 · 6 claims · 8 setups
AlphaFold2-derived structural features (solvent accessibility, amino acid network features, physicochemical environment, pLDDT) can be used to train a random forest classifier (AlphScore) that distinguishes proxy-benign from proxy-pathogenic missense variants.
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Interaction profile-based protein classification of death domain.
PMID 15189571 · PMC459208 · BMC bioinformatics · 2004 · 7 claims · 6 setups
An SVM-based classifier using Residue Pair Interaction Profiles (RPIPs) can classify death domain superfamily members into subfamilies with 89% average cross-validation accuracy
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SePaCS--a web-based application for classification of seroreactivity profiles.
PMID 17478503 · PMC1933220 · Nucleic acids research · 2007 · 8 claims · 4 setups
SePaCS is a freely available web-based tool that trains and applies multiple classification methods (4 Naive Bayes variants, SVM with RBF kernel, LDA, DLDA) to seroreactivity profiles and outputs results as a summary table plus a detailed PDF report
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Has reproduction · 58
Identification of common genetic characteristics of rheumatoid arthritis and major depressive disorder by bioinformatics analysis and machine learning.
PMID 37415981 · PMC10320004 · Frontiers in immunology · 2023 · 7 claims · 8 setups
EAF1, SDCBP and RNF19B are common genetic characteristics (hub genes) shared by RA and MDD