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
Artificial Intelligence Meets Whole Slide Images: Deep Learning Model Shapes an Immune-Hot Tumor and Guides Precision Therapy in Bladder Cancer.
PMID 36245985 · PMC9553530 · Journal of oncology · 2022 · 6 claims · 8 setups
A deep learning WSI cluster (three-class mini batch K-means on Inception V3 features) is associated with overall survival (P<0.001) and is an independent prognostic predictor (P=0.031) in BLCA.
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Has reproduction · 79
Interpretable prediction models for widespread m6A RNA modification across cell lines and tissues.
PMID 37995291 · PMC10697738 · Bioinformatics (Oxford, England) · 2023 · 7 claims · 6 setups
CLSM6A, a CNN-based model set, predicts single-nucleotide-resolution m6A RNA modification sites across eight cell lines and three tissues in H. sapiens
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Has reproduction · 67
Adaptive learning embedding features to improve the predictive performance of SARS-CoV-2 phosphorylation sites.
PMID 37847658 · PMC10628388 · Bioinformatics (Oxford, England) · 2023 · 7 claims · 3 setups
PSPred-ALE, a deep learning predictor using a self-adaptive learning embedding algorithm, automatically extracts contextual sequence features and identifies SARS-CoV-2 phosphorylation sites without feature engineering.
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Has reproduction
Developing a thyroid cancer differentiation state classification system using deep residual networks and metabolic signature profiling.
PMID 40993300 · PMC12460824 · NPJ digital medicine · 2025 · 8 claims · 7 setups
A ResNet classifier built on a 10-gene metabolic signature distinguishes all thyroid cancer differentiation states with ~92.7% average accuracy.
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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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Full-text index only
In silico analysis of missense substitutions using sequence-alignment based methods.
PMID 18951440 · PMC3431198 · Human mutation · 2008 · 8 claims · 7 setups
Carefully validated PMSA-based computational algorithms can achieve predictive values of ~75-95% for classifying missense substitutions as pathogenic or neutral.