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 · 71
Transcriptome and machine learning analysis of the impact of COVID-19 on mitochondria and multiorgan damage.
PMID 38295140 · PMC10830027 · PloS one · 2024 · 6 claims · 7 setups
Potential cardiac, hepatic, and renal impairments in COVID-19 are associated with ACE2, inflammatory cytokine storms, and mitochondrial pathways.
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Has reproduction · 100
miRbiom: Machine-learning on Bayesian causal nets of RBP-miRNA interactions successfully predicts miRNA profiles.
PMID 34637468 · PMC8509996 · PloS one · 2021 · 7 claims · 6 setups
RBPs beyond Drosha/DGCR8/Dicer are involved in regulating miRNA biogenesis and explain its spatio-temporal nature
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Has reproduction
Unlocking the microbial studies through computational approaches: how far have we reached?
PMID 36920617 · PMC10016191 · Environmental science and pollution research international · 2023 · 8 claims · 8 setups
Metagenomics enables culture-independent study of microbial communities directly from their natural environments, bypassing the need for clonal isolation.
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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 · 71
Gene Set Enrichment Analysis Reveals Individual Variability in Host Responses in Tuberculosis Patients.
PMID 34421903 · PMC8375662 · Frontiers in immunology · 2021 · 8 claims · 8 setups
TB patients show substantial individual variability in the intensity of hallmark IFN responses, as well as in complement system, metabolic, and other pathway responses.
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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