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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Epidemiologic and evolutionary relationships between Romanian and Brazilian HIV-subtype F strains.
PMID 8903171 · PMC2626880 · Emerging infectious diseases · 1995 · 7 claims · 4 setups
Romanian and Brazilian HIV-1 subtype F envelope C2-V3 sequences cluster into two related but distinct phylogenetic groups.
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Direct evidence of extensive diversity of HIV-1 in Kinshasa by 1960.
PMID 18833279 · PMC3682493 · Nature · 2008 · 7 claims · 8 setups
Recovered and characterized HIV-1 sequences (DRC60) from a 1960 Bouin's-fixed paraffin-embedded lymph node biopsy from Léopoldville, Belgian Congo
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Synonymous substitution rates predict HIV disease progression as a result of underlying replication dynamics.
PMID 17305421 · PMC1797821 · PLoS computational biology · 2007 · 8 claims · 8 setups
The synonymous substitution rate (dS) of HIV env is strongly correlated with disease progression parameters (progression time, CD4+ decline rate, viral load increase rate), unlike the nonsynonymous rate (dN).
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Timing constraints of in vivo gag mutations during primary HIV-1 subtype C infection.
PMID 19890401 · PMC2768328 · PloS one · 2009 · 7 claims · 7 setups
Reverse mutations to the wild type (HIV-1C consensus) in Gag appear significantly earlier than escape mutations from the wild type during primary infection
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Has reproduction · 78
QuasiFlow: a Nextflow pipeline for analysis of NGS-based HIV-1 drug resistance data.
PMID 36699347 · PMC9722223 · Bioinformatics advances · 2022 · 6 claims · 8 setups
QuasiFlow is a Nextflow pipeline that runs entirely locally via command-line tools and a local HIVdb database copy to analyze NGS-based HIV-1 drug resistance testing data.
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Has reproduction · 94
Deep learning from phylogenies to uncover the epidemiological dynamics of outbreaks.
PMID 35794110 · PMC9258765 · Nature communications · 2022 · 8 claims · 5 setups
Deep learning (FFNN-SS and CNN-CBLV) enables accurate and fast likelihood-free estimation of epidemiological parameters and model selection from phylogenies