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 · 95
In vivo structural characterization of the SARS-CoV-2 RNA genome identifies host proteins vulnerable to repurposed drugs.
PMID 33636127 · PMC7871767 · Cell · 2021 · 8 claims · 8 setups
icSHAPE was used to determine the in vivo and in vitro structural landscape of the SARS-CoV-2 RNA genome in infected Huh7.5.1 cells, plus UTR structures of six other coronaviruses
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Has reproduction · 100
Intra-Host Co-Existing Strains of SARS-CoV-2 Reference Genome Uncovered by Exhaustive Computational Search.
PMID 37243151 · PMC10224212 · Viruses · 2023 · 8 claims · 7 setups
An exhaustive-search workflow can recover intra-host co-existing SARS-CoV-2 strains from the reference-genome read set (SRR11092062) that de Bruijn-graph assemblers discard.
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Has reproduction · 63
Target identification for repurposed drugs active against SARS-CoV-2 via high-throughput inverse docking.
PMID 34825285 · PMC8616721 · Journal of computer-aided molecular design · 2022 · 8 claims · 6 setups
Combining Vinardo, Ledock, and Korp-PL scoring functions (via averaged Z-scores) improves correct target identification over any single scoring function.
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Has reproduction · 87
Inhibition of SARS-CoV-2 Infections in Engineered Human Tissues Using Clinical-Grade Soluble Human ACE2.
PMID 32333836 · PMC7181998 · Cell · 2020 · 8 claims · 7 setups
Clinical-grade hrsACE2 significantly inhibits SARS-CoV-2 infection of Vero-E6 cells in a dose-dependent manner
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Has reproduction · 85
Single-Cell Differential Network Analysis with Sparse Bayesian Factor Models.
PMID 35186014 · PMC8855158 · Frontiers in genetics · 2021 · 8 claims · 2 setups
A hierarchical Bayesian factor model using treatment-dependent latent factor loadings can construct gene co-expression networks from scRNA-seq data and identify differences in network structure between two (or more) biological conditions.