ScreenIT
The Automated Screening Working Groups is a group of software engineers and biologists passionate about improving scientific manuscripts on a large scale. Our members have created tools that check for common problems in scientific manuscripts, including information needed to improve transparency and reproducibility. We have combined our tools into a single pipeline, called ScreenIT. We're currently using our tools to screen COVID preprints.
Latest preprint reviews
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Structure prediction of the druggable fragments in SARS-CoV-2 untranslated regions
This article has 22 authors:Reviewed by ScreenIT
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In vitro and computational analysis of the putative furin cleavage site (RRARS) in the divergent spike protein of the rodent coronavirus AcCoV-JC34 (sub-genus luchacovirus)
This article has 5 authors:Reviewed by ScreenIT
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Human Genetic Variants Associated with COVID-19 Severity are Enriched in Immune and Epithelium Regulatory Networks
This article has 4 authors:Reviewed by ScreenIT
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The rise and fall of SARS-CoV-2 variants and the mutational profile of Omicron
This article has 5 authors:Reviewed by ScreenIT
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Disrupted Peyer’s Patch Microanatomy in COVID-19 Including Germinal Centre Atrophy Independent of Local Virus
This article has 13 authors:Reviewed by ScreenIT
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Variable loss of antibody potency against SARS-CoV-2 B.1.1.529 (Omicron)
This article has 11 authors:Reviewed by ScreenIT
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SARS-CoV-2 variants of concern: spike protein mutational analysis and epitope for broad neutralization
This article has 19 authors:Reviewed by ScreenIT
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ACE2-containing defensosomes serve as decoys to inhibit SARS-CoV-2 infection
This article has 16 authors:Reviewed by ScreenIT
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Neutrophil profiles of pediatric COVID-19 and multisystem inflammatory syndrome in children
This article has 18 authors:Reviewed by ScreenIT
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How effective is vaccination protection?
This article has 2 authors:Reviewed by ScreenIT