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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Virus-Receptor Interactions of Glycosylated SARS-CoV-2 Spike and Human ACE2 Receptor
This article has 16 authors:Reviewed by ScreenIT
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In situ structural analysis of SARS-CoV-2 spike reveals flexibility mediated by three hinges
This article has 20 authors:Reviewed by ScreenIT
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Using nucleocapsid proteins to investigate the relationship between SARS-CoV-2 and closely related bat and pangolin coronaviruses
This article has 1 author:Reviewed by ScreenIT
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A cytosine-to-uracil change within the programmed -1 ribosomal frameshift signal of SARS-CoV-2 results in structural similarities with the MERS-CoV signal
This article has 2 authors:Reviewed by ScreenIT
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Glycans on the SARS-CoV-2 Spike Control the Receptor Binding Domain Conformation
This article has 8 authors:Reviewed by ScreenIT
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Population Bottlenecks and Intra-host Evolution During Human-to-Human Transmission of SARS-CoV-2
This article has 32 authors:Reviewed by ScreenIT
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Ag nanoparticles-based antimicrobial polycotton fabrics to prevent the transmission and spread of SARS-CoV-2
This article has 14 authors:Reviewed by ScreenIT
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Elucidation of the antiviral mechanism of cystine and theanine through transcriptome analysis of mice and comparison with COVID-19 gene set data
This article has 6 authors:Reviewed by ScreenIT
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Neighbourhood income and physical distancing during the COVID-19 pandemic in the United States
This article has 7 authors:Reviewed by ScreenIT
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Ethnic variation in outcome of people hospitalised during the first COVID-19 epidemic wave in Wales (UK): an analysis of national surveillance data using Onomap, a name-based ethnicity classification tool
This article has 10 authors:Reviewed by ScreenIT