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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Device-assessed sleep and physical activity in individuals recovering from a hospital admission for COVID-19: a prospective, multicentre study
Reviewed by ScreenIT
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ImmunoTyper-SR: A computational approach for genotyping immunoglobulin heavy chain variable genes using short-read data
This article has 33 authors:Reviewed by ScreenIT
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Toward Atomistic Models of Intact SARS-CoV-2 via Martini Coarse-Grained Molecular Dynamics Simulations
This article has 6 authors:Reviewed by ScreenIT
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Mapping the Evolutionary Space of SARS-CoV-2 Variants to Anticipate Emergence of Subvariants Resistant to COVID-19 Therapeutics
This article has 12 authors:Reviewed by ScreenIT
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How concerning is a SARS-CoV-2 variant of concern? Computational predictions and the variants labeling system
This article has 8 authors:Reviewed by ScreenIT
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Metabolic dyshomeostasis induced by SARS-CoV-2 structural proteins reveals immunological insights into viral olfactory interactions
This article has 11 authors:Reviewed by ScreenIT
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CLEC5A and TLR2 are critical in SARS-CoV-2-induced NET formation and lung inflammation
This article has 6 authors:Reviewed by ScreenIT
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Detection and Interspecies Comparison of SARS-CoV-2 Delta Variant (AY.3) in Feces from a Domestic Cat and Human Samples
This article has 9 authors:Reviewed by ScreenIT
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Comparative complete scheme and booster effectiveness of COVID-19 vaccines in preventing SARS-CoV-2 infections with SARS-CoV-2 Omicron (BA.1) and Delta (B.1.617.2) variants
This article has 10 authors:Reviewed by ScreenIT
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Design and development of potent h-ACE2 derived peptide mimetics in SARS-CoV-2 Omicron variant therapeutics
This article has 3 authors:Reviewed by ScreenIT