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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Molecular Dynamics Simulations Studies On The Effects Of Mutations On The Binding Affinities Between SARS-CoV-2 Spike RBD And Human ACE2
This article has 2 authors:Reviewed by ScreenIT
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Relation of Incident Type 1 Diabetes to Recent COVID-19 Infection: Cohort Study Using e-Health Record Linkage in Scotland
This article has 10 authors:Reviewed by ScreenIT
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Cell delivery peptides for small interfering RNAs targeting SARS-CoV-2 new variants through a bioinformatics and deep learning design
This article has 3 authors:Reviewed by ScreenIT
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The rise and fall of SARS-CoV-2 variants and the emergence of competing Omicron lineages
This article has 5 authors:Reviewed by ScreenIT
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SARS-CoV-2 Nsp1 N-terminal and linker regions as a platform for host translational shutoff
This article has 5 authors:Reviewed by ScreenIT
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Remdesivir and GS-441524 Retain Antiviral Activity against Delta, Omicron, and Other Emergent SARS-CoV-2 Variants
This article has 18 authors:Reviewed by ScreenIT
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Dual Inhibition of Cathepsin L and 3CL-Pro by GC-376 Constrains SARS Cov2 Infection Including Omicron Variant
This article has 11 authors:Reviewed by ScreenIT
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Epigenetic memory of coronavirus infection in innate immune cells and their progenitors
This article has 55 authors:Reviewed by ScreenIT
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Severe Acute Respiratory Syndrome Coronavirus 2 Neutralization After Messenger RNA Vaccination and Variant Breakthrough Infection
This article has 14 authors:Reviewed by ScreenIT
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Predicting Epitope Candidates for SARS-CoV-2
This article has 10 authors:Reviewed by ScreenIT