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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Remdesivir, Molnupiravir and Nirmatrelvir remain active against SARS-CoV-2 Omicron and other variants of concern
This article has 10 authors:Reviewed by ScreenIT
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Deciphering the quality of SARS‐CoV‐2 specific T‐cell response associated with disease severity, immune memory and heterologous response
This article has 26 authors:Reviewed by ScreenIT
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Comparative analysis of single cell lung atlas of bat, cat, tiger, and pangolin
This article has 16 authors:Reviewed by ScreenIT
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Mapping the allosteric effects that define functional activity of SARS-CoV-2 specific antibodies
This article has 16 authors:Reviewed by ScreenIT
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Peptide-based epitope design on non-structural proteins of SARS-CoV-2
This article has 5 authors:Reviewed by ScreenIT
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Functional properties of the spike glycoprotein of the emerging SARS-CoV-2 variant B.1.1.529
This article has 9 authors:Reviewed by ScreenIT
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Post COVID-19 1 st Dose Vaccination Common Symptoms among SE Asia College Students
This article has 3 authors:Reviewed by ScreenIT
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Breakthrough SARS-CoV-2 infections after COVID-19 mRNA vaccination in MS patients on disease modifying therapies during the Delta and the Omicron waves in Italy
This article has 119 authors:Reviewed by ScreenIT
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Forecasting COVID-19 Infection Trends and New Hospital Admissions in Spain due to SARS-CoV-2 Variant of Concern Omicron
This article has 4 authors:Reviewed by ScreenIT
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Topological data analysis identifies distinct biomarker phenotypes during the ‘inflammatory’ phase of COVID-19
This article has 28 authors:Reviewed by ScreenIT