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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Meta-Analysis and Structural Dynamics of the Emergence of Genetic Variants of SARS-CoV-2
This article has 3 authors:Reviewed by ScreenIT
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High-content screening of coronavirus genes for innate immune suppression reveals enhanced potency of SARS-CoV-2 proteins
This article has 22 authors:Reviewed by ScreenIT
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Is WHO International Standard for Anti-SARS-CoV-2 Immunoglobulin Clinically Useful?
This article has 8 authors:Reviewed by ScreenIT
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Factors Associated with Emerging and Re-emerging of SARS-CoV-2 Variants
This article has 9 authors:Reviewed by ScreenIT
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A robust SARS-CoV-2 replication model in primary human epithelial cells at the air liquid interface to assess antiviral agents
This article has 11 authors:Reviewed by ScreenIT
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Identifying SARS-CoV-2 antiviral compounds by screening for small molecule inhibitors of Nsp3 papain-like protease
This article has 19 authors:Reviewed by ScreenIT
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Analysis of accumulated SARS-CoV-2 seroconversion in North Carolina: The COVID-19 Community Research Partnership
This article has 23 authors:Reviewed by ScreenIT
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Investigating the first stage of the COVID-19 pandemic in Ukraine using epidemiological and genomic data
This article has 7 authors:Reviewed by ScreenIT
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Large-scale analysis of SARS-CoV-2 synonymous mutations reveals the adaptation to the human codon usage during the virus evolution
This article has 10 authors:Reviewed by ScreenIT
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Targeted Drug Repurposing Against the SARS-CoV-2 E channel Identifies Blockers With in vitro Antiviral Activity
This article has 3 authors:Reviewed by ScreenIT