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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Discovery of potent inhibitors of PL pro CoV2 by screening a library of selenium-containing compounds
This article has 5 authors:Reviewed by ScreenIT
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Type I and Type III Interferons Restrict SARS-CoV-2 Infection of Human Airway Epithelial Cultures
This article has 21 authors:Reviewed by ScreenIT
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Prediction of the incubation period for COVID-19 and future virus disease outbreaks
This article has 4 authors:Reviewed by ScreenIT
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A panel of human neutralizing mAbs targeting SARS-CoV-2 spike at multiple epitopes
This article has 23 authors:Reviewed by ScreenIT
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A Multiple Peptides Vaccine against nCOVID-19 Designed from the Nucleocapsid phosphoprotein (N) and Spike Glycoprotein (S) via the Immunoinformatics Approach
This article has 8 authors:Reviewed by ScreenIT
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SARS ‐CoV‐2 targets neurons of 3D human brain organoids
This article has 23 authors:Reviewed by ScreenIT
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A Replication-Competent Vesicular Stomatitis Virus for Studies of SARS-CoV-2 Spike-Mediated Cell Entry and Its Inhibition
This article has 23 authors:Reviewed by ScreenIT
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Intra-host variation and evolutionary dynamics of SARS-CoV-2 populations in COVID-19 patients
This article has 34 authors:Reviewed by ScreenIT
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Clinical and Analytical Performance of an Automated Serological Test That Identifies S1/S2-Neutralizing IgG in COVID-19 Patients Semiquantitatively
This article has 14 authors:Reviewed by ScreenIT
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Potential CD8+ T Cell Cross-Reactivity Against SARS-CoV-2 Conferred by Other Coronavirus Strains
This article has 8 authors:Reviewed by ScreenIT