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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Multi-pronged human protein mimicry by SARS-CoV-2 reveals bifurcating potential for MHC detection and immune evasion
This article has 6 authors:Reviewed by ScreenIT
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Cross-neutralization activity against SARS-CoV-2 is present in currently available intravenous immunoglobulins
This article has 10 authors:Reviewed by ScreenIT
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Proteotyping SARS-CoV-2 virus from nasopharyngeal swabs: a proof-of-concept focused on a 3 min mass spectrometry window
This article has 11 authors:Reviewed by ScreenIT
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Nucleocapsid protein of SARS-CoV-2 phase separates into RNA-rich polymerase-containing condensates
This article has 4 authors:Reviewed by ScreenIT
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An in-silico based clinical insight on the effect of noticeable CD4 conserved residues of SARS-CoV-2 on the CD4-MHC-II interactions
This article has 4 authors:Reviewed by ScreenIT
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Mechanism and inhibition of SARS-CoV-2 PLpro
This article has 28 authors:Reviewed by ScreenIT
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Identification of a critical horseshoe-shaped region in the nsp5 (Mpro, 3CLpro) protease interdomain loop (IDL) of coronavirus mouse hepatitis virus (MHV)
This article has 9 authors:Reviewed by ScreenIT
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Drug repurposing screens reveal FDA approved drugs active against SARS-Cov-2
This article has 10 authors:Reviewed by ScreenIT
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“Acute Respiratory Distress and Cytokine Storm in Aged, SARS-CoV-2 Infected African Green Monkeys, but not in Rhesus Macaques”
This article has 26 authors:Reviewed by ScreenIT
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Estimation of the incubation period of COVID-19 using viral load data
This article has 12 authors:Reviewed by ScreenIT