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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Cryo-EM Structure of the 2019-nCoV Spike in the Prefusion Conformation
This article has 8 authors:Reviewed by ScreenIT
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Long-Term Persistence of IgG Antibodies in SARS-CoV Infected Healthcare Workers
This article has 8 authors:Reviewed by ScreenIT
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Structural genomics and interactomics of 2019 Wuhan novel coronavirus, 2019-nCoV, indicate evolutionary conserved functional regions of viral proteins
This article has 9 authors:Reviewed by ScreenIT
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Identification of a pangolin niche for a 2019-nCoV-like coronavirus through an extensive meta-metagenomic search
This article has 7 authors:Reviewed by ScreenIT
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Single-cell RNA expression profiling of ACE2, the putative receptor of Wuhan 2019-nCoV, in the nasal tissue
This article has 4 authors:Reviewed by ScreenIT
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Potentially highly potent drugs for 2019-nCoV
This article has 5 authors:Reviewed by ScreenIT
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Evidence of recombination in coronaviruses implicating pangolin origins of nCoV-2019
This article has 4 authors:Reviewed by ScreenIT
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Glycopeptide antibiotic teicoplanin inhibits cell entry of SARS-CoV-2 by suppressing the proteolytic activity of cathepsin L
This article has 26 authors:Reviewed by ScreenIT
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Serial interval of novel coronavirus (COVID-19) infections
This article has 3 authors:Reviewed by ScreenIT
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Data-based analysis, modelling and forecasting of the COVID-19 outbreak
This article has 4 authors:Reviewed by ScreenIT