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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Behaviours and attitudes in response to the COVID-19 pandemic: insights from a cross-national Facebook survey
This article has 7 authors:Reviewed by ScreenIT
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Impact of delays on effectiveness of contact tracing strategies for COVID-19: a modelling study
This article has 6 authors:Reviewed by ScreenIT
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Recommendations for sample pooling on the Cepheid GeneXpert ® system using the Cepheid Xpert ® Xpress SARS-CoV-2 assay
This article has 6 authors:Reviewed by ScreenIT
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Distribution of ACE2, CD147, cyclophilins, CD26 and other SARS-CoV-2 associated molecules in human tissues and immune cells in health and disease
This article has 18 authors:Reviewed by ScreenIT
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Sequence characterization and molecular modeling of clinically relevant variants of the SARS-CoV-2 main protease
This article has 8 authors:Reviewed by ScreenIT
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IgA MAb blocks SARS-CoV-2 Spike-ACE2 interaction providing mucosal immunity
This article has 17 authors:Reviewed by ScreenIT
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Two mutations P/L and Y/C in SARS-CoV-2 helicase domain exist together and influence helicase RNA binding
This article has 4 authors:Reviewed by ScreenIT
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Expression of ACE2 and TMPRSS2 proteins in the upper and lower aerodigestive tracts of rats
This article has 6 authors:Reviewed by ScreenIT
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Traffic-derived particulate matter and angiotensin-converting enzyme 2 expression in human airway epithelial cells
This article has 4 authors:Reviewed by ScreenIT
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Phylogenetic Analysis of SARS-CoV-2 Genomes in Turkey
This article has 7 authors:Reviewed by ScreenIT