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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The unmitigated profile of COVID-19 infectiousness
This article has 6 authors:This article has been curated by 1 group: -
Germinal centre-driven maturation of B cell response to SARS-CoV-2 vaccination
This article has 21 authors:Reviewed by ScreenIT
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Multiple spillovers from humans and onward transmission of SARS-CoV-2 in white-tailed deer
This article has 18 authors:Reviewed by ScreenIT
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Global Mutational Sweep of SARS-CoV-2: From Chaos to Order
This article has 8 authors:Reviewed by ScreenIT
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Modelling the response to vaccine in non-human primates to define SARS-CoV-2 mechanistic correlates of protection
This article has 23 authors:This article has been curated by 1 group: -
Profiling RT-LAMP tolerance of sequence variation for SARS-CoV-2 RNA detection
This article has 3 authors:Reviewed by ScreenIT
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Predicting SARS-CoV-2 epitope-specific TCR recognition using pre-trained protein embeddings
This article has 2 authors:Reviewed by ScreenIT
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Coronavirus RNA Synthesis Takes Place within Membrane-Bound Sites
This article has 4 authors:Reviewed by ScreenIT
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SARS-CoV-2 triggered excessive inflammation and abnormal energy metabolism in gut microbiota
This article has 18 authors:Reviewed by ScreenIT
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Variations in Cell Surface ACE2 Levels Alter Direct Binding of SARS-CoV-2 Spike Protein and Viral Infectivity: Implications for Measuring Spike Protein Interactions with Animal ACE2 Orthologs
This article has 6 authors:Reviewed by ScreenIT