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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Open science saves lives: lessons from the COVID-19 pandemic
This article has 9 authors: -
Free fatty acid binding pocket in the locked structure of SARS-CoV-2 spike protein
This article has 16 authors:Reviewed by ScreenIT
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Self-assembling SARS-CoV-2 nanoparticle vaccines targeting the S protein induces protective immunity in mice
This article has 11 authors:Reviewed by ScreenIT
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Monitoring the propagation of SARS CoV2 variants by tracking identified mutation in wastewater using specific RT-qPCR
This article has 10 authors:Reviewed by ScreenIT
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CD8+ T cell epitope variations suggest a potential antigen presentation deficiency for spike protein of SARS-CoV-2
This article has 17 authors:Reviewed by ScreenIT
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A novel antibody against the furin cleavage site of SARS-CoV-2 spike protein: Effects on proteolytic cleavage and ACE2 binding
This article has 3 authors:Reviewed by ScreenIT
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Comparing COVID-19 risk factors in Brazil using machine learning: the importance of socioeconomic, demographic and structural factors
This article has 6 authors:Reviewed by ScreenIT
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MARCH8 Targets Cytoplasmic Lysine Residues of Various Viral Envelope Glycoproteins
This article has 8 authors:Reviewed by ScreenIT
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Smoking and COVID-19: A two-sample Mendelian randomization study
This article has 2 authors:Reviewed by ScreenIT
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Allelic variation in Class I HLA determines pre-existing memory responses to SARS-CoV-2 that shape the CD8 + T cell repertoire upon viral exposure
This article has 35 authors:Reviewed by ScreenIT