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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SARS-CoV2 (COVID-19) Structural/Evolution Dynamicome: Insights into functional evolution and human genomics
This article has 22 authors:Reviewed by ScreenIT
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Predicting the Immunogenicity of T cell epitopes: From HIV to SARS-CoV-2
This article has 7 authors:Reviewed by ScreenIT
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Unveiling diffusion pattern and structural impact of the most invasive SARS-CoV-2 spike mutation
This article has 8 authors:Reviewed by ScreenIT
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Identification of conserved epitopes in SARS-CoV-2 spike and nucleocapsid protein
This article has 4 authors:Reviewed by ScreenIT
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The Red Queen’s Crown: an evolutionary arms race between coronaviruses and mammalian species reflected in positive selection of the ACE2 receptor among many species
This article has 2 authors:Reviewed by ScreenIT
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Recombination in sarbecovirus lineage and mutations/insertions in spike protein are linked to the emergence and adaptation of SARS-CoV-2
This article has 2 authors:Reviewed by ScreenIT
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The Estimated Time-Varying Reproduction Numbers during the Ongoing Pandemic of the Coronavirus Disease 2019 (COVID-19) in 12 Selected Countries outside China
This article has 1 author:Reviewed by ScreenIT
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Automatic Detection of COVID-19 Infection from Chest X-ray using Deep Learning
This article has 3 authors:Reviewed by ScreenIT
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COVID-19: Easing the coronavirus lockdowns with caution
This article has 3 authors:Reviewed by ScreenIT
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Kawasaki-like multisystem inflammatory syndrome in children during the covid-19 pandemic in Paris, France: prospective observational study
This article has 15 authors:Reviewed by ScreenIT