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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Genome-wide analysis provides genetic evidence that ACE2 influences COVID-19 risk and yields risk scores associated with severe disease
This article has 171 authors:Reviewed by ScreenIT
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An ACE2 Microbody Containing a Single Immunoglobulin Fc Domain Is a Potent Inhibitor of SARS-CoV-2
This article has 10 authors:Reviewed by ScreenIT
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Graduate students significantly more concerned than undergraduates about returning to campus in the era of COVID-19
This article has 3 authors:Reviewed by ScreenIT
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Baricitinib treatment resolves lower-airway macrophage inflammation and neutrophil recruitment in SARS-CoV-2-infected rhesus macaques
This article has 45 authors:Reviewed by ScreenIT
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Evaluating social and spatial inequalities of large scale rapid lateral flow SARS-CoV-2 antigen testing in COVID-19 management: An observational study of Liverpool, UK (November 2020 to January 2021)
This article has 9 authors:Reviewed by ScreenIT
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Modelling COVID-19 transmission in a hemodialysis centre using simulation generated contacts matrices
This article has 9 authors:Reviewed by ScreenIT
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A Peptide Vaccine Candidate Tailored to Individuals' Genetics Mimics the Multi-Targeted T Cell Immunity of COVID-19 Convalescent Subjects
This article has 12 authors:Reviewed by ScreenIT
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Covid-19 Pandemic Data Analysis and Forecasting using Machine Learning Algorithms
This article has 3 authors:Reviewed by ScreenIT
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Resource allocation for different types of vaccines against COVID-19: Tradeoffs and synergies between efficacy and reach
This article has 4 authors:Reviewed by ScreenIT
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Lifelines COVID-19 cohort: investigating COVID-19 infection and its health and societal impacts in a Dutch population-based cohort
This article has 31 authors:Reviewed by ScreenIT