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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Angiotensin-converting enzymes (ACE, ACE2) gene variants and COVID-19 outcome
This article has 17 authors:Reviewed by ScreenIT
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Remdesivir but not famotidine inhibits SARS-CoV-2 replication in human pluripotent stem cell-derived intestinal organoids
This article has 13 authors:Reviewed by ScreenIT
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ROBOCOV: An affordable open-source robotic platform for SARS-CoV-2 testing by RT-qPCR
This article has 7 authors:Reviewed by ScreenIT
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COVID-19 Variants Database: A repository for Human SARS-CoV-2 Polymorphism Data
This article has 6 authors:Reviewed by ScreenIT
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Investigation of the Effect of Temperature on the Structure of SARS-CoV-2 Spike Protein by Molecular Dynamics Simulations
This article has 2 authors:Reviewed by ScreenIT
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Hijacking SARS-Cov-2/ACE2 receptor interaction by natural and semi-synthetic steroidal agents acting on functional pockets on receptor binding region
This article has 13 authors:Reviewed by ScreenIT
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Chimeric synthetic reference standards enable cross-validation of positive and negative controls in SARS-CoV-2 molecular tests
This article has 5 authors:Reviewed by ScreenIT
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Transmission Dynamics of COVID-19 and Impact on Public Health Policy
This article has 5 authors:Reviewed by ScreenIT
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The Pathogenicity of SARS-CoV-2 in hACE2 Transgenic Mice
This article has 49 authors:Reviewed by ScreenIT
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Pericyte-specific vascular expression of SARS-CoV-2 receptor ACE2 – implications for microvascular inflammation and hypercoagulopathy in COVID-19
This article has 32 authors:Reviewed by ScreenIT