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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Prediction and evolution of B cell epitopes of surface protein in SARS-CoV-2
This article has 5 authors:Reviewed by ScreenIT
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Atazanavir, Alone or in Combination with Ritonavir, Inhibits SARS-CoV-2 Replication and Proinflammatory Cytokine Production
This article has 18 authors:Reviewed by ScreenIT
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LY6E Restricts Entry of Human Coronaviruses, Including Currently Pandemic SARS-CoV-2
This article has 10 authors:Reviewed by ScreenIT
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Indomethacin has a potent antiviral activity against SARS CoV-2 in vitro and canine coronavirus in vivo
This article has 5 authors:Reviewed by ScreenIT
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Increasing testing throughput and case detection with a pooled-sample Bayesian approach in the context of COVID-19
This article has 2 authors:Reviewed by ScreenIT
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Iterative community-driven development of a SARS-CoV-2 tissue simulator
This article has 35 authors:Reviewed by ScreenIT
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SARS-CoV-2 and SARS-CoV differ in their cell tropism and drug sensitivity profiles
This article has 10 authors:Reviewed by ScreenIT
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Antiviral activities of type I interferons to SARS-CoV-2 infection
This article has 5 authors:Reviewed by ScreenIT
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One-step RNA extraction for RT-qPCR detection of 2019-nCoV
This article has 3 authors:Reviewed by ScreenIT
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Detecting SARS-CoV-2 at point of care: preliminary data comparing loop-mediated isothermal amplification (LAMP) to polymerase chain reaction (PCR)
This article has 11 authors:Reviewed by ScreenIT