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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Topoisomerase III-β is required for efficient replication of positive-sense RNA viruses
This article has 15 authors:Reviewed by ScreenIT
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In-Silico Evidence for a Two Receptor Based Strategy of SARS-CoV-2
This article has 11 authors:Reviewed by ScreenIT
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Broad anti-coronaviral activity of FDA approved drugs against SARS-CoV-2 in vitro and SARS-CoV in vivo
This article has 6 authors:Reviewed by ScreenIT
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Non-neuronal expression of SARS-CoV-2 entry genes in the olfactory system suggests mechanisms underlying COVID-19-associated anosmia
This article has 25 authors: -
Codon usage and evolutionary rates of the 2019-nCoV genes
This article has 5 authors:Reviewed by ScreenIT
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Computational simulations reveal the binding dynamics between human ACE2 and the receptor binding domain of SARS‐CoV‐2 spike protein
This article has 7 authors:Reviewed by ScreenIT
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Structure-Based Modeling of SARS-CoV-2 Peptide/HLA-A02 Antigens
This article has 2 authors:Reviewed by ScreenIT
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The effects of containment measures in the Italian outbreak of COVID-19
This article has 5 authors:Reviewed by ScreenIT
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Immune cell profiling of COVID-19 patients in the recovery stage by single-cell sequencing
This article has 18 authors:Reviewed by ScreenIT
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ACE2 Expression Is Increased in the Lungs of Patients With Comorbidities Associated With Severe COVID-19
This article has 9 authors:Reviewed by ScreenIT