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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Self-reported Taste and Smell Disorders in Patients with COVID-19: Distinct Features in China
This article has 14 authors:Reviewed by ScreenIT
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An enzyme-based immunodetection assay to quantify SARS-CoV-2 infection
This article has 13 authors:Reviewed by ScreenIT
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Characterization of the SARS-CoV-2 S Protein: Biophysical, Biochemical, Structural, and Antigenic Analysis
This article has 34 authors:Reviewed by ScreenIT
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SARS-CoV-2 D614G spike mutation increases entry efficiency with enhanced ACE2-binding affinity
This article has 12 authors:Reviewed by ScreenIT
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Pulmonary Toxicity and Inflammatory Response of Vape Cartridges Containing Medium-Chain Triglycerides Oil and Vitamin E Acetate: Implications in the Pathogenesis of EVALI
This article has 6 authors:Reviewed by ScreenIT
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Microscopy‐based assay for semi‐quantitative detection of SARS‐CoV‐2 specific antibodies in human sera
This article has 27 authors:Reviewed by ScreenIT
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Genome-wide mapping of SARS-CoV-2 RNA structures identifies therapeutically-relevant elements
This article has 11 authors:Reviewed by ScreenIT
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Interfacial Water Molecules Make RBD of SPIKE Protein and Human ACE2 to Stick Together
This article has 4 authors:Reviewed by ScreenIT
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In silico multi-epitope vaccine against covid19 showing effective interaction with HLA-B*15:03
This article has 20 authors:Reviewed by ScreenIT
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Single-cell screening of SARS-CoV-2 target cells in pets, livestock, poultry and wildlife
This article has 52 authors:Reviewed by ScreenIT