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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Unique molecular signatures sustained in circulating monocytes and regulatory T cells in convalescent COVID-19 patients
This article has 23 authors:Reviewed by ScreenIT
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Identification of consensus hairpin loop structure among the negative sense sub-genomic RNAs of SARS-CoV-2
This article has 2 authors:Reviewed by ScreenIT
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Mosaic RBD nanoparticles protect against multiple sarbecovirus challenges in animal models
This article has 22 authors:Reviewed by ScreenIT
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A rapid, high-throughput, viral infectivity assay using automated brightfield microscopy with machine learning
This article has 11 authors:Reviewed by ScreenIT
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An engineered ACE2 decoy receptor can be administered by inhalation and potently targets the BA.1 and BA.2 omicron variants of SARS-CoV-2
This article has 11 authors:Reviewed by ScreenIT
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Genetically Engineered MRI-Trackable Extracellular Vesicles as SARS-CoV-2 Mimetics for Mapping ACE2 Binding In Vivo
This article has 10 authors:Reviewed by ScreenIT
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A SARS-CoV-2 Spike Ferritin Nanoparticle Vaccine Is Protective and Promotes a Strong Immunological Response in the Cynomolgus Macaque Coronavirus Disease 2019 (COVID-19) Model
This article has 44 authors:Reviewed by ScreenIT
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The interplay between lncRNAs, RNA-binding proteins and viral genome during SARS-CoV-2 infection reveals strong connections with regulatory events involved in RNA metabolism and immune response
This article has 16 authors:Reviewed by ScreenIT
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Monitoring of the SARS-CoV-2 Omicron BA.1/BA.2 lineage transition in the Swedish population reveals increased viral RNA levels in BA.2 cases
This article has 4 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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B cell receptor repertoire analysis unveils dynamic antibody response and severity markers in COVID-19 patients
This article has 4 authors:Reviewed by ScreenIT