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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Structure-based screening of drug candidates targeting the SARS-CoV-2 envelope protein
This article has 5 authors:Reviewed by ScreenIT
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Structural analysis of receptor binding domain mutations in SARS-CoV-2 variants of concern that modulate ACE2 and antibody binding
This article has 11 authors:Reviewed by ScreenIT
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Discordant humoral and T cell immune responses to SARS-CoV-2 vaccination in people with multiple sclerosis on anti-CD20 therapy
This article has 10 authors:Reviewed by ScreenIT
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Epitopedia: identifying molecular mimicry between pathogens and known immune epitopes
This article has 11 authors:Reviewed by ScreenIT
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An Intranasal OMV-Based Vaccine Induces High Mucosal and Systemic Protecting Immunity Against a SARS-CoV-2 Infection
This article has 5 authors:Reviewed by ScreenIT
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Mental Health and Substance Use Associated with Hospitalization among People with COVID-19: A Population-Based Cohort Study
This article has 13 authors:Reviewed by ScreenIT
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Global disparities in SARS-CoV-2 genomic surveillance
This article has 214 authors:Reviewed by ScreenIT
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The unequal burden of the Covid-19 pandemic: Capturing racial/ethnic disparities in US cause-specific mortality
This article has 4 authors:Reviewed by Rapid Reviews Infectious Diseases, ScreenIT
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Population impact of SARS-CoV-2 variants with enhanced transmissibility and/or partial immune escape
This article has 5 authors:Reviewed by ScreenIT
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Reduction in initiations of HIV treatment in South Africa during the COVID pandemic
This article has 6 authors:Reviewed by ScreenIT