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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What is the effect of lockdown upon hospitalisation because of COVID‐19 amongst patients from a heart failure registry?
This article has 5 authors:Reviewed by ScreenIT
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Clonal analysis of immunodominance and cross-reactivity of the CD4 T cell response to SARS-CoV-2
This article has 19 authors:Reviewed by ScreenIT
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Understanding the B and T cell epitopes of spike protein of severe acute respiratory syndrome coronavirus-2: A computational way to predict the immunogens
This article has 3 authors:Reviewed by ScreenIT
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Comparative host interactomes of the SARS-CoV-2 nonstructural protein 3 and human coronavirus homologs
This article has 3 authors:Reviewed by ScreenIT
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Impact of SARS-CoV-2 variants on the total CD4+ and CD8+ T cell reactivity in infected or vaccinated individuals
This article has 21 authors:Reviewed by ScreenIT
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Stapled Peptides Based on Human Angiotensin-Converting Enzyme 2 (ACE2) Potently Inhibit SARS-CoV-2 Infection In Vitro
This article has 8 authors:Reviewed by ScreenIT
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Sequence signatures of two public antibody clonotypes that bind SARS-CoV-2 receptor binding domain
This article has 13 authors:Reviewed by ScreenIT
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An international comparison of age and sex dependency of COVID-19 deaths in 2020: a descriptive analysis
This article has 4 authors:Reviewed by ScreenIT
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Brain Networks Associated With COVID-19 Risk: Data From 3,662 Participants
This article has 1 author:Reviewed by ScreenIT
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VGsim: Scalable viral genealogy simulator for global pandemic
This article has 6 authors:Reviewed by ScreenIT