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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SARS-CoV-2 and ORF3a: Non-Synonymous Mutations and Polyproline Regions
This article has 5 authors:Reviewed by ScreenIT
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Correlation between universal BCG vaccination policy and reduced mortality for COVID-19
This article has 6 authors:Reviewed by ScreenIT
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SARS-CoV-2 Proteome Microarray for Mapping COVID-19 Antibody Interactions at Amino Acid Resolution
This article has 12 authors:Reviewed by ScreenIT
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Re-analysis of SARS-CoV-2-infected host cell proteomics time-course data by impact pathway analysis and network analysis: a potential link with inflammatory response
This article has 2 authors:Reviewed by ScreenIT
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RNA genome conservation and secondary structure in SARS-CoV-2 and SARS-related viruses: a first look
This article has 7 authors:Reviewed by ScreenIT
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The Nucleocapsid Protein of SARS-CoV-2 Abolished Pluripotency in Human Induced Pluripotent Stem Cells
This article has 9 authors:Reviewed by ScreenIT
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Structure-Based Design, Synthesis and Biological Evaluation of Peptidomimetic Aldehydes as a Novel Series of Antiviral Drug Candidates Targeting the SARS-CoV-2 Main Protease
This article has 27 authors:Reviewed by ScreenIT
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Acute gastrointestinal injury in critically ill patients with COVID-19 in Wuhan, China
This article has 10 authors:Reviewed by ScreenIT
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Anti-hypertensive Angiotensin II receptor blockers associated to mitigation of disease severity in elderly COVID-19 patients
This article has 18 authors:Reviewed by ScreenIT
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A special case of COVID-19 with long duration of viral shedding for 49 days
This article has 9 authors:Reviewed by ScreenIT