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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A database resource for Genome-wide dynamics analysis of Coronaviruses on a historical and global scale
This article has 3 authors:Reviewed by ScreenIT
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ACE2 expression by colonic epithelial cells is associated with viral infection, immunity and energy metabolism
This article has 18 authors:Reviewed by ScreenIT
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Doubling Time of the COVID-19 Epidemic by Province, China
This article has 12 authors:Reviewed by ScreenIT
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Network-based drug repurposing for novel coronavirus 2019-nCoV/SARS-CoV-2
This article has 6 authors:Reviewed by ScreenIT
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Forecasting the Wuhan coronavirus (2019-nCoV) epidemics using a simple (simplistic) model
This article has 1 author:Reviewed by ScreenIT
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Population Movement, City Closure in Wuhan, and Geographical Expansion of the COVID-19 Infection in China in January 2020
This article has 12 authors:Reviewed by ScreenIT
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Assessing spread risk of COVID-19 in early 2020
This article has 9 authors:Reviewed by ScreenIT
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Integrative Bioinformatics Analysis Provides Insight into the Molecular Mechanisms of 2019-nCoV
This article has 8 authors:Reviewed by ScreenIT
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Risk Assessment of Novel Coronavirus COVID-19 Outbreaks Outside China
This article has 6 authors:Reviewed by ScreenIT
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Distinguishing viruses responsible for influenza-like illness
This article has 7 authors:Reviewed by ScreenIT