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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Mutation Y453F in the spike protein of SARS-CoV-2 enhances interaction with the mink ACE2 receptor for host adaption
This article has 15 authors:Reviewed by ScreenIT
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Simultaneous monitoring of HIV viral load and screening of SARS-CoV-2 employing a low-cost RT-qPCR test workflow
This article has 14 authors:Reviewed by ScreenIT
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All-cause excess mortality across 90 municipalities in Gujarat, India, during the COVID-19 pandemic (March 2020-April 2021)
This article has 7 authors:Reviewed by ScreenIT
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Presence and stability of SARS-CoV-2 on environmental currency and money cards in Utah reveals a lack of live virus
This article has 6 authors:Reviewed by ScreenIT
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Gene Expression Risk Scores for COVID-19 Illness Severity
This article has 9 authors:Reviewed by ScreenIT
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Immunization with SARS-CoV-2 nucleocapsid protein triggers a pulmonary immune response in rats
This article has 19 authors:Reviewed by ScreenIT
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Antiviral cyclic peptides targeting the main protease of SARS-CoV-2
This article has 20 authors:Reviewed by ScreenIT
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Defective ORF8 dimerization in delta variant of SARS CoV2 leads to abrogation of ORF8 MHC-I interaction and overcome suppression of adaptive immune response
This article has 5 authors:Reviewed by ScreenIT
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Structure-based design of antisense oligonucleotides that inhibit SARS-CoV-2 replication
This article has 4 authors:Reviewed by ScreenIT
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A Lagrangian Approach Towards Quantitative Analysis of Flow-mediated Infection Transmission in Indoor Spaces with Application to SARS-COV-2
This article has 3 authors:Reviewed by ScreenIT