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 Multiscale and Comparative Model for Receptor Binding of 2019 Novel Coronavirus and the Implication of its Life Cycle in Host Cells
This article has 2 authors:Reviewed by ScreenIT
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Potential T-cell and B-cell Epitopes of 2019-nCoV
This article has 3 authors:Reviewed by ScreenIT
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Single cell RNA sequencing of 13 human tissues identify cell types and receptors of human coronaviruses
This article has 4 authors:Reviewed by ScreenIT
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Protection of Rhesus Macaque from SARS-Coronavirus challenge by recombinant adenovirus vaccine
This article has 11 authors:Reviewed by ScreenIT
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Functional pangenome analysis suggests inhibition of the protein E as a readily available therapy for COVID-2019
This article has 7 authors:Reviewed by ScreenIT
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Are pangolins the intermediate host of the 2019 novel coronavirus (2019-nCoV) ?
This article has 9 authors:Reviewed by ScreenIT
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Isolation and Characterization of 2019-nCoV-like Coronavirus from Malayan Pangolins
This article has 26 authors:Reviewed by ScreenIT
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Structure, Function, and Antigenicity of the SARS-CoV-2 Spike Glycoprotein
This article has 6 authors:Reviewed by ScreenIT
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Aberrant pathogenic GM-CSF + T cells and inflammatory CD14 + CD16 + monocytes in severe pulmonary syndrome patients of a new coronavirus
This article has 10 authors:Reviewed by ScreenIT
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Candidate targets for immune responses to 2019-Novel Coronavirus (nCoV): sequence homology- and bioinformatic-based predictions
This article has 6 authors:Reviewed by ScreenIT