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
-
The “double eights mask brace” improves the fit and protection of a basic surgical mask amidst COVID‐19 pandemic
This article has 6 authors:Reviewed by ScreenIT
-
A high-throughput neutralizing antibody assay for COVID-19 diagnosis and vaccine evaluation
This article has 7 authors:Reviewed by ScreenIT
-
A modular framework for the development of targeted Covid-19 blood transcript profiling panels
This article has 18 authors:Reviewed by ScreenIT
-
SARS-CoV-2 mutations and where to find them: an in silico perspective of structural changes and antigenicity of the spike protein
This article has 10 authors:Reviewed by ScreenIT
-
Systemic effects of missense mutations on SARS-CoV-2 spike glycoprotein stability and receptor-binding affinity
This article has 5 authors:Reviewed by ScreenIT
-
Dynamically evolving novel overlapping gene as a factor in the SARS-CoV-2 pandemic
This article has 8 authors:Reviewed by ScreenIT
-
Pooling nasopharyngeal swab specimens to increase testing capacity for SARS-CoV-2
This article has 4 authors:Reviewed by ScreenIT
-
Broad-spectrum virucidal activity of bacterial secreted lipases against flaviviruses, SARS-CoV-2 and other enveloped viruses
This article has 14 authors:Reviewed by ScreenIT
-
Electric field-driven microfluidics for rapid CRISPR-based diagnostics and its application to detection of SARS-CoV-2
This article has 8 authors:Reviewed by ScreenIT
-
Early antibody response to SARS-CoV-2
This article has 3 authors:Reviewed by ScreenIT