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
-
Rapid Serological Assays and SARS-CoV-2 Real-Time Polymerase Chain Reaction Assays for the Detection of SARS-CoV-2: Comparative Study
This article has 12 authors:Reviewed by ScreenIT
-
Pooling RT-PCR or NGS samples has the potential to cost-effectively generate estimates of COVID-19 prevalence in resource limited environments
This article has 7 authors:Reviewed by ScreenIT
-
COVID-19 Pandemic: Power Law Spread and Flattening of the Curve
This article has 3 authors:Reviewed by ScreenIT
-
Energetics and IC50 based epitope screening in SARS CoV-2 (COVID 19) spike protein by immunoinformatic analysis implicating for a suitable vaccine development
This article has 3 authors:Reviewed by ScreenIT
-
Structural basis of RNA recognition by the SARS-CoV-2 nucleocapsid phosphoprotein
This article has 7 authors:Reviewed by ScreenIT
-
Coronavirus hemagglutinin-esterase and spike proteins coevolve for functional balance and optimal virion avidity
This article has 12 authors:Reviewed by ScreenIT
-
A snapshot of SARS-CoV-2 genome availability up to 30 th March, 2020 and its implications
This article has 4 authors:Reviewed by ScreenIT
-
Topological analysis of SARS CoV-2 main protease
This article has 1 author:Reviewed by ScreenIT
-
Leveraging mRNAs sequences to express SARS-CoV-2 antigens in vivo
This article has 8 authors:Reviewed by ScreenIT
-
In vitro screening of a FDA approved chemical library reveals potential inhibitors of SARS-CoV-2 replication
This article has 8 authors:Reviewed by ScreenIT