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
-
COVID-19 spreading in Rio de Janeiro, Brazil: Do the policies of social isolation really work?
This article has 1 author:Reviewed by ScreenIT
-
Sex differences and psychological stress: responses to the COVID-19 pandemic in China
This article has 10 authors:Reviewed by ScreenIT
-
Enhanced contact investigations for nine early travel-related cases of SARS-CoV-2 in the United States
This article has 100 authors:Reviewed by ScreenIT
-
Design of an epitope-based peptide vaccine against the SARS-CoV-2: a vaccine-informatics approach
This article has 7 authors:Reviewed by ScreenIT
-
Genomic Diversity and Hotspot Mutations in 30,983 SARS-CoV-2 Genomes: Moving Toward a Universal Vaccine for the “Confined Virus”?
This article has 24 authors:Reviewed by ScreenIT
-
Direct Observation of Repeated Infections With Endemic Coronaviruses
This article has 2 authors:Reviewed by ScreenIT
-
Neutralizing Antibodies Isolated by a site-directed Screening have Potent Protection on SARS-CoV-2 Infection
This article has 10 authors:Reviewed by ScreenIT
-
PSGL-1 inhibits the virion incorporation of SARS-CoV and SARS-CoV-2 spike glycoproteins and impairs virus attachment and infectivity
This article has 8 authors:Reviewed by ScreenIT
-
Release of potential pro-inflammatory peptides from SARS-CoV-2 spike glycoproteins in neutrophil-extracellular traps
This article has 2 authors:Reviewed by ScreenIT
-
Functional profiling of COVID-19 respiratory tract microbiomes
This article has 4 authors:Reviewed by ScreenIT