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
-
ACE2 coding variants in different populations and their potential impact on SARS-CoV-2 binding affinity
This article has 4 authors:Reviewed by ScreenIT
-
Epigenetic regulator miRNA pattern differences among SARS-CoV, SARS-CoV-2 and SARS-CoV-2 world-wide isolates delineated the mystery behind the epic pathogenicity and distinct clinical characteristics of pandemic COVID-19
This article has 5 authors:Reviewed by ScreenIT
-
Impact of Thiol-Disulfide Balance on the Binding of Covid-19 Spike Protein with Angiotensin Converting Enzyme 2 Receptor
This article has 2 authors:Reviewed by ScreenIT
-
The transcriptomic profiling of COVID-19 compared to SARS, MERS, Ebola, and H1N1
This article has 2 authors:Reviewed by ScreenIT
-
Lung biopsy cells transcriptional landscape from COVID-19 patient stratified lung injury in SARS-CoV-2 infection through impaired pulmonary surfactant metabolism
This article has 2 authors:Reviewed by ScreenIT
-
SARS-CoV-2 proteins exploit host’s genetic and epigenetic mediators for the annexation of key host signaling pathways that confers its immune evasion and disease pathophysiology
This article has 2 authors:Reviewed by ScreenIT
-
Multiple early introductions of SARS-CoV-2 into a global travel hub in the Middle East
This article has 17 authors:Reviewed by ScreenIT
-
Massive Multiplexing Can Deliver a $1 Test for COVID-19
This article has 5 authors:Reviewed by ScreenIT
-
Coarse-grained molecular simulations of the binding of the SARS-CoV-2 spike protein RBD to the ACE2 receptor
This article has 3 authors:Reviewed by ScreenIT
-
Identification of neutralizing human monoclonal antibodies from Italian Covid-19 convalescent patients
This article has 23 authors:Reviewed by ScreenIT