AIMC Topic: Viral Proteins
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Prediction of African Swine Fever Virus Inhibitors by Molecular Docking-Driven Machine Learning Models.
Molecules (Basel, Switzerland)
Jun 11, 2021
African swine fever virus (ASFV) causes a highly contagious and severe hemorrhagic viral disease with high mortality in domestic pigs of all ages. Although the virus is harmless to humans, the ongoing ASFV epidemic could have severe economic conseque...
Utilizing Computational Machine Learning Tools to Understand Immunogenic Breadth in the Context of a CD8 T-Cell Mediated HIV Response.
Frontiers in immunology
Feb 18, 2021
Predictive models are becoming more and more commonplace as tools for candidate antigen discovery to meet the challenges of enabling epitope mapping of cohorts with diverse HLA properties. Here we build on the concept of using two key parameters, div...
A protocol for adding knowledge to Wikidata: aligning resources on human coronaviruses.
BMC biology
Jan 22, 2021
BACKGROUND: Pandemics, even more than other medical problems, require swift integration of knowledge. When caused by a new virus, understanding the underlying biology may help finding solutions. In a setting where there are a large number of loosely ...
A protein folding robot driven by a self-taught agent.
Bio Systems
Dec 29, 2020
This paper presents a computer simulation of a virtual robot that behaves as a peptide chain of the Hemagglutinin-Esterase protein (HEs) from human coronavirus. The robot can learn efficient protein folding policies by itself and then use them to sol...
A Novel Strategy for the Development of Vaccines for SARS-CoV-2 (COVID-19) and Other Viruses Using AI and Viral Shell Disorder.
Journal of proteome research
Oct 2, 2020
A model that predicts levels of coronavirus (CoV) respiratory and fecal-oral transmission potentials based on the shell disorder has been built using neural network (artificial intelligence, AI) analysis of the percentage of disorder (PID) in the nuc...
IL6-mediated HCoV-host interactome regulatory network and GO/Pathway enrichment analysis.
PLoS computational biology
Sep 30, 2020
During these days of global emergency for the COVID-19 disease outbreak, there is an urgency to share reliable information able to help worldwide life scientists to get better insights and make sense of the large amount of data currently available. I...
Estimating the Binding of Sars-CoV-2 Peptides to HLA Class I in Human Subpopulations Using Artificial Neural Networks.
Cell systems
Sep 10, 2020
Epidemiological studies show that SARS-CoV-2 infection leads to severe symptoms only in a fraction of patients, but the determinants of individual susceptibility to the virus are still unknown. The major histocompatibility complex (MHC) class I expos...
Machine-learning approach expands the repertoire of anti-CRISPR protein families.
Nature communications
Jul 29, 2020
The CRISPR-Cas are adaptive bacterial and archaeal immunity systems that have been harnessed for the development of powerful genome editing and engineering tools. In the incessant host-parasite arms race, viruses evolved multiple anti-defense mechani...
COVID-19 Coronavirus Vaccine Design Using Reverse Vaccinology and Machine Learning.
Frontiers in immunology
Jul 3, 2020
To ultimately combat the emerging COVID-19 pandemic, it is desired to develop an effective and safe vaccine against this highly contagious disease caused by the SARS-CoV-2 coronavirus. Our literature and clinical trial survey showed that the whole vi...
Meta-iPVP: a sequence-based meta-predictor for improving the prediction of phage virion proteins using effective feature representation.
Journal of computer-aided molecular design
Jun 16, 2020
Phage virion protein (PVP) perforate the host cell membrane and eventually culminates in cell rupture thereby releasing replicated phages. The accurate identification of PVP is thus a crucial step towards improving our understanding of the biological...
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