Literature DB >> 34607353

A multi-step and multi-scale bioinformatic protocol to investigate potential SARS-CoV-2 vaccine targets.

Giulia Russo1, Valentina Di Salvatore1, Giuseppe Sgroi1, Giuseppe Alessandro Parasiliti Palumbo1, Pedro A Reche1, Francesco Pappalardo1.   

Abstract

The COVID-19 pandemic has highlighted the need to come out with quick interventional solutions that can now be obtained through the application of different bioinformatics software to actively improve the success rate. Technological advances in fields such as computer modeling and simulation are enriching the discovery, development, assessment and monitoring for better prevention, diagnosis, treatment and scientific evidence generation of specific therapeutic strategies. The combined use of both molecular prediction tools and computer simulation in the development or regulatory evaluation of a medical intervention, are making the difference to better predict the efficacy and safety of new vaccines. An integrated bioinformatics pipeline that merges the prediction power of different software that act at different scales for evaluating the elicited response of human immune system against every pathogen is proposed. As a working example, we applied this problem solving protocol to predict the cross-reactivity of pre-existing vaccination interventions against SARS-CoV-2.
© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  SARS-CoV-2; in silico trial; multi-scale approach; multi-step algorithm; vaccine

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Year:  2022        PMID: 34607353      PMCID: PMC8500048          DOI: 10.1093/bib/bbab403

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


  1 in total

Review 1.  Covid-19 and Artificial Intelligence: Genome sequencing, drug development and vaccine discovery.

Authors:  Sali Abubaker Bagabir; Nahla Khamis Ibrahim; Hala Abubaker Bagabir; Raghdah Hashem Ateeq
Journal:  J Infect Public Health       Date:  2022-01-19       Impact factor: 3.718

  1 in total

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