Name
Title | ||
|---|---|---|
A multi-step and multi-scale bioinformatic protocol to investigate potential SARS-CoV-2 vaccine targets |
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. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1093/bib/bbab403 | BRIEFINGS IN BIOINFORMATICS |
Keywords | DocType | Volume |
SARS-CoV-2, in silico trial, multi-step algorithm, multi-scale approach, vaccine | Journal | 23 |
Issue | ISSN | Citations |
1 | 1467-5463 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Giulia Russo | 1 | 15 | 10.89 |
| Valentina Di Salvatore | 2 | 0 | 1.69 |
| Giuseppe Sgroi | 3 | 1 | 3.09 |
| Giuseppe Alessandro Parasiliti Palumbo | 4 | 3 | 3.91 |
| Pedro A Reche | 5 | 0 | 0.34 |
| Francesco Pappalardo | 6 | 189 | 28.53 |