Published Paper Details:

Antibody therapeutics and vaccines are among our pis aller to finish the raging COVID-19 pandemic. They, however, are susceptible to over 5000 mutations on the spike (S) protein uncovered by a Mutation Tracker supported over 200?000 genome isolates. Recent variants of the virus within the UK, South Africa, and Brazil seem to spread more easily, which have the potential to steer to more hospitalizations and deaths. RNA sequence analysis of emerging SARS-CoV-2 infection is effective for tracking viral evolution and developing novel diagnostic tools. Furthermore, SARS-CoV-2 sequence analysis can provide insight into potential antigenic drift events that cause strain speciation and changing clinical outcomes. The tactic is definitely adaptable to research potential mutations of the virus, ensuring the simplest possible vaccines are quickly identified. This will give humans a big advantage over evolving mutations, with the model accomplishing vaccine design cycles that when took months or years during a matter of seconds or minutes. This text is an effort to predict mutations of novel coronavirus by applying machine learning techniques over bioinformatics.