Machine Learning - Based Approaches for Vaccine Target Identification: Implementation and Insights

• DOI: 10.31219/osf.io/p4ayq
• Publication Date: 2024-04-06T12:42:04Z
• Authors: Ronit Gandotra; Srishti Verma; Khushi Gupta; Manan Garg; Navya P. Vidhu; Prajwal Mahajan; Raghav Chawla; Shubhay Tripathi; Kamal Rawal
• Keywords: Identification

Vaccine development relies heavily on the identification of appropriate antigen targets to induce robust immune responses. Traditional methods for vaccine target often involve laborious experimental procedures and may lack scalability. In recent years, Machine Learning, has emerged as a viable alternative bioinformatics tasks, including identification. this paper, we present an implementation Learning -based approaches provide insights into their effectiveness. We utilize comprehensive dataset pathogen proteins employ feature analysis prediction. Our results demonstrate promising performance models in accurately identifying targets, showcasing efficiency interpretability. Through detailed analysis, highlight key factors influencing model discuss potential avenues further improvement. Overall, our study underscores - based identification, offering valuable future research field.