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@article{153688,
        author = {M. Nithya and Dr. Horne Iona Averal},
        title = {IDENTIFICATION AND COMPARISON OF POSSIBLE EPITOPE – DESIGNED TARGETS USING IN-SILICO TECHNIQUES FOR CORONA VIRUS},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {8},
        pages = {280-289},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=153688},
        abstract = {The SARS Coronavirus-2 (SARS-CoV-2) epidemic has become a global issue that has raised concerns for the scientific community to design and find a way to combat this deadly virus. To date, the epidemic has claimed hundreds of thousands of lives as a result of infection and spread. Growing evidence suggests that T cells may play a key role in the fight against acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Therefore, COVID-19 vaccines that can obtain a strong T cell response may be very important. The design, development and evaluation of vaccine trials help to understand the T cell epitopes of SARS-CoV-2, which is less well known. Because of the challenges of diagnosing epitopes by experimentation, many studies have suggested the use of in-silico methods. Here, we present of the in-silico methods used to predict SARS-CoV-2 T cell epitopes. These methods use a different set of technical methods, which often focus on machine learning. Functional comparisons are based on the diagnostic power of a specific set of immunogenic epitopes determined by experiments targeted T cells in recovering COVID-19 patients, highlighting the relative functional relevance of the various methods adopted by in - Silico studies. The investigation also prioritizes ideas for future research guidelines.},
        keywords = {Coronavirus, COVID-19, SARS-CoV-2, Epitope based techniques, In- silico techniques, MHC prediction, Bioinformatics},
        month = {},
        }