For a number of illnesses, such as cancer, autoimmune disorders and infectious diseases, the immune system is crucial to the creation of tailored treatment. Computational immunology, often known as immunoinformatics, is a new field that offers basic approaches for studying immunomics, or immune-related proteomics and genomes. A deeper comprehension of immune-related disorders at different systems levels could result from the combination of immunoinformatics and systems biology methodologies. These techniques can support translational research that improves clinical practice by using scientific findings about the immune system. One new medical treatment for breast cancer is vaccination. Cancer vaccines can be developed to teach the immune system to identify tumor cells by focusing on the tumor antigen. As a result, in addition to technological advancements, the process of creating vaccinations is now beginning to employ more logical techniques, such as the use of immunoinformatics techniques to create peptide vaccines based on epitopes. Immunoinformatics techniques can help with the safety and antigenicity of vaccine design. Tumor antigen identification, protein structure analysis, T cell epitope prediction, epitope characterisation, and assessment of protein–epitope interactions are common procedures utilized in the development of epitope-based peptide vaccines. Measurements and catalogs of genes, proteins, interactions, and behavior are made possible by high-throughput techneologis. A better knowledge ofthe network of interactions between people, medications, and vaccinations may result from this view, opening up new avenues for studying illnesses and developing effective treatments. Lastly, despite prediction models' great accuracy, testing in vitro andin vivo can have the opposite effect. Therefore, more research is required to guarantee the efficacy of the vaccine that will be created. Adjuvants can improve the immunogenicity of epitope-based peptide vaccines, notwithstanding their modest immunogenicity
For a number of illnesses, such as cancer, autoimmune disorders and infectious diseases, the immune system is crucial to the creation of tailored treatment. Computational immunology, often known as immunoinformatics, is a new field that offers basic approaches for studying immunomics, or immune-related proteomics and genomes. A deeper comprehension of immune-related disorders at different systems levels could result from the combination of immunoinformatics and systems biology methodologies. These techniques can support translational research that improves clinical practice by using scientific findings about the immune system. One new medical treatment for breast cancer is vaccination. Cancer vaccines can be developed to teach the immune system to identify tumor cells by focusing on the tumor antigen. As a result, in addition to technological advancements, the process of creating vaccinations is now beginning to employ more logical techniques, such as the use of immunoinformatics techniques to create peptide vaccines based on epitopes. Immunoinformatics techniques can help with the safety and antigenicity of vaccine design. Tumor antigen identification, protein structure analysis, T cell epitope prediction, epitope characterisation, and assessment of protein–epitope interactions are common procedures utilized in the development of epitope-based peptide vaccines. Measurements and catalogs of genes, proteins, interactions, and behavior are made possible by high-throughput techneologis. A better knowledge ofthe network of interactions between people, medications, and vaccinations may result from this view, opening up new avenues for studying illnesses and developing effective treatments. Lastly, despite prediction models' great accuracy, testing in vitro andin vivo can have the opposite effect. Therefore, more research is required to guarantee the efficacy of the vaccine that will be created. Adjuvants can improve the immunogenicity of epitope-based peptide vaccines, notwithstanding their modest immunogenicity
| № | Author name | position | Name of organisation |
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| 1 | Khozhiev K.A. | ! | Bioinformatician at Pharmaceutical Technical University |
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