K Kazi
- Professor and Head, Brahmdevdada Mane Institute of Technology, Maharashtra, India
Abstract
An immunity is facilitated by lymphocyte T&B-cells that possess a wide range of T&B-cell receptors, respectively. These cells can identify and react to pathogens and diseased cells by presenting peptide antigens by means of significant histocompatibility complexes (MHCs). The amount of data on the repertoire of adaptive immune receptors has increased dramatically in recent years because to advancements in deep sequencing. Furthermore, the presentation of peptides with MHC has been extensively studied by proteomics approaches. These massive data sets are now enabling the training of deep learning-DL and machine learning-ML models that may be applied to the identification of intricate and multidimensional structures in immune repertoires. This article presents adaptive immune repertoires, as they relate to biological sequence data. The passage delineates a comprehensive overview of the multifaceted applications within this domain, encompassing diverse areas such as the engineering of immunotherapeutic interventions aimed at bolstering immune responses, prognostication of a host’s immunological status for tailored medical interventions, and the fine-grained prediction of antigen specificity exhibited by individual receptors, thus underpinning advancements in personalized medicine and immunotherapy strategies
Keywords: IoT, Malware, Artificial immune, B-cell receptor, T-cell receptor
[This article belongs to Research & Reviews : A Journal of Immunology(rrjoi)]
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Research & Reviews : A Journal of Immunology
| Volume | 14 |
| Issue | 01 |
| Received | March 2, 2024 |
| Accepted | March 13, 2024 |
| Published | April 24, 2024 |