Browsing by Author "MUHAMMAD FARHAN AKHTAR"

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    PREDICTION OF T-CELL USING DEEP NEURAL NETWORKS (DNNs)
    (UMT, Lahore, 2023) MUHAMMAD FARHAN AKHTAR
    Accurate T-cell behavior prediction is a crucial objective in immunology research since it aids in a better understanding of immune responses and the development of specialized therapies. This study advances our knowledge of immunology and the creation of novel therapeutic alternatives by forecasting T-cell activity using a neural network-based methodology. T-cells are key players in adaptive immunity because they respond to a wide range of antigens with intricate activation and differentiation patterns. This study uses the strength of neural networks, particularly feedforward neural networks and similar designs, to unravel the intricacy of T-cell responses. This investigation's initial phase comprises a thorough examination of T-cell biology with a focus on their critical role in immunological defense and surveillance. The intricate connections between T-cells demonstrate the complexity of T-cell behavior. To assist in the forecasting of T-cell responses, a sizable dataset encompassing multiple T-cell activation profiles and associated molecular markers was assembled. In order to illustrate the intricate relationships between T-cell receptor sequences, signaling cascades, and biological effects, neural network models that utilize this dataset are trained.