Computation and Analysis for Genome Mapping using the Deep Learning-based Optimization Algorithm

Genome mapping has emerged as a vital issue within the observe modern day genetics, contributing to advancements in scientific research, evolutionary biology, and personalized medicinal drug. The computation and analysis for genome mapping in efficiency processing massive and complicated genomic pattern. This chapter proposes a modified deep learning-based optimization algorithm tailored for genome mapping, presenting greater computation efficiency and mapping accuracy. This proposed approach combining superior deep neural networks with evolutionary optimization strategies, the proposed technique appreciably reduces computation time while retaining high accuracy in identifying gene sequences. The overall performance the proposed algorithm is evaluated the usage of real-world genomic datasets, demonstrating its capability in accelerating genome analysis and improving precision.