دانلود کتاب کاربردهای یادگیری عمیق در ژنومیک

Over the past two decades, advancements in data analytics, computational biology, and high-throughput sequencing technologies have propelled the science of genomics forward. Researchers now have access to vast genetic data repositories, presenting unprecedented opportunities and challenges. The emergence of deep learning has ushered in a new era in genomics, where powerful algorithms uncover meaningful insights from the intricate patterns within DNA, RNA, and protein sequences. Emerging technologies like AI, Blockchain, and Quantum computing are transforming healthcare 5.0. Applications of Deep Learning in Genomics address this pivotal moment by bridging the gap between artificial intelligence and genomics. This book provides researchers, students, and professionals with a comprehensive overview of how deep learning revolutionizes the field, tackling critical challenges such as predicting gene functions, identifying disease-associated variations, modeling epigenetic regulation, and analyzing multi-omics data. With its unparalleled capabilities, deep learning is transforming exploration and discovery in genomics. The chapters are designed to deliver both foundational knowledge and practical insights. Readers will learn key concepts in deep learning, including transformer models, recurrent neural networks (RNNs), and convolutional neural networks (CNNs), in the context of biological sequence data. Real-world applications and case studies illustrate successful implementations and their contributions to advancing genomic science. As the field continues to grow, ethical considerations and challenges in data interpretation remain significant. This book provides a balanced discussion of the strengths and limitations of deep learning tools in genomics research while addressing these critical issues. We are deeply grateful to the contributors for their expertise and commitment, which made this book possible. We hope it serves as an invaluable resource for those applying deep learning techniques in genomics, inspiring groundbreaking innovations that will shape the future of biology and medicine. In summary, “Applications of Deep Learning in Genomics” serves as a comprehensive guide at the intersection of genomics and deep learning. It equips readers with practical tools for precision genome analysis, explores ethical considerations, and envisions the future of genomic exploration. Through a blend of theory and case studies, the book not only demystifies complex concepts but also inspires a commitment to responsible and impactful research, emphasizing the transformative potential of deep learning in advancing our understanding of the genome.