Deep Learning in Genetics and Genomics: Vol. 2 (Advanced Applications)

Delves into the Deep Learning methods and their applications in various fields of studies, including genetics and genomics, bioinformatics, health informatics, and medical informatics, generating the momentum of today’s developments in the field. In 25 chapters, this title covers advanced applications in the field which include deep learning in predictive medicines, analysis of genetic and clinical features, transcriptomics and gene expression patterns analysis, clinical decision support in genetic diagnostics, deep learning in personalized genomics and gene editing, and understanding genetic discoveries through Explainable AI.

Further, it also covers various deep learning-based case studies, making this book a unique resource for wider, deeper, and in-depth coverage of recent advancements in deep learning-based approaches. This volume is not only a valuable resource for health educators, clinicians, and healthcare professionals but also for graduate students of genetics, genomics, biology, biostatistics, biomedical sciences, bioinformatics, and interdisciplinary sciences.

Embraces the potential that deep learning holds for understanding genome biology

Encourages further advances in this area, extending to all aspects of genomics research

Provides Deep Learning algorithms in genetic and genomic research