Deep Learning in Genetics and Genomics 1st Edition

Deep Learning in Genetics and Genomics 1st Edition by Khalid Raza invites readers into the frontier where artificial intelligence meets the blueprint of life. This definitive guide translates complex neural network architectures and modern deep-learning workflows into practical strategies for solving pressing problems in genetics and genomics—variant discovery, gene expression modeling, single-cell analysis, epigenomic mapping and clinical genomics.

Starting with clear foundations in data preparation, model selection and evaluation, the book progresses to real-world applications and case studies that demonstrate how convolutional networks, recurrent models and transformers are reshaping bioinformatics. Emphasis on interpretability, reproducibility and best practices helps researchers avoid common pitfalls while extracting biologically meaningful insights from high-dimensional genomic data.

Tailored for computational biologists, data scientists, genomics researchers and advanced students, this volume balances theoretical rigor with hands-on guidance. Readers will find practical advice on preprocessing sequencing data, choosing loss functions and metrics, handling batch effects, and integrating multimodal datasets. Ethical considerations and deployment strategies for clinical and research settings are also addressed, making the text relevant for labs and institutions worldwide—from leading centers in North America and Europe to emerging research hubs across Asia-Pacific and beyond.

Whether you’re building predictive models for precision medicine or accelerating discovery in population genetics, Khalid Raza’s first edition is an essential resource to master deep learning applications in genomics. Practical, authoritative and forward-looking, this book equips you to turn genomic data into actionable knowledge. Add it to your library and advance your work at the intersection of AI and biological science.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.