eBook - PDF
Deep Learning in Genetics and Genomics
Volume 1: Foundations and Introductory Applications
- 320 pages
- English
- PDF
- Available on iOS & Android
eBook - PDF
Deep Learning in Genetics and Genomics
Volume 1: Foundations and Introductory Applications
About this book
Deep Learning in Genetics and Genomics vol. 1, Foundations and Applications, the intersection of deep learning and genetics opens up new avenues for advancing our understanding of the genetic code, gene regulation, and the broader genomics landscape. The book not only covers the most up-to-date advancements in the field of deep learning in genetics and genomics, but also a wide spectrum of (sub) topics including medical and clinical genetics, predictive medicine, transcriptomic, and gene expression studies. In 21 chapters Deep Learning in Genetics and Genomics vol. 1, Foundations and Applications describes how AI and DL have become increasingly useful in genetics and genomics research where both play a crucial role by accelerating research, improving the understanding of the human genome, and enabling personalized healthcare. From the fundamentals concepts and practical applications of deep learning algorithms to a wide range of challenging problems from genetics and genomics, Deep Learning in Genetics and Genomics vol. 1, Foundations and Applications creates a better knowledge of the biological and genetics mechanisms behind disease illnesses and improves the forecasting abilities using the different methodologies described. This title offers a unique resource for wider, deeper, and in-depth coverage of recent advancement in deep learning-based approaches in genetics and genomics, helping researchers process and interpret vast amounts of genetic data, identify patterns, and make discoveries that would be challenging or impossible using traditional methods.
- Brings together fundamental concepts of genetics, genomics, and deep learning
- Includes how to build background of solution methodologies and design of mathematical and logical algorithms
- Delves into the intersection of deep learning and genetics, offering a comprehensive exploration of how deep learning techniques can be applied to various aspects of genomics
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Yes, you can access Deep Learning in Genetics and Genomics by Khalid Raza in PDF and/or ePUB format, as well as other popular books in Biological Sciences & Molecular Biology. We have over one million books available in our catalogue for you to explore.
Information
Table of contents
- Front Cover
- Deep Learning in Genetics and Genomics
- Deep Learning in Genetics and GenomicsVolume 1: Foundations and Introductory Applications
- Copyright
- Dedication
- Contents
- Contributors
- Contributors
- About the editor
- Preface
- Acknowledgments
- About the book
- About the book
- 1 - Basics of genetics and genomics
- 2 - Introduction to deep learning for genomics
- 3 - Foundations and applications of computational genomics
- 4 - Decoding DNA: Deep learning's impact on genomic exploration
- 5 - AI and deep learning in cancer genomics
- 6 - Unravelling the recent developments in applications and challenges of AI in cancer biology: An overview
- 7 - Unlocking the potential of deep learning for oncological sequence analysis: A review
- 8 - Deep learning in medical genetics: A review
- 9 - Navigating the genomic landscape: A deep dive into clinical genetics with deep learning
- 10 - Advancing clinical genomics: Bridging the gap between deep learning models and interpretability for improved d ...
- 11 - Deep learning in clinical genomics-based cancer diagnosis
- 12 - Deep learning in predictive medicine: Current state of the art
- 13 - Applications of AI in cancer genomics: A way toward intelligent decision systems in healthcare
- 14 - The role of deep learning in drug discovery
- 15 - Deep learning applications in genomics-based toxicology assessment
- 16 - The revolutionary impact of deep learning in transcriptomics and gene expression analysis: A genomic paradigm ...
- 17 - Data-driven genomics: A triad of big data, cloud, and IoT in genomics research
- 18 - Deep learning in variant detection and annotation
- 19 - Inequality in genetic healthcare: Bridging gaps with deep learning innovations in low-income and middle-income ...
- 20 - Analysis of genetic and clinical features in neuro disorders using deep learning models
- Index
- Back Cover