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 includes 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 personalised 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 advancement in deep learning based approaches. This volume is not only a valuable resource for health educators, clinicians, and healthcare professionals but also to graduate students of genetics, genomics, biology, biostatistics, biomedical sciences, bioinformatics, and interdisciplinary sciences.
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Dr. Khalid Raza is an Associate Professor at the Department of Computer Science, Jamia Millia Islamia, New Delhi, India, and an Adjunct Professor at UCSI University, Malaysia. He has over 14 years of teaching and research experience and previously served as an ICCR Chair Visiting Professor at Ain Shams University, Egypt. Dr. Raza has published more than 160 peer-reviewed papers and authored/edited over 15 books with Springer, Elsevier, and CRC Press. He serves as Academic Editor of PLoS ONE, BMC Artificial Intelligence, and Guest Editor of npj Precision Oncology, JoVE, and several other journals. Recipient of Clarivate’s (Web of Science) India Excellence Research Citation Award 2025, Dr. Raza is consistently featured in the World’s Top 2% Scientists list (2022–2025). His research focuses on AI, bioinformatics, and health informatics
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 includes 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 personalised 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 advancement in deep learning based approaches. This volume is not only a valuable resource for health educators, clinicians, and healthcare professionals but also to graduate students of genetics, genomics, biology, biostatistics, biomedical sciences, bioinformatics, and interdisciplinary sciences.
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