Sinopsis
The objective of the book is to use advanced deep learning techniques to unlock the complexities of genomic data. It reveals hidden and unknown patterns, to improve our understanding the role of genetics in diseases, speeding up drug discovery processes, illuminating evolutionary trajectories, and dealing with the challenges posed by large genomic datasets. It also addresses ethical concerns, provides real-world applications, reviews future frontiers like as quantum computing and multi-omics integration, and presents a thorough picture of the genetic environment. Overall, the book aims to enhance our ability to use genomics for more precise forecasts, personalised therapies, and a better understanding of the underlying genetic fabric that defines life.
"Sinopsis" puede pertenecer a otra edición de este libro.
Acerca del autor
Bipin Kumar Rai is a Professor in the Department of Computer Science & Engineering, Dayanand Sagar University, Bangalore. He has a PhD from Banasthali University, Rajasthan and M. Tech (CSE) from RGPV Bhopal & B. Tech (CSE) from UPTU Lucknow, India. Dr. Bipin Kumar Rai has 20+ years teaching experience in renowned institutions. He has been actively involved in various academic and administrative roles. His interests include Information security, ML and blockchain. He has published 50+ research papers in WoS/Scopus indexed journals/conferences, 5 books and 5 patents. He has worked as an Editor/Reviewer of several SCI/Scopus indexed journals and as a session chair/TPC member in several conferences.
Rupa Rani is an Assistant Professor in the Department of CSE at AKG Engineering College, Ghaziabad (India). She has a PhD in Computer Science & Engineering from Banasthali Vidyapith, Rajasthan, and has a MTech in Computer Engineering. She published 20+ research papers indexed in WoS/Scopus journals/conferences. Her research interests include data science, AI, ML and cyber security.
Gautam Kumar is an Associate Professor at Manipal University Jaipur, India with the School of Computer Science and Engineering. He has a PhD degree in CSE from Jaypee University of Information Technology, India, and has MTech from RTU, Rajasthan & B.E. from RGPV, Bhopal, MP. His research interests cover cryptography, information security, algorithms, design and analysis of algorithms. He has published 50+ journals/conferences papers indexed in SCI/Scopus, 3 published books and 5 published patents.
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Applications of Deep Learning in Genomics
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Hardcover. Condición: new. Hardcover. The objective of the book is to use advanced deep learning techniques to unlock the complexities of genomic data. It reveals hidden and unknown patterns, to improve our understanding the role of genetics in diseases, speeding up drug discovery processes, illuminating evolutionary trajectories, and dealing with the challenges posed by large genomic datasets. It also addresses ethical concerns, provides real-world applications, reviews future frontiers like as quantum computing and multi-omics integration, and presents a thorough picture of the genetic environment. Overall, the book aims to enhance our ability to use genomics for more precise forecasts, personalised therapies, and a better understanding of the underlying genetic fabric that defines life. The book investigates future frontiers such as quantum computing and multi-omics integration, and presents a picture of the genetic environment to advance enhanced genomics, enabling more precise forecasts, and personalised therapies. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9781032878331
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Applications of Deep Learning in Genomics (Hardcover)
Publicado por
Taylor & Francis Ltd, London, 2025
ISBN 10: 1032878339
ISBN 13: 9781032878331
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Hardcover. Condición: new. Hardcover. The objective of the book is to use advanced deep learning techniques to unlock the complexities of genomic data. It reveals hidden and unknown patterns, to improve our understanding the role of genetics in diseases, speeding up drug discovery processes, illuminating evolutionary trajectories, and dealing with the challenges posed by large genomic datasets. It also addresses ethical concerns, provides real-world applications, reviews future frontiers like as quantum computing and multi-omics integration, and presents a thorough picture of the genetic environment. Overall, the book aims to enhance our ability to use genomics for more precise forecasts, personalised therapies, and a better understanding of the underlying genetic fabric that defines life. The book investigates future frontiers such as quantum computing and multi-omics integration, and presents a picture of the genetic environment to advance enhanced genomics, enabling more precise forecasts, and personalised therapies. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9781032878331
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