Handbook of Machine Learning Applications for Genomics

Language: English

Published by Springer Verlag, Singapore, SG, 2022

9811691576 / 9789811691577

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Currently, machine learning is playing a pivotal role in the progress of genomics. The applications of machine learning are helping all to understand the emerging trends and the future scope of genomics. This book provides comprehensive coverage of machine learning applications such as  DNN, CNN, and RNN, for predicting the sequence of DNA and RNA binding proteins, expression of the gene, and splicing control. In addition, the book addresses the effect of multiomics data analysis of cancers using tensor decomposition, machine learning techniques for protein engineering, CNN applications on genomics, challenges of long noncoding RNAs in human disease diagnosis, and how machine learning can be used as a  tool to shape the future of medicine. More importantly, it gives a comparative analysis and validates the outcomes of machine learning methods on genomic data to the functional laboratory tests or by formal clinical assessment. The topics of this book will cater interest to academicians,  practitioners working in the field of functional genomics, and machine learning. Also, this book shall guide comprehensively the graduate, postgraduates, and Ph.D. scholars working in these fields. …

Title
Handbook of Machine Learning Applications for Genomics
Author
Sanjiban Sekhar Roy
Publisher
Springer Verlag, Singapore, SG
Publication year
2022
Condition
New
Binding
Hardback
Language
English
ISBN 10
9811691576
ISBN 13
9789811691577
Edition
2022 ed.
Dimensions
15.6 x 1.42 x 23.39 cm

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