Roy S Handbook of Machine Learning Applications Genomics 2022
Category: eBooks
- views: 276
- date: 7 August 2022
- posted by: BeMyLove
Roy S Handbook of Machine Learning Applications Genomics 2022 | 5.81 MB
English | 222 Pages
Title: Handbook of Machine Learning Applications for Genomics (Studies in Big Data, 103)
Author: Sanjiban Sekhar Roy
Year: 2022
Description:
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 asВ 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 aВ 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,В 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.
DOWNLOAD:
https://rapidgator.net/file/26df467a626e8faedf91555c4a9a5c3d/Roy_S._Handbook_of_Machine_Learning_Applications...Genomics_2022.rar
https://uploadgig.com/file/download/e11E556d2cB0fdF7/Roy_S._Handbook_of_Machine_Learning_Applications...Genomics_2022.rar
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 asВ 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 aВ 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,В 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.
DOWNLOAD:
https://rapidgator.net/file/26df467a626e8faedf91555c4a9a5c3d/Roy_S._Handbook_of_Machine_Learning_Applications...Genomics_2022.rar
https://uploadgig.com/file/download/e11E556d2cB0fdF7/Roy_S._Handbook_of_Machine_Learning_Applications...Genomics_2022.rar
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