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Deep Learning for Genomics

You're reading from   Deep Learning for Genomics Data-driven approaches for genomics applications in life sciences and biotechnology

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Product type Paperback
Published in Nov 2022
Publisher Packt
ISBN-13 9781804615447
Length 270 pages
Edition 1st Edition
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Author (1):
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Upendra Kumar Devisetty Upendra Kumar Devisetty
Author Profile Icon Upendra Kumar Devisetty
Upendra Kumar Devisetty
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Toc

Table of Contents (18) Chapters Close

Preface 1. Part 1 – Machine Learning in Genomics
2. Chapter 1: Introducing Machine Learning for Genomics FREE CHAPTER 3. Chapter 2: Genomics Data Analysis 4. Chapter 3: Machine Learning Methods for Genomic Applications 5. Part 2 – Deep Learning for Genomic Applications
6. Chapter 4: Deep Learning for Genomics 7. Chapter 5: Introducing Convolutional Neural Networks for Genomics 8. Chapter 6: Recurrent Neural Networks in Genomics 9. Chapter 7: Unsupervised Deep Learning with Autoencoders 10. Chapter 8: GANs for Improving Models in Genomics 11. Part 3 – Operationalizing models
12. Chapter 9: Building and Tuning Deep Learning Models 13. Chapter 10: Model Interpretability in Genomics 14. Chapter 11: Model Deployment and Monitoring 15. Chapter 12: Challenges, Pitfalls, and Best Practices for Deep Learning in Genomics 16. Index 17. Other Books You May Enjoy

Index

As this ebook edition doesn't have fixed pagination, the page numbers below are hyperlinked for reference only, based on the printed edition of this book.

A

activation function 60

binary step function 60

leaky ReLU 62

ReLu 61

sigmoid 62

softmax 63, 64

tanh 63

activator protein (AP) 175

advanced tools, model monitoring

data quality tools 222

DL monitoring tools 223

monitoring 222

system monitoring tools 222

AI, in genomics market

reference link 6

Amazon SageMaker 210

Amazon Web Services (AWS) 17

Analysis using Denoising Autoencoders for Gene Expression (ADAGE)

reference link 130

anomaly detection 119

novelty detection 120

outlier detection 119, 120

area under the curve (AUC) 172

artificial neural networks (ANNs) 4

artificial neuron (AN) 57

association 121

autoencoder applications, for predicting gene expression

ADAGE 130

gene expression clustering, boosting 131

...
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