Book Image

Deep Learning for Genomics

By : Upendra Kumar Devisetty
Book Image

Deep Learning for Genomics

By: Upendra Kumar Devisetty

Overview of this book

Deep learning has shown remarkable promise in the field of genomics; however, there is a lack of a skilled deep learning workforce in this discipline. This book will help researchers and data scientists to stand out from the rest of the crowd and solve real-world problems in genomics by developing the necessary skill set. Starting with an introduction to the essential concepts, this book highlights the power of deep learning in handling big data in genomics. First, you’ll learn about conventional genomics analysis, then transition to state-of-the-art machine learning-based genomics applications, and finally dive into deep learning approaches for genomics. The book covers all of the important deep learning algorithms commonly used by the research community and goes into the details of what they are, how they work, and their practical applications in genomics. The book dedicates an entire section to operationalizing deep learning models, which will provide the necessary hands-on tutorials for researchers and any deep learning practitioners to build, tune, interpret, deploy, evaluate, and monitor deep learning models from genomics big data sets. By the end of this book, you’ll have learned about the challenges, best practices, and pitfalls of deep learning for genomics.
Table of Contents (18 chapters)
Part 1 – Machine Learning in Genomics
Part 2 – Deep Learning for Genomic Applications
Part 3 – Operationalizing models

DL life cycle

The DL life cycle is quite complex as it involves several phases, starting from identifying a business goal to model monitoring (see Figure 9.2). Each phase is driven by the key decision of what, why, and how that will affect the entire DL life cycle. Previously, we have looked at the basic concepts of leveraging DL for genomic applications, but to leverage DL to genomics requires one to understand each of these phases in the DL life cycle clearly. With that goal in mind, let’s go into the details of each of these phases in the following section:

Figure 9.2 – Different phases of a typical DL life cycle

We will go through the steps given in the previous screenshot:

  1. Identify business goal: The first phase in the DL life cycle is identifying a business goal. Every DL project starts with a business problem, scope and risks. This is simply coming up with a clear idea of the business problem to be solved any kind of risk that...