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)
1
Part 1 – Machine Learning in Genomics
5
Part 2 – Deep Learning for Genomic Applications
11
Part 3 – Operationalizing models

Technical requirements

This course assumes that you have a basic knowledge of Python for programming, so we will not introduce Python in this book.

Note

For a quick refresher on Python fundamentals, please refer to https://www.freecodecamp.org/news/python-fundamentals-for-data-science/.

Instead, you will be introduced to Biopython, which is a powerful library in Python that has tools for computational molecular biology for performing genomics data analysis.

Installing Biopython

Installing Biopython is very easy, and it will not take more than a few minutes on any operating system.

Step 1 – Verifying Python installation

Before we install Biopython, first check to see whether Python is installed using the following command in your command prompt:

$ python --version
Python 3.7.4

Note

The $ character represents the command prompt.

If your command prompt returns something like this, then it shows that Python is installed and 3.7.4 is your version...