chapter  1
4 Pages

Introduction

This book is meant to provide an informative yet accessible overview of the ways in which the two increasingly intertwined areas of bioinformatics andmachine learning borrow strength or motivation from each other. There are many different definitions of bioinformatics. Generally speaking, it is an emerging field of science growing from an application of mathematics, statistics and information science to the study and analysis of very large biological datasets with the help of powerful computers. No matter what precise definition is being used, there seems to be a consensus that bioinformatics is all about extracting knowledge from the deluge of information (in the form of huge datasets) produced by modern-day high-throughput biological experiments. And this is precisely the task that machine learning is meant for-it is supposed to provide innovative tools and techniques enabling us to handle the information overload that the scientific community is currently experiencing. So these two areas were destined to be married. In this book, our goal is to shed enough light on the key aspects of both areas for our readers to understand why this ‘couple’ is ‘made for each other.’