
- 312 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
eBook - ePub
About this book
All About Bioinformatics: From Beginner to Expert provides readers with an overview of the fundamentals and advances in the _x001F_field of bioinformatics, as well as some future directions. Each chapter is didactically organized and includes introduction, applications, tools, and future directions to cover the topics thoroughly.
The book covers both traditional topics such as biological databases, algorithms, genetic variations, static methods, and structural bioinformatics, as well as contemporary advanced topics such as high-throughput technologies, drug informatics, system and network biology, and machine learning. It is a valuable resource for researchers and graduate students who are interested to learn more about bioinformatics to apply in their research work.
- Presents a holistic learning experience, beginning with an introduction to bioinformatics to recent advancements in the field
- Discusses bioinformatics as a practice rather than in theory focusing on more application-oriented topics as high-throughput technologies, system and network biology, and workflow management systems
- Encompasses chapters on statistics and machine learning to assist readers in deciphering trends and patterns in biological data
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Please note we cannot support devices running on iOS 13 and Android 7 or earlier. Learn more about using the app.
Yes, you can access All About Bioinformatics by Yasha Hasija in PDF and/or ePUB format, as well as other popular books in Biological Sciences & Bioinformatics. We have over one million books available in our catalogue for you to explore.
Information
Table of contents
- All About Bioinformatics
- Table of Contents
- Chapter 1 What is bioinformatics?
- Chapter 2 Introduction to biological databases
- Chapter 3 Statistical methods in bioinformatics
- Chapter 4 Algorithms in computational biology
- Chapter 5 Genetic variations
- Chapter 6 Structural bioinformatics
- Chapter 7 High throughput technology
- Chapter 8 Drug informatics
- Chapter 9 A machine learning approach to bioinformatics
- Chapter 10 Systems and network biology
- Chapter 11 Bioinformatics workflow management systems
- Chapter 12 Data handling using Python
- Index