Deep Learning in Bioinformatics: Techniques and Applications in Practice

Deep Learning in Bioinformatics: Techniques and Applications in Practice, authored by Habib Izadkhah, offers a comprehensive introduction to the use of deep learning in bioinformatics. This book aims to simplify the understanding of deep learning techniques and their applications in addressing significant problems within the bioinformatics field. It covers a wide range of topics including drug discovery, de novo molecular design, sequence analysis, protein structure prediction, gene expression regulation, protein classification, biomedical image processing and diagnosis, biomolecule interaction prediction, and systems biology.

The book presents theoretical and practical successes of deep learning in bioinformatics, highlighting current challenges and suggesting future research directions. Dr. Izadkhah provides valuable insights and guidance for researchers looking to utilize deep learning techniques in their biological and bioinformatics studies.

Key Features

• Introduces deep learning in an easy-to-understand manner
• Explores how deep learning can be applied to address important problems in bioinformatics
• Discusses state-of-the-art algorithms in deep learning and bioinformatics
• Introduces deep learning libraries in bioinformatics

Publication Details

Published by Elsevier Science, this book is available in English and was released on January 8, 2022. The ISBNs for the book are 9780128238226 and 9780128238363.

Why This Book Matters

Deep Learning in Bioinformatics: Techniques and Applications in Practice is a valuable resource for researchers, students, and professionals in the fields of bioinformatics, computational biology, and machine learning. It provides a comprehensive overview of the current state of deep learning in bioinformatics and its potential applications, making it an essential read for those looking to advance their knowledge and skills in this rapidly evolving field.