Machine Learning in Biological Sciences: Updates and Future Prospects

Machine Learning (ML) is a powerful tool that is applied in various biological sciences, such as healthcare, animal sciences, agriculture, and plant sciences. It is used for process modeling, computer vision, signal processing, speech recognition, and language understanding and processing. This book covers eight major sections that describe the application of ML in a certain field, such as genetics, cell biology, plant-pathogen interactions, and animal behavior. It also discusses computational methods for toxicity prediction of environmental chemicals and drugs. This book is of relevance to post-graduate students and researchers interested in exploring the interdisciplinary areas of use of machine learning and deep learning in life sciences.

Format: Hardback
Length: 336 pages
Publication date: 05 May 2022
Publisher: Springer Verlag, Singapore

This comprehensive book delves into the diverse applications of Machine Learning (ML) across various biological sciences, encompassing healthcare, animal sciences, agriculture, and plant sciences. Machine learning finds significant utility in process modeling, computer vision, signal processing, speech recognition, language understanding, and processing, as well as in the fields of life and health sciences. It is increasingly employed to unravel DNA patterns and facilitate precision medicine.

Organized into eight major sections, each containing chapters that illustrate the application of ML in a specific domain, the book begins with an introductory overview of ML and its various methods. It then explores captivating and timely topics such as genetics, cell biology, the study of plant-pathogen interactions, and animal behavior. The book also delves into computational approaches for predicting the toxicity of environmental chemicals and drugs, which is a crucial area of research in the biological sciences.

This book is of immense value to post-graduate students and researchers seeking to explore the interdisciplinary realms of applying machine learning and deep learning in life sciences. Its comprehensive coverage and insightful discussions make it a valuable resource for scholars and practitioners alike.

Weight: 705g
Dimension: 235 x 155 (mm)
ISBN-13: 9789811688805
Edition number: 1st ed. 2022