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A comprehensive and current summary of machine learning-based strategies for constructing digital plant biology
Machine Learning for Plant Biology provides a comprehensive summary of the latest developments in machine learning (ML) technologies, emphasizing their role in analyzing complex biological networks of plants and in modeling the responses of major crops to biotic and abiotic stresses. The combinatorial strategies discussed in this book enable readers to further their understanding of plant biology, stress physiology, and protection.
Machine Learning for Plant Biology includes information on:
Machine Learning for Plant Biology is an essential reference on the subject for scientists, plant biologists, crop breeders, and students interested in the development of sustainable agriculture in the face of a changing global climate.
Author: Jen-Tsung Chen
ISBN-10: 139432961X
ISBN-13: 9781394329618
Publisher: Wiley
Language: English
Published: 11/13/2025
Pages: 400
Format: Hardcover
Weight: 2.52lbs
Size: 11.00h x 8.50w x 0.88d
Jen-Tsung Chen is a Professor of Cell Biology at the Department of Life Sciences, National University of Kaohsiung, Taiwan, where he teaches courses on cell biology, genomics, proteomics, plant physiology, and plant biotechnology. His research interests include bioactive compounds, chromatography techniques, plant molecular biology, plant biotechnology, bioinformatics, and systems pharmacology. In 2023 and 2024, Elsevier and Stanford University recognized Dr. Chen as one of the "World's Top 2% Scientists". In 2025, Dr. Chen received the "Springer Nature Editorial Contribution Award" for his contributions to Plant Methods.
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