Machine Learning in Protein Science: Efficient Prediction of Protein Structures and Properties

— —

Jinjin Li (Shanghai Jiao Tong University, China) Yanqiang Han (Shanghai Jiao Tong University, China)

Machine Learning in Protein Science

Efficient Prediction of Protein Structures and Properties

Jinjin Li (Shanghai Jiao Tong University, China), Yanqiang Han (Shanghai Jiao Tong University, China)

$257.95

Hardback

Forthcoming
Pre-Order now

QTY:

English

Blackwell Verlag GmbH
17 December 2025

Biochemistry; Machine learning

Harness the power of machine learning for quick and efficient calculations of protein structures and properties

Machine Learning in Protein Science is a unique and practical reference that shows how to employ machine learning approaches for full quantum mechanical (FQM) calculations of protein structures and properties, thereby saving costly computing time and making this technology available for routine users.

Machine Learning in Protein Science provides comprehensive coverage of topics including:

Machine learning models and algorithms, from deep neural network (DNN) and transfer learning (TL) to hybrid unsupervised and supervised learning Protein structure predictions with AlphaFold to predict the effects of point mutations Modeling and optimization of the catalytic activity of enzymes Property calculations (energy, force field, stability, protein-protein interaction, thermostability, molecular dynamics) Protein design and large language models (LLMs) of protein systems

Machine Learning in Protein Science is an essential reference on the subject for biochemists, molecular biologists, theoretical chemists, biotechnologists, and medicinal chemists, as well as students in related programs of study.

By: Jinjin Li (Shanghai Jiao Tong University China), Yanqiang Han (Shanghai Jiao Tong University, China)
Imprint: Blackwell Verlag GmbH
Country of Publication: Germany
Dimensions: Height: 244mm, Width: 170mm,
ISBN: 9783527352159
ISBN 10: 3527352155
Pages: 240
Publication Date: 17 December 2025
Audience: Professional and scholarly , College/higher education , Undergraduate , Further / Higher Education
Format: Hardback
Publisher's Status: Forthcoming

Jinjin Li is a Professor at the School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University in Shanghai, China. She performed postdoctoral work at the University of Illinois, USA and was a Senior Research Fellow at the University of California, USA. Yanqiang Han is an Assistant Professor at the School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University in Shanghai, China.