Machine Learning in Protein Science

Machine Learning in Protein Science, 1st Edition, written by Jinjin Li and Yanqiang Han, is a 2026 textbook published by Wiley-VCH. The volume concentrates on efficiently predicting protein structures and properties, establishing a structured framework for applying modern algorithmic methods to fundamental biological questions.

The pedagogical focus centers on integrating machine learning techniques with core principles of protein science. The coverage connects analytical data models directly with molecular biology, illustrating how quantitative tools facilitate the prediction of structural configurations and functional properties in biological systems.

Comprising 240 pages in English, this textbook provides clear thematic organization for academic study within biological sciences and molecular biology curricula. It equips readers with essential concepts needed to evaluate predictive computational models in protein research.