Английски език
Reactive Publishing
In the rapidly evolving intersection of artificial intelligence and biotechnology, geometric deep learning has emerged as a powerful framework for modeling the complex 3D structures and interactions that define protein function. Geometric Deep Learning for Protein Engineering with Python provides a practical, hands-on guide to applying these cutting-edge techniques to real-world protein engineering challenges.
Perfect for computational biologists, machine learning engineers, bioinformaticians, and researchers seeking to bridge deep learning with structural biology. Whether you're a graduate student, industry professional, or experienced Python developer looking to enter the biotech space, this book offers the technical depth and code-first approach you need.
Clear explanations, fully reproducible Python code examples, and progressive exercises make complex concepts accessible without sacrificing rigor. Move beyond traditional sequence-based methods and harness the full power of 3D molecular geometry to accelerate your protein engineering projects.
Start engineering the proteins of tomorrow, today.
