| Management number | 238739279 | Release Date | 2026/07/11 | List Price | US$16.80 | Model Number | 238739279 | ||
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<p><b>Reactive Publishing</b> </p><p>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. <i>Geometric Deep Learning for Protein Engineering with Python</i> provides a practical, hands-on guide to applying these cutting-edge techniques to real-world protein engineering challenges.</p>What You'll Learn<ul><li><b>Core Principles</b>: Master the mathematical and computational foundations of geometric deep learning, including graph neural networks, equivariant architectures, and manifold-based representations tailored to molecular data.</li><li><b>Python Implementation</b>: Build end-to-end pipelines using popular libraries such as PyTorch Geometric, DGL, and E3NN to process protein structures from PDB files and design novel sequences with enhanced properties.</li><li><b>Protein Engineering Applications</b>: Learn how to predict protein stability, binding affinity, folding dynamics, and enzyme activity. Explore case studies in therapeutic protein design, antibody engineering, and synthetic biology.</li><li><b>Advanced Techniques</b>: Dive into diffusion models for protein generation, geometric transformers, and hybrid approaches that combine physics-based simulations with deep learning.</li></ul>Who This Book Is For<p>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.</p><p>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.</p><p><b>Start engineering the proteins of tomorrow, today.</b></p>
| Book format | Paperback |
|---|---|
| Fiction/nonfiction | Non-Fiction |
| Genre | Computing & Internet |
| Publication date | June, 2026 |
| Pages | 500 |
| Subgenre | Languages |
| Series title | No Series |
| Number in series | 0 |
| Edition | 1 |
| Publisher | Amazon Digital Services LLC - Kdp |
| Language | English |
| Is collectible | N |
| Recording time | 0 min |
| Retail packaging | Single Piece |
| Assembled product dimensions (l x w x h) | 6.00 x 1.24 x 9.00 in |
| Assembled product weight | 1.32 lb |
| Bisac subject heading | Computers |
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