Computational and Experimental Approaches in Protein Engineering and Design offers a one-stop resource for students, researchers, and practitioners. Cutting-edge techniques in AI and machine learning applications are expertly covered in the book, empowering readers with the tools they need to tackle modern challenges in biotechnology and therapeutics. Step-by-step protocols provide readers with actionable guidance to transition smoothly from computational modelling to laboratory implementation. The inclusion of real-world case studies makes the theoretical concepts relatable and actionable and immediately applicable to solving complex problems, such as producing protein-based vaccines for immunotherapy.
The book’s focus on synthetic biology positions it at the forefront of innovation, appealing to a broad audience, from those involved in tissue engineering to those exploring next-generation therapeutics. With its forward-looking approach, emphasizing machine-learning-driven protein design and nanobody engineering, this book is an indispensable resource for researchers preparing to navigate the future of biotechnology.
- Bridges theoretical knowledge with the latest practical advances in computational and experimental protein engineering
- Enables readers to leverage computational and experimental approaches synergistically, which is increasingly crucial in drug discovery, enzyme engineering, and synthetic biology
- Details methods such as directed evolution, rational design, and machine-learning-based protein modeling that are essential for researchers aiming to use these methods in tandem
