Orkid Coskuner-Weber – författare

In Silico Protein Structure and Function: From AI-Based to Hybrid Quantum Computing Approaches provides a comprehensive overview of computational techniques including classical, AI-based, and hybrid quantum computing approaches, detailing algorithms such as generative AI and large language models, which is essential for scientists and engineers aiming to use these algorithms. Describes the latest cutting-edge AI-based and hybrid quantum computing approaches, providing readers with the knowledge needed to leverage these approaches to optimize developments in protein structure-function predictions, protein design, protein engineering and drug discovery. Rapid developments in computational biology related to AI-based and hybrid quantum computing tools often leave scientists and engineers needing resources to keep pace.This book incorporates the latest algorithms, methodologies tools and applications, offering an up-to-date reference that informs readers of current trends. Protein structure and function prediction by AI-based and hybrid quantum computing tools demands both conceptual understanding and practical expertise. This book provides real-world applications and case studies that demonstrate how theoretical principles translate to practical scenarios, empowering readers to apply their knowledge in research settings. Practical examples illustrate how protein structure-function predictions are applied in protein design and protein engineering, drug discovery, and biotechnology areas. The latest trends, including applications in next-gen therapeutics, bioinformatics, and molecular biology are explored, providing readers with insights into where the field is heading, which is valuable for those who are preparing for the future of protein science, protein design, protein engineering, and molecular biology.By offering clear explanations of complex topics and processes and highlighting real-world applications, In Silico Protein Structure and Protein Function: From AI-Based to Hybrid Quantum Computing Approaches equips readers to tackle modern challenges in protein design, protein engineering and drug development, ultimately fostering innovation across various sectors in life sciences, engineering, and industryIn Silico Protein Structure and Function is an accessible resource for senior students, scientists, engineers, and professionals who want to deepen their understanding of protein structure and function predictions using the most up to date toolsDescribes the latest cutting-edge AI-based and hybrid quantum computing approaches, which are increasingly important in protein structure-function predictions, protein design, protein engineering, and drug discoveryIncorporates the latest algorithms, methodologies and tools and applications, offering an up-to-date reference of current trendsIncludes a comprehensive overview of computational techniques including classical, AI-based and hybrid quantum computing approaches, detailing algorithms such as generative AI and large language modelsPractical examples are included, illustrating how protein structure-function predictions are applied in protein design, protein engineering, drug discovery and biotechnology areas. These case studies provide insights into solving real-world challenges using the advanced computational approaches covered