Elsevier Introduction to Structural Bioinformatics

Introduction to Structural Bioinformatics offers a complete overview on the fundamental concepts and methodologies of structural bioinformatics and computational structural biology. The book is divided into three sections, beginning with a discussion of the key principles of bioinformatics and fundamental aspects, including bioinformatics databases, multiple sequence alignment, and machine learning. Section two then moves on to structural bioinformatics, where topics include Monte Carlo simulation, protein structure prediction, RNA structure prediction, and protein design. The final section of the book focuses on experimental structural determination, where chapters focus on techniques including X-ray crystallography, nuclear magnetic resonance and cryo-electron microscopy. This is an ideal guide on key principles, methods, and the most up-to-date developments across structural bioinformatics and computational structural biology. It will be a comprehensive reference for postgraduate students, instructors, and researchers working in these and adjacent subjects. Discusses cutting-edge AI and deep-learning techniques, including AlphaFold and D-I-TASSER, along with their impact on structural bioinformatics Explores protein and RNA structure prediction Considers the most recent advances in the field as well as more classical physics-based approaches Features chapter outlines, definitions, key learning objectives, and case studies throughout the book to aid comprehension