Introduction to Structural Bioinformatics

Erscheinungsjahr 2026
ISBN: 978-0-443-33765-9
Verlag: Elsevier Science

Buch, Englisch, 350 Seiten, Format (B × H): 216 mm x 276 mm, Gewicht: 449 g

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.

Autoren/Hrsg.

Zhang, Yang

Hu, Jun

Fachgebiete

• Naturwissenschaften Biowissenschaften Angewandte Biologie Bioinformatik
• Mathematik | Informatik EDV | Informatik Angewandte Informatik Bioinformatik

Inhaltsverzeichnis

Part 1: Bioinformatics Basics
1. Bioinformatics databases
2. Pairwise sequence alignments and database search
3. Evolution and phylogenetic tree
4. Multiple sequence alignments
5. Machine learning and deep neural-network learning

Part 2: Structural Bioinformatics
6. Protein structure alignments
7. Monte Carlo simulation and local energy minimization
8. Protein structure prediction
9. RNA structure prediction
10. Quaternary structure prediction
11. Function annotations
12. Protein design

Part 3: Experimental Structural Determination
13. Principle of X-ray crystallography and molecular replacement
14. Introduction to nuclear magnetic resonance
15. Cryo-electron microscopy for protein structure determination

Über Autor(innen)

Hu, Jun
Dr. Jun Hu obtained his Ph.D. in Control Science and Engineering from Nanjing University of Science and Technology. He served as an Associate Professor of Bioinformatics at Zhejiang University of Technology from 2018 to 2023 and has been a Research Associate Professor of AI and Bioinformatics at the Suzhou Institute of Systems Biology since 2024. His research focuses on deep learning-based protein structure and function prediction. He has authored over 40 peer-reviewed publications, including 18 as first and/or corresponding author. His work includes widely used open-source algorithms in structural bioinformatics, such as LS-align, ATPdock, and RLEAAI, for ligand structure alignment, protein-ATP docking, and antibody-antigen interaction prediction, respectively.

Zhang, Yang
Dr Yang Zhang is Professor in the Department of Computer Science, School of Computing, National University of Singapore (NUS). He also serves as Professor and Senior Principal Investigator in the Department of Biochemistry at School of Medicine, NUS, and Cancer Science Institute of Singapore, respectively. Prior to this, Dr Zhang worked as Professor in the Department of Computational Medicine and Bioinformatics and the Department of Biological Chemistry, University of Michigan. Dr Zhang has been teaching graduate courses in bioinformatics for more than a decade. His research interests are in artificial intelligence, deep neural network learning, protein folding, structure prediction, and protein design and engineering. Dr. Zhang is the inventor of many fundamental concepts and methods in structural bioinformatics, including TM-score, TM-align, I-TASSER, and QUARK. Dr. Zhang has received honours including the Alfred P Sloan Award, US NSF Career Award, ASBMB DeLano Award, and University of Michigan Basic Science Research Award.