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Elsevier

Introduction to Structural Bioinformatics

  • 1st Edition - February 1, 2027
  • Latest edition
  • Authors: Yang Zhang, Jun Hu, András Szilágyi
  • Language: English

Introduction to Structural Bioinformatics offers a complete overview on the fundamental concepts and methodologies of structural bioinformatics and computational structural biolog… Read more

Description

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.

Key features

  • 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

Readership

Researchers, postgraduate and PhD students, and instructors across structural bioinformatics, structural biology, computational biology and related fields

Table of contents

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

Product details

  • Edition: 1
  • Latest edition
  • Published: February 1, 2027
  • Language: English

About the authors

YZ

Yang Zhang

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.

Affiliations and expertise
Department of Computer Science, School of Computing, National University of Singapore, Singapore

JH

Jun Hu

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.
Affiliations and expertise
Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences, Suzhou, China

AS

András Szilágyi

Dr. András Szilágyi is a Senior Research Fellow at the Institute of Molecular Life Sciences of the HUN-REN Research Centre for Natural Sciences in Budapest, Hungary. He obtained his MS degree in physics and biophysics and his PhD in biology from Eötvös Loránd University. He conducted postdoctoral research in Prof. Jeffrey Skolnick’s group at the University at Buffalo and was a visiting professor at Dr. Yang Zhang’s at the University of Kansas. He has strong expertise in computational structural biology, and his research spans protein structure modeling and prediction, protein–protein interactions, molecular dynamics, and the effects of mutations and post-translational modifications.

Affiliations and expertise
Senior Research Fellow, Institute of Molecular Life Sciences, HUN-REN Research Centre for Natural Sciences,Budapest, Hungary