Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics

Informationen zum Autor YI PAN, PHD, is the Chair and Full Professor in the Department of Computer Science at Georgia State University, and a Visiting Chair Professor in the School of Information Science and Engineering at Central South University in Changsha, China. MIN LI, PHD, is Associate Professor in the School of Information Science and Engineering and a postdoctoral associate in the State Key Laboratory of Medical Genetics at Central South University in Changsha, China. JIANXIN WANG, PHD, is Associate Dean and Full Professor in the School of Information Science and Engineering at Central South University in Changsha, China. Klappentext An in-depth look at the latest research, methods, and applications in the field of protein bioinformaticsThis book presents the latest developments in protein bioinformatics, introducing for the first time cutting-edge research results alongside novel algorithmic and AI methods for the analysis of protein data. In one complete, self-contained volume, Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics addresses key challenges facing both computer scientists and biologists, arming readers with tools and techniques for analyzing and interpreting protein data and solving a variety of biological problems.Featuring a collection of authoritative articles by leaders in the field, this work focuses on the analysis of protein sequences, structures, and interaction networks using both traditional algorithms and AI methods. It also examines, in great detail, data preparation, simulation, experiments, evaluation methods, and applications. Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics: Highlights protein analysis applications such as protein-related drug activity comparison Incorporates salient case studies illustrating how to apply the methods outlined in the book Tackles the complex relationship between proteins from a systems biology point of view Relates the topic to other emerging technologies such as data mining and visualization Includes many tables and illustrations demonstrating concepts and performance figuresAlgorithmic and Artificial Intelligence Methods for Protein Bioinformatics is an essential reference for bioinformatics specialists in research and industry, and for anyone wishing to better understand the rich field of protein bioinformatics. Zusammenfassung An in-depth look at the latest research, methods, and applications in the field of protein bioinformaticsThis book presents the latest developments in protein bioinformatics, introducing for the first time cutting-edge research results alongside novel algorithmic and AI methods for the analysis of protein data. In one complete, self-contained volume, Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics addresses key challenges facing both computer scientists and biologists, arming readers with tools and techniques for analyzing and interpreting protein data and solving a variety of biological problems.Featuring a collection of authoritative articles by leaders in the field, this work focuses on the analysis of protein sequences, structures, and interaction networks using both traditional algorithms and AI methods. It also examines, in great detail, data preparation, simulation, experiments, evaluation methods, and applications. Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics: Highlights protein analysis applications such as protein-related drug activity comparison Incorporates salient case studies illustrating how to apply the methods outlined in the book Tackles the complex relationship between proteins from a systems biology point of view Relates the topic to other emerging technologies such as data mining and visualization Includes many tables and illustrations demonstrating concepts and performance figuresAlgorithmic and Artificial Intel...

Auteur

YI PAN, PHD, is the Chair and Full Professor in the Department of Computer Science at Georgia State University, and a Visiting Chair Professor in the School of Information Science and Engineering at Central South University in Changsha, China. MIN LI, PHD, is Associate Professor in the School of Information Science and Engineering and a postdoctoral associate in the State Key Laboratory of Medical Genetics at Central South University in Changsha, China. JIANXIN WANG, PHD, is Associate Dean and Full Professor in the School of Information Science and Engineering at Central South University in Changsha, China.

Texte du rabat

An in-depth look at the latest research, methods, and applications in the field of protein bioinformatics This book presents the latest developments in protein bioinformatics, introducing for the first time cutting-edge research results alongside novel algorithmic and AI methods for the analysis of protein data. In one complete, self-contained volume, Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics addresses key challenges facing both computer scientists and biologists, arming readers with tools and techniques for analyzing and interpreting protein data and solving a variety of biological problems. Featuring a collection of authoritative articles by leaders in the field, this work focuses on the analysis of protein sequences, structures, and interaction networks using both traditional algorithms and AI methods. It also examines, in great detail, data preparation, simulation, experiments, evaluation methods, and applications. Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics: Highlights protein analysis applications such as protein-related drug activity comparison Incorporates salient case studies illustrating how to apply the methods outlined in the book Tackles the complex relationship between proteins from a systems biology point of view Relates the topic to other emerging technologies such as data mining and visualization * Includes many tables and illustrations demonstrating concepts and performance figures Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics is an essential reference for bioinformatics specialists in research and industry, and for anyone wishing to better understand the rich field of protein bioinformatics.

Contenu

PREFACE ix

CONTRIBUTORS xv

I FROM PROTEIN SEQUENCE TO STRUCTURE

1 EMPHASIZING THE ROLE OF PROTEINS IN CONSTRUCTION OF THE DEVELOPMENTAL GENETIC TOOLKIT IN PLANTS 3
Anamika Basu and Anasua Sarkar

2 PROTEIN SEQUENCE MOTIF INFORMATION DISCOVERY 41
Bernard Chen

3 IDENTIFYING CALCIUM BINDING SITES IN PROTEINS 57
Hui Liu and Hai Deng

4 REVIEW OF IMBALANCED DATA LEARNING FOR PROTEIN METHYLATION PREDICTION 71
Zejin Ding and Yan-Qing Zhang

5 ANALYSIS AND PREDICTION OF PROTEIN POSTTRANSLATIONAL MODIFICATION SITES 91
Jianjiong Gao, Qiuming Yao, Curtis Harrison Bollinger, and Dong Xu

II PROTEIN ANALYSIS AND PREDICTION

6 PROTEIN LOCAL STRUCTURE PREDICTION 109
Wei Zhong, Jieyue He, Robert W. Harrison, Phang C. Tai, and Yi Pan

7 PROTEIN STRUCTURAL BOUNDARY PREDICTION 125
Gulsah Altun

8 PREDICTION OF RNA BINDING SITES IN PROTEINS 153
Zhi-Ping Liu and Luonan Chen

9 ALGORITHMIC FRAMEWORKS FOR PROTEIN DISULFIDE CONNECTIVITY DETERMINATION 171
Rahul Singh, William Murad, and Timothy Lee

10 PROTEIN CONTACT ORDER PREDICTION: UPDATE 205
Yi Shi, Jianjun Zhou, David S. Wishart, and Guohui Lin

11 PROGRESS IN PREDICTION OF OXIDATION STATES OF CYSTEINES VIA COMPUTATIONAL APPROACHES 217
Aiguo Du, Hui Liu, Hai Deng, and Yi Pan

12 COMPUTATIONAL METHODS IN CRYOELECTRON MICROSCOPY 3D STRUCTURE RECONSTRUCTION 231
Fa Zhang, Xiaohua Wan, and Zhiyong Liu

III PROTEIN STRUCTURE ALIGNMENT AND ASSESSMENT

13 FUNDAMENTALS OF PROTEIN STRUCTURE ALIGNMENT 255
Mark Brandt, Allen Holder, and Yosi Shibberu

14 DISCOVERING 3…