Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics

ISBN-13: 9781118345788 / Angielski / Twarda / 2013 / 536 str.

Yi Pan

Opis

Delivered by one of the leading bioinformaticians in the field, this book teaches the basis of protein bioinformatics by incorporating articles from an array of industry and academic professionals.

Spis treści

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 3D PROTEIN STRUCTURES FOR OPTIMAL STRUCTURE ALIGNMENT 281
Tomá Novosád, Václav Sná el, Ajith Abraham, and Jack Y. Yang

15 ALGORITHMIC METHODOLOGIES FOR DISCOVERY OF NONSEQUENTIAL PROTEIN STRUCTURE SIMILARITIES 299
Bhaskar DasGupta, Joseph Dundas, and Jie Liang

16 FRACTAL RELATED METHODS FOR PREDICTING PROTEIN STRUCTURE CLASSES AND FUNCTIONS 317
Zu–Guo Yu, Vo Anh, Jian–Yi Yang, and Shao–Ming Zhu

17 PROTEIN TERTIARY MODEL ASSESSMENT 339
Anjum Chida, Robert W. Harrison, and Yan–Qing Zhang

IV PROTEIN PROTEIN ANALYSIS OF BIOLOGICAL NETWORKS

18 NETWORK ALGORITHMS FOR PROTEIN INTERACTIONS 357
Suely Oliveira

19 IDENTIFYING PROTEIN COMPLEXES FROM PROTEIN PROTEIN INTERACTION NETWORKS 377
Jianxin Wang, Min Li, and Xiaoqing Peng

20 PROTEIN FUNCTIONAL MODULE ANALYSIS WITH PROTEIN PROTEIN INTERACTION (PPI) NETWORKS 393
Lei Shi, Xiujuan Lei, and Aidong Zhang

21 EFFICIENT ALIGNMENTS OF METABOLIC NETWORKS WITH BOUNDED TREEWIDTH 413
Qiong Cheng, Piotr Berman, Robert W. Harrison, and Alexander Zelikovsky

22 PROTEIN PROTEIN INTERACTION NETWORK ALIGNMENT: ALGORITHMS AND TOOLS 431
Valeria Fionda

V APPLICATION OF PROTEIN BIOINFORMATICS

23 PROTEIN–RELATED DRUG ACTIVITY COMPARISON USING SUPPORT VECTOR MACHINES 451
Wei Zhong and Jieyue He

24 FINDING REPETITIONS IN BIOLOGICAL NETWORKS: CHALLENGES, TRENDS, AND APPLICATIONS 461
Simona E. Rombo

25 MeTaDoR: ONLINE RESOURCE AND PREDICTION SERVER FOR MEMBRANE TARGETING PERIPHERAL PROTEINS 481
Nitin Bhardwaj, Morten Källberg, Wonhwa Cho, and Hui Lu

26 BIOLOGICAL NETWORKS BASED ANALYSIS OF GENE EXPRESSION SIGNATURES 495
Gang Chen and Jianxin Wang

INDEX 507

O autorze

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.

Blurb

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.