Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics
- 9h 45m
- Jianxin Wang, Min Li (eds), Yi Pan
- John Wiley & Sons (US)
- 2014
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.
About the Editors
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.
In this Book
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Emphasizing the Role of Proteins in Construction of the Developmental Genetic Toolkit in Plants
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Protein Sequence Motif Information Discovery
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Identifying Calcium Binding Sites in Proteins
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Review of Imbalanced Data Learning for Protein Methylation Prediction
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Analysis and Prediction of Protein Posttranslational Modification Sites
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Protein Local Structure Prediction
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Protein Structural Boundary Prediction
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Prediction of Rna Binding Sites in Proteins
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Algorithmic Frameworks for Protein Disulfide Connectivity Determination
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Protein Contact Order Prediction—Update
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Progress in Prediction of Oxidation States of Cysteines via Computational Approaches
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Computational Methods in Cryoelectron Microscopy 3D Structure Reconstruction
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Fundamentals of Protein Structure Alignment
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Discovering 3D Protein Structures for Optimal Structure Alignment
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Algorithmic Methodologies for Discovery of Nonsequential Protein Structure Similarities
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Fractal Related Methods for Predicting Protein Structure Classes and Functions
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Protein Tertiary Model Assessment
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Network Algorithms for Protein Interactions
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Identifying Protein Complexes from Protein-Protein Interaction Networks
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Protein Functional Module Analysis with Protein-Protein Interaction (PPI) Networks
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Efficient Alignments of Metabolic Networks with Bounded Treewidth
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Protein-Protein Interaction Network Alignment—Algorithms and Tools
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Protein-Related Drug Activity Comparison Using Support Vector Machines
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Finding Repetitions in Biological Networks—Challenges, Trends, and Applications
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MeTaDoR—Online Resource and Prediction Server for Membrane Targeting Peripheral Proteins
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Biological Networks-Based Analysis of Gene Expression Signatures
