An invaluable tool in Bioinformatics, this unique volume provides
both theoretical and experimental results, and describes basic
principles of computational intelligence and pattern analysis while
deepening the reader's understanding of the ways in which these
principles can be used for analyzing biological data in an
efficient manner.
This book synthesizes current research in the integration of
computational intelligence and pattern analysis techniques, either
individually or in a hybridized manner. The purpose is to analyze
biological data and enable extraction of more meaningful
information and insight from it. Biological data for analysis
include sequence data, secondary and tertiary structure data, and
microarray data. These data types are complex and advanced methods
are required, including the use of domain-specific knowledge for
reducing search space, dealing with uncertainty, partial truth and
imprecision, efficient linear and/or sub-linear scalability,
incremental approaches to knowledge discovery, and increased level
and intelligence of interactivity with human experts and decision
makers
* Chapters authored by leading researchers in CI in biology
informatics.
* Covers highly relevant topics: rational drug design; analysis
of microRNAs and their involvement in human diseases.
* Supplementary material included: program code and relevant data
sets correspond to chapters.
Autorentext
Dr. Ujjwal Maulik is Professor of Computer Science and Engineering at Jadavpur University (India). He is the editor or author of five books and coauthor of more than 150 articles. Dr. Maulik is a Senior Member of IEEE and also a Humboldt Fellow.
Dr. Sanghamitra Bandyopadhyay is Professor at the Indian Statistical Institute. She is the editor or author of six books and coauthor of more than 180 articles. Dr. Bandyopadhyay is a Senior Member of IEEE and also a Humboldt Fellow.
Dr. Jason T. L. Wang is a Professor and Director of the Data and Knowledge Engineering Lab at the New Jersey Institute of Technology. He is the editor or author of six books and Executive Editor of the World Scientific Book Series on Science, Engineering, and Biology Informatics.
Klappentext
An expert review of recent developments in CI in biological informatics
In the field of biological informatics, new methods of data collection that gather huge amounts of data and produce new data types have spurred advanced methods of searching for useful regularities or patterns in these data sets. Of these methods, computational intelligence has found particular favor among researchers. This book synthesizes current research in the integration of computational intelligence and pattern analysis techniques.
Computational Intelligence and Pattern Analysis in Biological Informatics brings together research articles by active practitioners, reporting recent advances in integrating computational intelligence and pattern analysis techniques for analyzing biological data in order to extract more meaningful information and insights from them. It covers highly relevant topics, including rational drug design and the involvement of microRNAs in human diseases. The book:
- Presents a description of some of CI's important components, fundamental concepts in pattern analysis, and different issues in biological informatics
- Gives detailed descriptions of the different applications of computational intelligence and pattern analysis techniques to biological informatics
- Provides details on analysis of sequences, structures, and microarray data, as well as an examination of topics in systems biology
Packed with theoretical and experimental results, Computational Intelligence and Pattern Analysis in Biological Informatics deepens the understanding?of?the ways?in which the basic principles of computational intelligence and pattern analysis can be used for analyzing biological data in an efficient manner. Graduate students and researchers in computer science, bioinformatics, computational and molecular biology, biochemistry, systems science, and information technology will find this unique volume a valuable tool.
Zusammenfassung
An invaluable tool in Bioinformatics, this unique volume provides both theoretical and experimental results, and describes basic principles of computational intelligence and pattern analysis while deepening the reader's understanding of the ways in which these principles can be used for analyzing biological data in an efficient manner.
This book synthesizes current research in the integration of computational intelligence and pattern analysis techniques, either individually or in a hybridized manner. The purpose is to analyze biological data and enable extraction of more meaningful information and insight from it. Biological data for analysis include sequence data, secondary and tertiary structure data, and microarray data. These data types are complex and advanced methods are required, including the use of domain-specific knowledge for reducing search space, dealing with uncertainty, partial truth and imprecision, efficient linear and/or sub-linear scalability, incremental approaches to knowledge discovery, and increased level and intelligence of interactivity with human experts and decision makers
- Chapters authored by leading researchers in CI in biology informatics.
- Covers highly relevant topics: rational drug design; analysis of microRNAs and their involvement in human diseases.
- Supplementary material included: program code and relevant data sets correspond to chapters.
Inhalt
Preface.
Contributors.
PART 1 INTRODUCTION.
1 Computational Intelligence: Foundations, Perspectives, and Recent Trends (Swagatam Das, Ajith Abraham, and B. K. Panigrahi).
2 Fundamentals of Pattern Analysis: A Brief Overview (Basabi Chakraborty).
3 Biological Informatics: Data, Tools, and Applications (Kevin Byron, Miguel Cervantes-Cervantes, and Jason T. L. Wang).
PART II SEQUENCE ANALYSIS.
4 Promoter Recognition Using Neural Network Approaches (T. Sobha Rani, S. Durga Bhavani, and S. Bapi Raju).
5 Predicting microRNA Prostate Cancer Target Genes (Francesco Masulli, Stefano Rovetta, and Giuseppe Russo).
PART III STRUCTURE ANALYSIS.
6 Structural Search in RNA Motif Databases (Dongrong Wen and Jason T. L. Wang).
7 Kernels on Protein Structures (Sourangshu Bhattacharya, Chiranjib Bhattacharyya, and Nagasuma R. Chandra).
8 Characterization of Conformational Patterns in Active and Inactive Forms of Kinases using Protein Blocks Approach (G. Agarwal, D. C. Dinesh, N. Srinivasan, and Alexandre G. de Brevern).
9 Kernel Function Applications in Cheminformatics (Aaron Smalter and Jun Huan).
10 In Silico Drug Design Using a Computational Intelligence Technique (Soumi Sengupta and Sanghamitra Bandyopadhyay).
PART IV MICROARRAY DATA ANALYSIS.
11 Integrated Differential Fuzzy Clustering for Analysis of Microarray Data (Indrajit Saha and Ujjwal Maulik).
12 Identifying Potential Gene Markers Using SVM Classifier Ensemble (Anirban Mukhopadhyay, Ujjwal Maulik, and Sanghamitra Bandyopadhyay).
13 Gene Microarray Data Analysis Using Parallel Point Symmetry-Based Clustering (Ujjwal Maulik and Anasua Sarkar).
PART V SYSTEMS BIOLOGY.
14 Techniques for Prioritization of Candidate Disease Genes (Jieun Jeong and Jake Y. Chen).
15 Prediction of ProteinProtein Interactions (Angshuman Bagchi).
16 Analyzing Topolog…