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 micro RNAs and their involvement in human diseases.
* Supplementary material included: program code and relevant data
sets correspond to chapters.
Cuprins
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 micro RNA 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 Protein-Protein Interactions
(Angshuman Bagchi).
16 Analyzing Topological Properties of Protein-Protein
Interaction Networks: A Perspective Toward Systems Biology
(Malay Bhattacharyya and Sanghamitra Bandyopadhyay).
Index.
Despre autor
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.
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