DescriptionAn 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.
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 Protein–Protein Interactions (Angshuman Bagchi).
16 Analyzing Topological Properties of Protein–Protein Interaction Networks: A Perspective Toward Systems Biology (Malay Bhattacharyya and Sanghamitra Bandyopadhyay).