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Full Description
Computational systems biology is a new and rapidly developing field of research, concerned with understanding the structure and processes of biological systems at the molecular, cellular, tissue, and organ levels through computational modeling as well as novel information theoretic data and image analysis methods. By focusing on either information processing of biological data or on modeling physical and chemical processes of biosystems, and in combination with the recent breakthrough in deciphering the human genome, computational systems biology is guaranteed to play a central role in disease prediction and preventive medicine, gene technology and pharmaceuticals, and other biotechnology fields.This book begins by introducing the basic mathematical, statistical, and data mining principles of computational systems biology, and then presents bioinformatics technology in microarray and sequence analysis step-by-step. Offering an insightful look into the effectiveness of the systems approach in computational biology, it focuses on recurrent themes in bioinformatics, biomedical applications, and future directions for research.
Contents
Introduction; Mathematical, Statistical and Data Mining Principles; Missing Value Estimation Using KNN and Bayesian Methods; Normalization, Scaling and Discretization; Cross-Platform Comparison; Discovering Differential Biomarkers; Gene Selection and Classification; Gene Clustering; Gene Prediction; Reverse Engineering: Gene Regulatory Network Construction and Its Behavior; Motif Detection and Transcription Factor Binding Site Identification; Gene Interaction Based on Combined Microarray and Sequence Technology; Protein Structure Informatics; Biomarker Discovery from Proteomics; Bioimaging Informatics; Conclusions.
