دانلود کتاب A Practical Guide To Cancer Systems Biology

Systems biology combines computational and experimental approaches to analyze complex biological systems and focuses on understanding functional activities from a systems-wide perspective. It provides an iterative process of experimental measurements, data analysis, and computational simulation to model biological behavior. This book provides explained protocols for high-throughput experiments and computational analysis procedures central to cancer systems biology research and education. Readers will learn how to generate and analyze high-throughput data, therapeutic target protein structure modeling and docking simulation for drug discovery. This is the first practical guide for students and scientists who wish to become systems biologists or utilize the approach for cancer research. Contents: Introduction to Cancer Systems Biology (Hsueh-Fen Juan and Hsuan-Cheng Huang)Transcriptome Analysis: Library Construction (Hsin-Yi Chang and Hsueh-Fen Juan)Quantitative Proteome: The Isobaric Tags for Relative and Absolute Quantitation (iTRAQ) (Yi-Hsuan Wu and Hsueh-Fen Juan)Phosphoproteome: Sample Preparation (Chia-Wei Hu and Hsueh-Fen Juan)Transcriptomic Data Analysis: RNA-Seq Analysis Using Galaxy (Chia-Lang Hsu and Chantal Hoi Yin Cheung)Proteomic Data Analysis: Functional Enrichment (Hsin-Yi Chang and Hsueh-Fen Juan)Phosphorylation Data Analysis (Chia-Lang Hsu and Wei-Hsuan Wang)Pathway and Network Analysis (Chen-Tsung Huang and Hsueh-Fen Juan)Dynamic Modeling (Yu-Chao Wang)Protein Structure Modeling (Chia-Hsien Lee and Hsueh-Fen Juan)Docking Simulation (Chia-Hsien Lee and Hsueh-Fen Juan) Readership: Graduate students and researchers entering the cancer systems biology field. Keywords: Systems Biology;Transcriptomics;Proteomics;Network Biology;Dynamic Modeling;Protein Structure Modeling;Docking Simulation;BioinformaticsReview: Key Features: Written by two active researchers in the fieldCovers both experimental and computational areas in cancer systems biologyStep-by-step instructions help beginners who are interested in creating biological data and analyzing the data by themselvesReaders will gain the skills to generate and analyze omics data and discover potential therapeutic targets and drug candidates