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Systems Biology and In-Depth Applications for Unlocking Diseases: Principles, Tools, and Application to Disease

Editat de Babak Sokouti
en Limba Engleză Paperback – dec 2024
Systems Biology and In-Depth Applications for Unlocking Diseases: Principles, tools and Application to Disease provides the essence of systems biology approaches in a practical manner, illustrating the basic principles essential to develop and model in real life science applications. Methodologies covered show how to interrogate biological data, with the purpose of obtaining insight about disease diagnosis, prognosis, and treatment. Sections provide an introduction and history of systems biology, discuss the tools and resources needed for structure and function of biological systems, and present evidence of systems biology in action. Examples include big data techniques, scale networks, mathematical model development, and much more. This is the perfect reference to provide the fundamental base of knowledge needed for systems biologists, professionals in systems medicine, computational biologists, and bioinformaticians.


  • Provides detailed and comprehensive coverage of the field of systems biology
  • Delivers instruction on how to interrogate biological data, with the purpose of obtaining insight about disease diagnosis, prognosis, and treatment
  • Makes effective steps towards personalized medicine in the treatment of disease
  • Explains effective disease treatment strategies at early diagnosis stages
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Specificații

ISBN-13: 9780443223266
ISBN-10: 0443223262
Pagini: 300
Dimensiuni: 216 x 276 mm
Editura: ELSEVIER SCIENCE

Cuprins

Part 1. Introduction 1.1 Systems biology at a glance 1.2. A history on systems biology evolution 1.3. Brief information on cellular biology and signaling pathways 1.4. Systems biology: where are we? 1.5. Filling the gaps between systems biology and cell biology 1.6 Concluding remarks 1.7 Mathematical concepts 1.5. Kinetic and dynamics of biological systems Part 2. Tools and Resources 2.1. Biological data sources 2.1.1. Microarray 2.1.2. Next generation sequencing (NGS) 2.1.3. Comparative genomic hybridization (CGH) 2.1.4. Single nucleotide polymorphisms (SNP) 2.2. High throughput data 2.1.2. Databases 2.3. Programming, tools and software Part 3. Systems biology in action – to understand diseases 3.1 Big data analysis techniques 3.2 Reconstruction of genome and proteomic scale network structures and functions 3.3 Validation strategies 3.3.1 Mathematical model development 3.3.2 Biological gene expression models 3.3.3 Experimental techniques 3.4 Applications of systems biology extensions in diseases 3.4.1 Systems immunology 3.4.2 Systems pharmacology 3.4.3 Systems virology 3.4.4 Systems vaccinology 3.4.5 Systems neuroscience 3.4.6 Systems medicine 3.4.7 Future directions on systems biology