- 432 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Analysis Of Biological Systems
About this book
Modeling is fast becoming fundamental to understanding the processes that define biological systems. High-throughput technologies are producing increasing quantities of data that require an ever-expanding toolset for their effective analysis and interpretation. Analysis of high-throughput data in the context of a molecular interaction network is particularly informative as it has the potential to reveal the most relevant network modules with respect to a phenotype or biological process of interest.
Analysis of Biological Systems collects classical material on analysis, modeling and simulation, thereby acting as a unique point of reference. The joint application of statistical techniques to extract knowledge from big data and map it into mechanistic models is a current challenge of the field, and the reader will learn how to build and use models even if they have no computing or math background. An in-depth analysis of the currently available technologies, and a comparison between them, is also included. Unlike other reference books, this in-depth analysis is extended even to the field of language-based modeling. The overall result is an indispensable, self-contained and systematic approach to a rapidly expanding field of science.
Contents:
- Algorithmic Systems Biology
- Setting the Context
- Systems and Models
- Static Modeling Technologies
- Dynamic Modeling Technologies
- Language-based Modeling
- Dynamic Modeling Process
- Simulation
- Perspectives and Conclusions
- Appendix A: Basic Math
- Appendix B: Probability and Statistics
- Appendix C: Semantics of Modeling Languages
Readership: Graduate students in computer science, physics, mathematics or engineering or biology-related fields who want to better understand how to develop and use models of biological systems. Practitioners in systems biology who want to understand algorithmic modeling and algorithmic systems biology.
Key Features:
- The book jointly deals with static (statistical) and dynamic (simulation) technologies making it a strong reference for who wants to approach real systems biology problems
- The content of the book is the result of more than ten years application of the material in university courses and to industrial-level problems in systems pharmacology and systems nutrition
- There is no reference work available for the field of language-based modeling that is studied in depth in this book
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Information
Table of contents
- Cover Page
- Title Page
- Copyright Page
- Dedication
- Preface
- Acknowledgments
- Contents
- 1. Algorithmic systems biology
- 2. Setting the context
- 3. Systems and models
- 4. Static modeling technologies
- 5. Dynamic modeling technologies
- 6. Language-based modeling
- 7. Dynamic modeling process
- 8. Simulation
- 9. Perspectives and conclusions
- Appendix A Basic math
- Appendix B Probability and statistics
- Appendix C Semantics of modeling languages
- Bibliography
- Index