Analysis of Biological Systems

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. These modules denote the borders of the interacting molecular components that contribute to a specific biological process, and thus constitute a natural starting point for building dynamic models. 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 modelling. The overall result is an indispensable, self-contained and systematic approach to a rapidly expanding field of science.

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