This book presents the theoretical foundations of Systems Biology, as well as its application in studies on human hosts, pathogens and associated diseases. This book presents several chapters written by renowned experts in the field. Some topics discussed in depth in this book include: computational modeling of multiresistant bacteria, systems biology of cancer, systems immunology, networks in systems biology.

A survey of how engineering techniques from control and systems theory can be used to help biologists understand the behavior of cellular systems.

This collective monograph aims at contributing to an improved understanding of the epistemic presumptions, sociocultural implications and historically backgrounds of the newly emerging and currently expanding approach of systems biology. In doing so, it offers empirically grounded, valuable and reflexive information about a paradigmatic shift in the biosciences for a wide range of scientists working in the interdisciplinary areas of systems biology, synthetic biology, molecular biology, biology, the philosophy of science, the sociology of science and scientific knowledge, science and technology studies, technology assessment and the like. The authors of this monograph share the theoretical methodological premise that science is a culturally and socially embedded practice which characterizes our culture as a scientific one and at the same time draws its innovative potential from its socio-cultural context. This dialectic relationship lies at the heart of the current development of systems biology which is conceived as a so-called successor of ‘-omics’ research and triggered by high-throughput information technologies. At the same time a need for a holistic conceptualization of complex biological processes emerges. The title Contextualizing Systems Biology suggests that this book analyzes the development and advent of systems biology from different theoretical and methodological perspectives. We investigate a variety of contexts ranging from the analysis of cognitive contexts (such as basic theoretical concepts) to regulative contexts (policies) to the concrete application of a systems biology in the socio-scientific context of a European research project. In empirically analyzing these different and interrelated layers and dimensions of systems biology, the scope of the book goes beyond present attempts to investigate the advent of new approaches in the biological sciences as it frames and assesses systems biology from an interdisciplinary and integrated perspective.

This book presents a range of current research topics in biological network modeling, as well as its application in studies on human hosts, pathogens, and diseases. Systems biology is a rapidly expanding field that involves the study of biological systems through the mathematical modeling and analysis of large volumes of biological data. Gathering contributions from renowned experts in the field, some of the topics discussed in depth here include networks in systems biology, the computational modeling of multidrug-resistant bacteria, and systems biology of cancer. Given its scope, the book is intended for researchers, advanced students, and practitioners of systems biology. The chapters are research-oriented, and present some of the latest findings on their respective topics.

This textbook focuses on stochastic analysis in systems biology containing both the theory and application. While the authors provide a review of probability and random variables, subsequent notions of biochemical reaction systems and the relevant concepts of probability theory are introduced side by side. This leads to an intuitive and easy-to-follow presentation of stochastic framework for modeling subcellular biochemical systems. In particular, the authors make an effort to show how the notion of propensity, the chemical master equation and the stochastic simulation algorithm arise as consequences of the Markov property. The text contains many illustrations, examples and exercises to illustrate the ideas and methods that are introduced. Matlab code is also provided where appropriate. Additionally, the cell cycle is introduced as a more complex case study. Senior undergraduate and graduate students in mathematics and physics as well as researchers working in the area of systems biology, bioinformatics and related areas will find this text useful.

Presenting the main concepts, this book leads students as well as advanced researchers from different disciplines to an understanding of current ideas in the complex field of comprehensive experimental investigation of biological objects, analysis of data, development of models, simulation, and hypothesis generation. It provides readers with guidance on how a specific complex biological question may be tackled: - How to formulate questions that can be answered - Which experiments to perform - Where to find information in databases and on the Internet - What kinds of models are appropriate - How to use simulation tools - What can be learned from the comparison of experimental data and modeling results - How to make testable predictions. The authors demonstrate how mathematical concepts can illuminate the principles underlying biology at a genetic, molecular, cellular and even organism level, and how to use mathematical tools for analysis and prediction.

Epigenetics and Systems Biology highlights the need for collaboration between experiments and theoretical modeling that is required for successful application of systems biology in epigenetics studies. This book breaks down the obstacles which exist between systems biology and epigenetics researchers due to information barriers and segmented research, giving real-life examples of successful combinations of systems biology and epigenetics experiments. Each section covers one type of modeling and one set of epigenetic questions on which said models have been successfully applied. In addition, the book highlights how modeling and systems biology relate to studies of RNA, DNA, and genome instability, mechanisms of DNA damage signaling and repair, and the effect of the environment on genome stability. Presents original research in a wider perspective to reveal potential for synergies between the two fields of study Provides the latest experiments in primary literature for the modeling audience Includes chapters written by experts in systems biology and epigenetics who have vast experience studying clinical applications

The complexity of biological systems has intrigued scientists from many disciplines and has given birth to the highly influential field of systems biology wherein a wide array of mathematical techniques, such as flux balance analysis, and technology platforms, such as next generation sequencing, is used to understand, elucidate, and predict the functions of complex biological systems. More recently, the field of synthetic biology, i.e., de novo engineering of biological systems, has emerged. Scientists from various fields are focusing on how to render this engineering process more predictable, reliable, scalable, affordable, and easy. Systems and control theory is a branch of engineering and applied sciences that rigorously deals with the complexities and uncertainties of interconnected systems with the objective of characterising fundamental systemic properties such as stability, robustness, communication capacity, and other performance metrics. Systems and control theory also strives to offer concepts and methods that facilitate the design of systems with rigorous guarantees on these properties. Over the last 100 years, it has made stellar theoretical and technological contributions in diverse fields such as aerospace, telecommunication, storage, automotive, power systems, and others. Can it have, or evolve to have, a similar impact in biology? The chapters in this book demonstrate that, indeed, systems and control theoretic concepts and techniques can have a significant impact in systems and synthetic biology. Volume I provides a panoramic view that illustrates the potential of such mathematical methods in systems and synthetic biology. Recent advances in systems and synthetic biology have clearly demonstrated the benefits of a rigorous and systematic approach rooted in the principles of systems and control theory - not only does it lead to exciting insights and discoveries but it also reduces the inordinately lengthy trial-and-error process of wet-lab experimentation, thereby facilitating significant savings in human and financial resources. In Volume I, some of the leading researchers in the field of systems and synthetic biology demonstrate how systems and control theoretic concepts and techniques can be useful, or should evolve to be useful, in order to understand how biological systems function. As the eminent computer scientist Donald Knuth put it, "biology easily has 500 years of exciting problems to work on". This edited book presents but a small fraction of those for the benefit of (1) systems and control theorists interested in molecular and cellular biology and (2) biologists interested in rigorous modelling, analysis and control of biological systems.

Systems Biology and Its Application in TCM Formulas Research presents a theoretical research system formed for Traditional Chinese Medicine (TCM) formulas, along with information on the study of Shexiang Baoxin Pill (SBP), a TCM formula that has shown significant clinical efficacy in the treatment of cardiovascular diseases. The content combines theory and practice, and includes guidance for both theoretical concepts and operable technical routes. This is a valuable source not only for biomedical researchers involved in Systems Biology studies, but also for students and scientists interested in learning more about Traditional Chinese Medicine and its applications in contemporary medicine. - Explains, in detail, the Shexiang Baoxin Pill (SBP), a TCM formula efficiently applied in the treatment of cardiovascular diseases - Presents TCM formulas from perspectives of systems biology, basic chemical material groups, modern pharmacology and network biology - Offers an overview on biology, modern chemistry and information technology as applied in Systems Biology research

Thorough and accessible, this book presents the design principles of biological systems, and highlights the recurring circuit elements that make up biological networks. It provides a simple mathematical framework which can be used to understand and even design biological circuits. The textavoids specialist terms, focusing instead on several well-studied biological systems that concisely demonstrate key principles. An Introduction to Systems Biology: Design Principles of Biological Circuits builds a solid foundation for the intuitive understanding of general principles. It encourages the reader to ask why a system is designed in a particular way and then proceeds to answer with simplified models.