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Systems Biology by Fred Boogerd,Frank J. Bruggeman,Jan-Hendrik S. Hofmeyr,H.V. Westerhoff Pdf
Systems biology is a vigorous and expanding discipline, in many ways a successor to genomics and perhaps unprecedented in its combination of biology with a great many other sciences, from physics to ecology, from mathematics to medicine, and from philosophy to chemistry. Studying the philosophical foundations of systems biology may resolve a longer standing issue, i.e., the extent to which Biology is entitled to its own scientific foundations rather than being dominated by existing philosophies. * Answers the question of what distinguishes the living from the non-living * An in-depth look to a vigorous and expanding discipline, from molecule to system * Explores the region between individual components and the system
Fundamentals of Systems Biology by Markus W. Covert Pdf
For decades biology has focused on decoding cellular processes one gene at a time, but many of the most pressing biological questions, as well as diseases such as cancer and heart disease, are related to complex systems involving the interaction of hundreds, or even thousands, of gene products and other factors. How do we begin to understand this complexity? Fundamentals of Systems Biology: From Synthetic Circuits to Whole-cell Models introduces students to methods they can use to tackle complex systems head-on, carefully walking them through studies that comprise the foundation and frontier of systems biology. The first section of the book focuses on bringing students quickly up to speed with a variety of modeling methods in the context of a synthetic biological circuit. This innovative approach builds intuition about the strengths and weaknesses of each method and becomes critical in the book’s second half, where much more complicated network models are addressed—including transcriptional, signaling, metabolic, and even integrated multi-network models. The approach makes the work much more accessible to novices (undergraduates, medical students, and biologists new to mathematical modeling) while still having much to offer experienced modelers--whether their interests are microbes, organs, whole organisms, diseases, synthetic biology, or just about any field that investigates living systems.
Foundations of Systems Biology by Masao Nagasaki,Ayumu Saito,Atsushi Doi,Hiroshi Matsuno,Satoru Miyano Pdf
Today, as hundreds of genomes have been sequenced and thousands of proteins and more than ten thousand metabolites have been identi?ed, navigating safely through this wealth of information without getting completely lost has become crucial for research in, and teaching of, molecular biology. Consequently, a considerable number of tools have been developed and put on the market in the last two decades that describe the multitude of potential/putative interactions between genes, proteins, metabolites, and other biologically relevant compounds in terms of metabolic, genetic, signaling, and other networks, their aim being to support all sorts of explorations through bio-data bases currently called Systems Biology. As a result, navigating safely through this wealth of information-processing tools has become equally crucial for successful work in molecular biology. To help perform such navigation tasks successfully, this book starts by providing an extremely useful overview of existing tools for ?nding (or designing) and inv- tigating metabolic, genetic, signaling, and other network databases, addressing also user-relevant practical questions like • Is the database viewable through a web browser? • Is there a licensing fee? • What is the data type (metabolic, gene regulatory, signaling, etc. )? • Is the database developed/maintained by a curator or a computer? • Is there any software for editing pathways? • Is it possible to simulate the pathway? It then goes on to introduce a speci?c such tool, that is, the fabulous “Cell - lustrator 3. 0” tool developed by the authors.
Computational Systems Biology by Andres Kriete,Roland Eils Pdf
This comprehensively revised second edition of Computational Systems Biology discusses the experimental and theoretical foundations of the function of biological systems at the molecular, cellular or organismal level over temporal and spatial scales, as systems biology advances to provide clinical solutions to complex medical problems. In particular the work focuses on the engineering of biological systems and network modeling. Logical information flow aids understanding of basic building blocks of life through disease phenotypes Evolved principles gives insight into underlying organizational principles of biological organizations, and systems processes, governing functions such as adaptation or response patterns Coverage of technical tools and systems helps researchers to understand and resolve specific systems biology problems using advanced computation Multi-scale modeling on disparate scales aids researchers understanding of dependencies and constraints of spatio-temporal relationships fundamental to biological organization and function.
The Conceptual Foundations of Systems Biology by James A. Marcum Pdf
James Marcum provides an analysis of the fundamental concepts that constitute the foundations of contemporary systems biology. These concepts include holism, emergentism, and robustness, and are compared to the concepts, reductionism, mechanism, and homeostasis, which form the foundations of molecular biology. In an introductory chapter, a brief history of systems biology is reconstructed, along with the issues surrounding the definition and methodology of systems biology, and a discussion of chaos and complexity theories and their relationship to systems biology. Also included in the chapter is a discussion of whether contemporary systems biology represents a Kuhnian paradigm shift or scientific revolution. In the next three chapters, the fundamental concepts of holism, emergentism, and robustness are examined in detail. The notion of holism is discussed first, since it is the major characteristic of systems biology. It is developed in response to the notion of reductionism, which historically is the main approach to the investigation of complex natural phenomena. The notion of emergence is explored in the next chapter and entails the process by which complex phenomena and their properties appear at higher levels of organisation. It is compared to the notion of mechanism, which molecular biologists use to explain ultimately natural phenomena. The final fundamental concept, robustness, is discussed in a following chapter and is contrasted to the notion of homeostasis. It refers to the functional capability or property of a system to maintain its integrity and performance in response to either internal or external perturbations or disturbances, which could compromise a system's stability. In a fifth chapter, cancer is used as a case study to exemplify systems biology's conceptual foundations as applied to disease. In a penultimate chapter, the challenges facing systems biology are discussed, along with the challenges facing its application to cancer biology. In a concluding chapter, the question is addressed whether systems biology is a revolutionary replacement of molecular biology for investigating and understanding biological phenomena.
Modeling in Systems Biology by Ina Koch,Wolfgang Reisig,Falk Schreiber Pdf
The emerging, multi-disciplinary field of systems biology is devoted to the study of the relationships between various parts of a biological system, and computer modeling plays a vital role in the drive to understand the processes of life from an holistic viewpoint. Advancements in experimental technologies in biology and medicine have generated an enormous amount of biological data on the dependencies and interactions of many different molecular cell processes, fueling the development of numerous computational methods for exploring this data. The mathematical formalism of Petri net theory is able to encompass many of these techniques. This essential text/reference presents a comprehensive overview of cutting-edge research in applications of Petri nets in systems biology, with contributions from an international selection of experts. Those unfamiliar with the field are also provided with a general introduction to systems biology, the foundations of biochemistry, and the basics of Petri net theory. Further chapters address Petri net modeling techniques for building and analyzing biological models, as well as network prediction approaches, before reviewing the applications to networks of different biological classification. Topics and features: investigates the modular, qualitative modeling of regulatory networks using Petri nets, and examines an Hybrid Functional Petri net simulation case study; contains a glossary of the concepts and notation used in the book, in addition to exercises at the end of each chapter; covers the topological analysis of metabolic and regulatory networks, the analysis of models of signaling networks, and the prediction of network structure; provides a biological case study on the conversion of logical networks into Petri nets; discusses discrete modeling, stochastic modeling, fuzzy modeling, dynamic pathway modeling, genetic regulatory network modeling, and quantitative analysis techniques; includes a Foreword by Professor Jens Reich, Professor of Bioinformatics at Humboldt University and Max Delbrück Center for Molecular Medicine in Berlin. This unique guide to the modeling of biochemical systems using Petri net concepts will be of real utility to researchers and students of computational biology, systems biology, bioinformatics, computer science, and biochemistry.
Foundations of Theoretical Approaches in Systems Biology by Alberto Marin-Sanguino,Julio Vera,Rui Alves Pdf
If biology in the 20th century was characterized by an explosion of new technologies and experimental methods, that of the 21st has seen an equally exuberant proliferation of mathematical and computational methods that attempt to systematize and explain the abundance of available data. As we live through the consolidation of a new paradigm where experimental data goes hand in hand with computational analysis, we contemplate the challenge of fusing these two aspects of the new biology into a consistent theoretical framework. Whether systems biology will survive as a field or be washed away by the tides of future fads will ultimately depend on its success to achieve this type of synthesis. The famous quote attributed to Kurt Lewin comes to mind: "there is nothing more practical than a good theory". This book presents a wide assortment of articles on systems biology in an attempt to capture the variety of current methods in systems biology and show how they can help to find answers to the challenges of modern biology.
Drawing on the latest research in the field, Systems Biology: Mathematical Modeling and Model Analysis presents many methods for modeling and analyzing biological systems, in particular cellular systems. It shows how to use predictive mathematical models to acquire and analyze knowledge about cellular systems. It also explores how the models are systematically applied in biotechnology. The first part of the book introduces biological basics, such as metabolism, signaling, gene expression, and control as well as mathematical modeling fundamentals, including deterministic models and thermodynamics. The text also discusses linear regression methods, explains the differences between linear and nonlinear regression, and illustrates how to determine input variables to improve estimation accuracy during experimental design. The second part covers intracellular processes, including enzymatic reactions, polymerization processes, and signal transduction. The author highlights the process–function–behavior sequence in cells and shows how modeling and analysis of signal transduction units play a mediating role between process and function. The third part presents theoretical methods that address the dynamics of subsystems and the behavior near a steady state. It covers techniques for determining different time scales, sensitivity analysis, structural kinetic modeling, and theoretical control engineering aspects, including a method for robust control. It also explores frequent patterns (motifs) in biochemical networks, such as the feed-forward loop in the transcriptional network of E. coli. Moving on to models that describe a large number of individual reactions, the last part looks at how these cellular models are used in biotechnology. The book also explains how graphs can illustrate the link between two components in large networks with several interactions.
Systems and Synthetic Biology by Vikram Singh,Pawan K. Dhar Pdf
This textbook has been conceptualized to provide a detailed description of the various aspects of Systems and Synthetic Biology, keeping the requirements of M.Sc. and Ph.D. students in mind. Also, it is hoped that this book will mentor young scientists who are willing to contribute to this area but do not know from where to begin. The book has been divided into two sections. The first section will deal with systems biology – in terms of the foundational understanding, highlighting issues in biological complexity, methods of analysis and various aspects of modelling. The second section deals with the engineering concepts, design strategies of the biological systems ranging from simple DNA/RNA fragments, switches and oscillators, molecular pathways to a complete synthetic cell will be described. Finally, the book will offer expert opinions in legal, safety, security and social issues to present a well-balanced information both for students and scientists.
An Introduction to Systems Biology by Uri Alon Pdf
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.
Evolutionary Systems Biology by Anton Crombach Pdf
This new edition captures the advances made in the field of evolutionary systems biology since the publication of the first edition. The first edition focused on laying the foundations of evolutionary systems biology as an interdisciplinary field, where a way of thinking and asking questions is combined with a wide variety of tools, both experimental and theoretical/computational. Since publication of the first edition, evolutionary systems biology is now a well-known term describing this growing field. The new edition provides an overview of the current status and future developments of this interdisciplinary field. Chapters highlight several key achievements from the last decade and outline exciting new developments, including an understanding of the interplay between complexity and predictability in evolutionary systems, new viewpoints and methods to study organisms in evolving populations at the level of the genome, gene regulatory network, and metabolic network, and better analysis and modeling techniques that will open new avenues of scientific inquiry.
Systems Biomedicine by Edison T. Liu,Douglas A. Lauffenburger Pdf
Systems biology is a critical emerging field that quantifies and annotates the complexity of biological systems in order to construct algorithmic models to predict outcomes from component input. Applications in medicine are revolutionizing our understanding of biological processes and systems. Systems Biomedicine is organized around foundations, computational modeling, network biology, and integrative biology, with the extension of examples from human biology and pharmacology, to focus on the applications of systems approaches to medical problems. An integrative approach to the underlying genomic, proteomic, and computational biology principles provides researchers with guidance in the use of qualitative systems and hypothesis generators. To reflect the highly interdisciplinary nature of the field, careful detail has been extended to ensure explanations of complex mathematical and biological principles are clear with minimum technical jargon. Organized to reflect the important distinguishing characteristics of systems strategies in experimental biology and medicine Provides precise and comprehensive measurement tools for constructing a model of the system and tools for defining complexity as an experimental dependent variable Includes a thorough discussion of the applications of quantitative principles to biomedical problems
