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This book is intended as a communication platform to bridge the cultural, conceptual, and technological gap among the key systems biology disciplines of biology, mathematics, and information technology. To support this goal, contributors were asked to adopts an approach that appeals to audiences from different backgrounds.
This volume contains papers based on the workshop OC Energy and Information Transfer in Biological Systems: How Physics Could Enrich Biological UnderstandingOCO, held in Italy in 2002. The meeting was a forum aimed at evaluating the potential and outlooks of a modern physics approach to understanding and describing biological processes, especially regarding the transition from the microscopic chemical scenario to the macroscopic functional configurations of living matter. In this frame some leading researchers presented and discussed several basic topics, such as the photon interaction with biological systems also from the viewpoint of photon information processes and of possible applications; the influence of electromagnetic fields on the self-organization of biosystems including the nonlinear mechanism for energy transfer and storage; and the influence of the structure of water on the properties of biological matter."
Living beings require constant information processing for survival. In cells, information is being processed and propagated at various levels, from the gene regulatory network to chemical pathways, to the interaction with the environment. How this is achieved and how information is coded is still poorly understood. For example, what a cell interprets as information in the temporal level of an mRNA and what is interpreted as noise remains an open question. Recently, information theoretical methods and other tools, developed in the context of engineering and natural sciences, have been applied to study diverse biological processes. This book covers the latest findings on how information is processed in various biological processes, ranging from information processing and propagation in gene regulatory networks to information processing in natural language. An overview is presented of the state-of-the-art in information processing in biological systems and the opinion of current leaders in this research field on future research directions.
Systems Biology is the systematic study of the interactions between the components of a biological system and studies how these interactions give rise to the function and behavior of the living system. Through this, a life process is to be understood as a whole system rather than the collection of the parts considered separately. Systems Biology is therefore more than just an emerging field: it represents a new way of thinking about biology with a dramatic impact on the way that research is performed. The logical approach provides an intuitive method to provide explanations based on an expressive relational language. This book covers various aspects of logical modeling of biological systems,...
Investigating Biological Systems Using Modeling describes how to apply software to analyze and interpret data from biological systems. It is written for students and investigators in lay person's terms, and will be a useful reference book and textbook on mathematical modeling in the design and interpretation of kinetic studies of biological systems. It describes the mathematical techniques of modeling and kinetic theory, and focuses on practical examples of analyzing data. The book also uses examples from the fields of physiology, biochemistry, nutrition, agriculture, pharmacology, and medicine. - Contains practical descriptions of how to analyze kinetic data - Provides examples of how to develop and use models - Describes several software packages including SAAM/CONSAM - Includes software with working models
A number of books written by statisticians address the mathematical optimization of biological systems, but do not directly address statistical optimization. Statistical Optimization of Biological Systems covers the optimization of bioprocess systems in its entirety, devoting much-needed attention to the experimental optimization of biological syst
This book introduces students to methods that will help them understand behaviour in terms of cellular components and their interactions in non-intuitive ways, which calls for an interdisciplinary approach combining mathematical, chemical, computational and biological strategies. Tibor Ganti was one of the early pioneers who proposed a theoretical framework to understand living principles in terms of chemical transformation cycles and their coupling. The twenty-first century then brought with it a novel ‘systems’ paradigm, which shone new light on all previous work and was accompanied by numerous implications for the way we conceive of chemical and biological complexity today. This book ...
The exponential increase in computing power in the late twentieth century has allowed researchers to gather, process and analyze large volumes of information and construct rational paradigms of systems. Life sciences are no exception and computing advances have led to the birth of fields such as functional genomics and bioinformatics and facilitated an expansion of our understanding of biological systems. Biological Systems: Complexity and Artificial Life is an essential primer on systems biology for biologists and researchers having a multidisciplinary background. The volume covers a variety of theoretical models explaining biological processes. The book starts with an introductory chapter on the classical molecular biology paradigm and progresses towards concepts related to enzyme kinetics, non equilibrium dynamics, cellular thermodynamics, molecular motion in cells and more. The book concludes with a philosophical note on the concept of the biological system.
Biological structures built through mechanisms involving self-organization are examined in this text. Examples of such structures are termite mounds, which provide their inhabitants with a secure & stable environment. The text looks at why & how self-organization occurs in nature.