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An understanding of biological systems at cellular and molecular levels helps researchers to model cellular behavior in different experimental conditions. This, in turn, can lead to insights about the influence of cell culture environment and the effect of knockout gene research when studying mutations that affect specific metabolic pathways. A systems biology approach, therefore, allows researchers to simulate experimental observations in order to predict outcomes at the cellular level. Fundamentals of Systems Analysis and Modeling of Biosystems and Metabolism presents the basic concepts required for a systems biology approach towards cellular modeling. The book is intended as a primer for systems biology and biomedical engineering graduates and researchers. The text introduces readers to concepts related to cellular metabolism and its regulation, (enzymatic regulation and transcriptional regulation) which are also incorporated into a main metabolic model of a cell. The book also has chapters dedicated to identifying and incorporating steady-state and dynamic characteristics when considering a biological model for a computer simulation. Readers will be able to (1) understand the basis of systems analysis towards creating appropriate biological models and simulations, (2) develop useful kinetic models based on cellular transport phenomena and metabolic regulation, (3) understand how to simulate a cell growth phenotype, and analyze it with experimental data.
The global warming problem is becoming critical year by year, causing climate disaster all over the world, where it has been believed that the CO2 gas emitted from the factories and the burning of fossil fuels may be one of the reasons of global warming. Moreover, the global stock of fossil fuels is limited, and may run out soon within several tens of years. Although wind, geo-thermal, and tide energies have been considered as clean energy sources, those depend on the land or sea locations and subject to the climate change. Biofuel and biochemical production from renewable bio-resources has thus been paid recent attention from environmental protection and energy production points of view, where the current chemical and energy producing plants can be also utilized with slight modification. The so-called 1st generation biofuels have been produced from corn starch and sugarcane in particular in USA and Brazil. However, this causes the problem of the so-called "food and energy issues" as the production scale increases. The 2nd generation biofuel production from lingo-cellulosic biomass or wastes has thus been paid recent attention. However, it requires energy intensive pretreatment for the degradation of lingo-cellulosic biomass, and the fermentation is slow due to low growth rate, and thus the productivity of biofuels and bio-chemicals is low. The 3rd generation biofuel production from photosynthetic organisms such as cyanobacteria and algae has been also paid attention, because such organisms can grow with only sun light and CO2 in the air, but the cell growth rate and thus the productivity of the fuels is significantly low. The main part or core of such production processes is the fermentation by micro-organisms. In particular, it is critical to properly understand the cell metabolism followed by the efficient metabolic engineering. The book gives comprehensive explanation of the cell metabolism and the metabolic regulation mechanisms of a variety of micro-organisms. Then the efficient metabolic engineering approaches are explained to properly design the microbial cell factories for the efficient cell growth and biofuel and biochemical production.
A comprehensive overview of the topic, highlighting recent developments, ongoing research trends and future directions. Experts from Europe, Asia and the US cover five core areas of imminent importance to the food, feed, pharmaceutical and water treatment industries in terms of sustainable and innovative processing and production. In the field of enzyme engineering, they summarize historic developments and provide an overview of molecular enzyme engineering, while also discussing key principles of microbial process engineering, including chapters on process development and control. Further sections deal with animal and plant cell culture engineering. The final section of the book deals with environmental topics and highlights the application of bioengineering principles in waste treatment and the recovery of valuable resources. With its cutting-edge visions, extensive discussions and unique perspectives, this is a ready reference for biotechnologists, bioengineers, bioengineers, biotechnological institutes, and environmental chemists.
This book constitutes the thoroughly refereed post-conference proceedings of the 13th International Conference on Membrane Computing, CMC 2012, held in Budapest, Hungary, in August 2012. The 21 revised selected papers presented together with 6 invited lectures were carefully reviewed and selected from 25 papers presented at the conference. The book also deals with membrane systems, also called P systems, which are distributed and parallel algebraic models processing multisets of objects in a localized manner (evolution rules and evolving objects are encapsulated into compartments delimited by membranes), with an essential role played by the communication among compartments and with the environment.
This advanced textbook is tailored for an introductory course in Systems Biology and is well-suited for biologists as well as engineers and computer scientists. It comes with student-friendly reading lists and a companion website featuring a short exam prep version of the book and educational modeling programs. The text is written in an easily accessible style and includes numerous worked examples and study questions in each chapter. For this edition, a section on medical systems biology has been included.
The book presents topics in discrete biomathematics. Mathematics has been widely used in modeling biological phenomena. However, the molecular and discrete nature of basic life processes suggests that their logic follow principles that are intrinsically based on discrete and informational mechanisms. The ultimate reason of polymers, as key element of life, is directly based on the computational power of strings, and the intrinsic necessity of metabolism is related to the mathematical notion of multiset. The switch of the two roots of bioinformatics suggests a change of perspective. In bioinformatics, the biologists ask computer scientists to assist them in processing biological data. Conversely, in infobiotics mathematicians and computer scientists investigate principles and theories yielding new interpretation keys of biological phenomena. Life is too important to be investigated by biologists alone, and though computers are essential to process data from biological laboratories, many fundamental questions about life can be appropriately answered by a perspicacious intervention of mathematicians, computer scientists, and physicists, who will complement the work of chemists, biochemists, biologists, and medical investigators. The volume is organized in seven chapters. The first part is devoted to research topics (Discrete information and life, Strings and genomes, Algorithms and Biorhythms, Life Strategies), the second one to mathematical backgrounds (Numbers and Measures, Languages and Grammars, Combinations and Chances).
This textbook is uniquely crafted for use in teaching undergraduate students in the life, math, computer and other sciences and engineering. It is INTRODUCTORY LEVEL, for students who have taken or are currently completing their undergraduate math requirements, and are acquiring analytical-thinking and doing skills, along with introductory biology, chemistry and physics subject matter. It's about learning HOW to model and simulate dynamic biological systems, which also makes it useful for graduate students and professional researchers who want a more rigorous treatment of introductory life science math modeling, integrated with the biology. It brings together the multidisciplinary pedagogy of these subjects into a SINGLE INTRODUCTORY MODELING METHODOLOGY COURSE, crystalizing the experience of an author who has been teaching dynamic biosystems modeling and simulation methodology for the life sciences for more than 50 years. DiStefano maximizes accessibility and "systems-math-biology" integration - without diminishing conceptual rigor. Minimally essential applied math and SYSTEMS ENGINEERING METHODS are included, along with a synopsis of the biology and physiology underlying dynamic biosystem modeling, all in a modeling pedagogy context. This textbook fills a major need in the training of contemporary biology students.Dynamic biosystems modeling methodology is presented over 12 distinctive chapters, primarily with systems diagrams and simple differential equations and algebra for expressing them quantitatively, integrated with the biology. Solving and analyzing (quantifying) the biomodels are then accomplished by simulation, using a facile control system simulation language Simulink, a GUI/Matlab toolbox that emulates control systems diagramming, rather than by "coding" the model in a standard computer programming language. Students see and work with the system model - not the code - a big plus. Higher math and complex analytical solutions are avoided.Each chapter begins with a list of LEARNING GOALS, to help with both perspective for the chapter material, and retrospective, to measure learning. EXERCISES for the student at the end of each chapter are designed to test and reinforce learning. A SOLUTIONS MANUAL for chapter exercises is available to qualified instructors from the author, as are LECTURE SLIDES and LAB ASSIGNMENTS AND SOLUTIONS, for courses that adopt the textbook for student use.
Systems and Synthetic Metabolic Engineering provides an overview of the development of metabolic engineering within medicine that is fueled by systems and synthetic biology. These newly developed, successful strategies of metabolic engineering guide the audience on how to propose and test proper strategies for metabolic engineering research. In addition to introductory, regulatory and challenges in the field, the book also covers dynamic control and autonomous regulation to control cell metabolism, along with computational modeling and industrial applications. The book is written by leaders in the field, making it ideal for synthetic biologists, researchers, students and anyone working in this area. - Discusses the current progress of metabolic engineering, focusing on systems biology and synthetic biology - Covers introductory, regulatory, strategies, production and challenges in the field - Written technically for synthetic biologists, researchers, students, industrialists, policymakers and stakeholders
Membrane Computing was introduced as a computational paradigm in Natural Computing. The models introduced, called Membrane (or P) Systems, provide a coherent platform to describe and study living cells as computational systems. Membrane Systems have been investigated for their computational aspects and employed to model problems in other fields, like: Computer Science, Linguistics, Biology, Economy, Computer Graphics, Robotics, etc. Their inherent parallelism, heterogeneity and intrinsic versatility allow them to model a broad range of processes and phenomena, being also an efficient means to solve and analyze problems in a novel way. Membrane Computing has been used to model biological systems, becoming with time a thorough modeling paradigm comparable, in its modeling and predicting capabilities, to more established models in this area. This book is the result of the need to collect, in an organic way, different facets of this paradigm. The chapters of this book, together with the web pages accompanying them, present different applications of Membrane Systems to Biology. Deterministic, non-deterministic and stochastic systems paired with different algorithms and methodologies show the full potential of this framework. The book is addressed to researchers interested in applications of discrete biological models and the interplay between Membrane Systems and other approaches to analyze complex systems.