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The reductionist approach of molecular biology has given us detailed descriptions for many biochemical constituents of complex biological systems. For some of the simpler systems nearly the entire "parts catalog" has been assembled. These developments have set the stage for a new generation of questions -- questions of integration that deal with the relation between behavior of intact systems and their underlying molecular determinants, questions of unifying design principles that will give meaning to the bewildering diversity of alternative molecular designs, questions of higher-level theory and quantitative prediction, which currently are not available in most of biology. The motivation to develop this new perspective comes from the study of complex biochemical pathways, intricate circuits of gene regulation, network interactions within the immune system, plasticity of neural networks, and pattern formation by cellular networks. All these networks consist of more elemental constituents that find their meaning within the context of the intact system. The integrative perspective requires a new language and methodology. The objective of this text is to systematically develop these and to apply them to specific classes of metabolic networks and gene circuitry. The applications demonstrate the power of this approach to formulate and answer fundamental questions concerning network function, design and evolution that currently cannot be addressed by other methods. The text was first published in 1976 and is being reissued to commemorate the 40th anniversary of the author's first paper published on Biochemical Systems Analysis.
This book focuses on counting processes and continuous-time Markov chains motivated by examples and applications drawn from chemical networks in systems biology. The book should serve well as a supplement for courses in probability and stochastic processes. While the material is presented in a manner most suitable for students who have studied stochastic processes up to and including martingales in continuous time, much of the necessary background material is summarized in the Appendix. Students and Researchers with a solid understanding of calculus, differential equations and elementary probability and who are well-motivated by the applications will find this book of interest. David F. Anderson is Associate Professor in the Department of Mathematics at the University of Wisconsin and Thomas G. Kurtz is Emeritus Professor in the Departments of Mathematics and Statistics at that university. Their research is focused on probability and stochastic processes with applications in biology and other areas of science and technology. These notes are based in part on lectures given by Professor Anderson at the University of Wisconsin – Madison and by Professor Kurtz at Goethe University Frankfurt.
Teaches the use of modern computational methods for the analysis of biomedical systems using case studies and accompanying software.
Numerical simulation and modelling have been growing in importance and seeing steadily increasing practical application. The proliferation of applications and physical domains for which simulation technologies are now needed, compounded by generally increased complexity, has expanded the scope of numerical simulation and modelling within CAD and spurred new research directions. Numerical Simulation and Modelling of Electronic and Biochemical Systems provides an introduction to the fundamentals of numerical simulation, and to the basics of modelling electronic circuits and biochemical reactions. The emphasis is on capturing a minimal set of important concepts succinctly, but concretely enough that the reader will be left with an adequate foundation for further independent exploration. Starting from mathematical models of basic electronic elements, circuits are modelled as nonlinear differential-algebraic equation (DAE) systems. Two basic techniques - quiescent steady state and transient - for solving these differential equations systems are then developed. It is then shown how biochemical reactions can also be modelled deterministically as DAEs. Following this, frequency domain techniques for finding sinusoidal steady states of linear DAEs are developed, as are direct and adjoint techniques for computing parameter sensitivities and the effects of stationary random noise. For readers interested in a glimpse of topics beyond these basics, an introduction to nonlinear periodic steady state methods (harmonic balance and shooting) and the multitime partial differential equation formulation is provided. Also provided is an overview of model order reduction, an important topic of current research that has roots in numerical simulation algorithms. Finally, sample applications of nonlinear oscillator macromodels - in circuits (PLLs), biochemical reaction-diffusion systems and nanoelectronics - are presented.
Data Analysis in Biochemistry and Biophysics describes the techniques how to derive the most amount of quantitative and statistical information from data gathered in enzyme kinetics, protein-ligand equilibria, optical rotatory dispersion, chemical relaxation methods. This book focuses on the determination and analysis of parameters in different models that are used in biochemistry, biophysics, and molecular biology. The Michaelis-Menten equation can explain the process to obtain the maximum amount of information by determining the parameters of the model. This text also explains the fundamentals present in hypothesis testing, and the equation that represents the statistical aspects of a linear model occurring frequently in this field of testing. This book also analyzes the ultraviolet spectra of nucleic acids, particularly, to establish the composition of melting regions of nucleic acids. The investigator can use the matrix rank analysis to determine the spectra to substantiate systems whose functions are not known. This text also explains flow techniques and relaxation methods associated with rapid reactions to determine transient kinetic parameters. This book is suitable for molecular biologists, biophysicists, physiologists, biochemists, bio- mathematicians, statisticians, computer programmers, and investigators involved in related sciences
Designed to serve as the first point of reference on the subject, Comprehensive Chemometrics presents an integrated summary of the present state of chemical and biochemical data analysis and manipulation. The work covers all major areas ranging from statistics to data acquisition, analysis, and applications. This major reference work provides broad-ranging, validated summaries of the major topics in chemometrics—with chapter introductions and advanced reviews for each area. The level of material is appropriate for graduate students as well as active researchers seeking a ready reference on obtaining and analyzing scientific data. Features the contributions of leading experts from 21 countries, under the guidance of the Editors-in-Chief and a team of specialist Section Editors: L. Buydens; D. Coomans; P. Van Espen; A. De Juan; J.H. Kalivas; B.K. Lavine; R. Leardi; R. Phan-Tan-Luu; L.A. Sarabia; and J. Trygg Examines the merits and limitations of each technique through practical examples and extensive visuals: 368 tables and more than 1,300 illustrations (750 in full color) Integrates coverage of chemical and biological methods, allowing readers to consider and test a range of techniques Consists of 2,200 pages and more than 90 review articles, making it the most comprehensive work of its kind Offers print and online purchase options, the latter of which delivers flexibility, accessibility, and usability through the search tools and other productivity-enhancing features of ScienceDirect
Navigate the complexities of biochemical thermodynamics with Mathematica(r) Chemical reactions are studied under the constraints of constant temperature and constant pressure; biochemical reactions are studied under the additional constraints of pH and, perhaps, pMg or free concentrations of other metal ions. As more intensive variables are specified, more thermodynamic properties of a system are defined, and the equations that represent thermodynamic properties as a function of independent variables become more complicated. This sequel to Robert Alberty's popular Thermodynamics of Biochemical Reactions describes how researchers will find Mathematica(r) a simple and elegant tool, which makes it possible to perform complex calculations that would previously have been impractical. Biochemical Thermodynamics: Applications of Mathematica(r) provides a comprehensive and rigorous treatment of biochemical thermodynamics using Mathematica(r) to practically resolve thermodynamic issues. Topics covered include: * Thermodynamics of the dissociation of weak acids * Apparent equilibrium constants * Biochemical reactions at specified temperatures and various pHs * Uses of matrices in biochemical thermodynamics * Oxidoreductase, transferase, hydrolase, and lyase reactions * Reactions at 298.15K * Thermodynamics of the binding of ligands by proteins * Calorimetry of biochemical reactions Because Mathematica(r) allows the intermingling of text and calculations, this book has been written in Mathematica(r) and includes a CD-ROM containing the entire book along with macros that help scientists and engineers solve their particular problems.
The first edition of this text, based on the author's 30 years of teaching and research on neurosensory systems, helped biomedical engineering students and professionals strengthen their skills in the common network of applied mathematics that ties together the diverse disciplines that comprise this field. Updated and revised to include new materia
A comprehensive discussion of the various analytical techniques that are carried out in biochemistry, intends to support students in grasping techniques which are of use for theoretical and practical purposes.