Nonlinear Computer Modeling of Chemical and Biochemical Data

Author: James F. Rusling
Publisher: Academic Press
ISBN: 0080537685
Format: PDF, ePub, Mobi
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Assuming only background knowledge of algebra and elementary calculus, and access to a modern personal computer, Nonlinear Computer Modeling of Chemical and Biochemical Data presents the fundamental basis and procedures of data modeling by computer using nonlinear regression analysis. Bypassing the need for intermediary analytical stages, this method allows for rapid analysis of highly complex processes, thereby enabling reliable information to be extracted from raw experimental data. By far the greater part of the book is devoted to selected applications of computer modeling to various experiments used in chemical and biochemical research. The discussions include a short review of principles and models for each technique, examples of computer modeling for real and theoretical data sets, and examples from the literature specific to each instrumental technique. The book also offers detailed tutorial on how to construct suitable models and a score list of appropriate mathematics software packages.

Advanced Excel for Scientific Data Analysis

Author: Robert De Levie
Publisher: Oxford University Press, USA
ISBN: 0195152751
Format: PDF, ePub, Mobi
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Excel is by far the most widely distributed data analysis software but few users are aware of its full powers. Advanced Excel For Scientific Data Analysis takes off from where most books dealing with scientific applications of Excel end. It focuses on three areas-least squares, Fourier transformation, and digital simulation-and illustrates these with extensive examples, often taken from the literature. It also includes and describes a number of sample macros and functions to facilitate common data analysis tasks. These macros and functions are provided in uncompiled, computer-readable, easily modifiable form; readers can therefore use them as starting points for making their own personalized data analysis tools. Detailed descriptions and sample applications of standard and specialized uses of least squares for fitting data to a variety of functions, including resolving multi-component spectra; standard processes such as calibration curves and extrapolation; custom macros for general "error" propagation, standard deviations of Solver results, weighted or equidistant least squares, Gram-Schmidt orthogonalization, Fourier transformation, convolution and deconvolution, time-frequency analysis, and data mapping. There are also worked examples showing how to use centering, the covariance matrix, imprecision contours, and Wiener filtering and custom functions for bisections, Lagrange interpolation, Euler and Runge-Kutta integration.

Fitting Models to Biological Data Using Linear and Nonlinear Regression

Author: Harvey Motulsky
Publisher: Oxford University Press
ISBN: 0190291397
Format: PDF, ePub, Mobi
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Most biologists use nonlinear regression more than any other statistical technique, but there are very few places to learn about curve-fitting. This book, by the author of the very successful Intuitive Biostatistics, addresses this relatively focused need of an extraordinarily broad range of scientists.

Fitting Models to Biological Data Using Linear and Nonlinear Regression

Author: Harvey Motulsky
Publisher: Oxford University Press
ISBN: 9780198038344
Format: PDF, ePub, Mobi
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Most biologists use nonlinear regression more than any other statistical technique, but there are very few places to learn about curve-fitting. This book, by the author of the very successful Intuitive Biostatistics, addresses this relatively focused need of an extraordinarily broad range of scientists.

An Introduction to Nonlinear Chemical Dynamics

Author: Irving R. Epstein
Publisher: Oxford University Press
ISBN: 9780198025665
Format: PDF, Mobi
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Just a few decades ago, chemical oscillations were thought to be exotic reactions of only theoretical interest. Now known to govern an array of physical and biological processes, including the regulation of the heart, these oscillations are being studied by a diverse group across the sciences. This book is the first introduction to nonlinear chemical dynamics written specifically for chemists. It covers oscillating reactions, chaos, and chemical pattern formation, and includes numerous practical suggestions on reactor design, data analysis, and computer simulations. Assuming only an undergraduate knowledge of chemistry, the book is an ideal starting point for research in the field. The book begins with a brief history of nonlinear chemical dynamics and a review of the basic mathematics and chemistry. The authors then provide an extensive overview of nonlinear dynamics, starting with the flow reactor and moving on to a detailed discussion of chemical oscillators. Throughout the authors emphasize the chemical mechanistic basis for self-organization. The overview is followed by a series of chapters on more advanced topics, including complex oscillations, biological systems, polymers, interactions between fields and waves, and Turing patterns. Underscoring the hands-on nature of the material, the book concludes with a series of classroom-tested demonstrations and experiments appropriate for an undergraduate laboratory.

Multiscale Analysis and Nonlinear Dynamics

Author: Misha Meyer Pesenson
Publisher: John Wiley & Sons
ISBN: 352767165X
Format: PDF, ePub
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Since modeling multiscale phenomena in systems biology and neuroscience is a highly interdisciplinary task, the editor of the book invited experts in bio-engineering, chemistry, cardiology, neuroscience, computer science, and applied mathematics, to provide their perspectives. Each chapter is a window into the current state of the art in the areas of research discussed and the book is intended for advanced researchers interested in recent developments in these fields. While multiscale analysis is the major integrating theme of the book, its subtitle does not call for bridging the scales from genes to behavior, but rather stresses the unifying perspective offered by the concepts referred to in the title. It is believed that the interdisciplinary approach adopted here will be beneficial for all the above mentioned fields.

Computational Intelligence Techniques for Bioprocess Modelling Supervision and Control

Author: Maria Carmo Nicoletti
Publisher: Springer Science & Business Media
ISBN: 3642018874
Format: PDF, ePub, Docs
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Computational Intelligence (CI) and Bioprocess are well-established research areas which have much to offer each other. Under the perspective of the CI area, Biop- cess can be considered a vast application area with a growing number of complex and challenging tasks to be dealt with, whose solutions can contribute to boosting the development of new intelligent techniques as well as to help the refinement and s- cialization of many of the already existing techniques. Under the perspective of the Bioprocess area, CI can be considered a useful repertoire of theories, methods and techniques that can contribute and offer interesting alternative approaches for solving many of its problems, particularly those hard to solve using conventional techniques. Although throughout the past years CI and Bioprocess areas have accumulated substantial specific knowledge and progress has been quick and with a high degree of success, we believe there is still a long way to go in order to use the potentialities of the available CI techniques and knowledge at their full extent, as tools for supporting problem solving in bioprocesses. One of the reasons is the fact that both areas have progressed steadily and have been continuously accumulating and refining specific knowledge; another reason is the high level of technical expertise demanded by each of them. The acquisition of technical skills, experience and good insights in either of the two areas is very demanding and a hard task to be accomplished by any professional.