Biophysical Methods for Biotherapeutics

Biophysical Chemistry is an outstanding book that delivers both fundamental and complex biophysical principles, along with an excellent overview of the current biophysical research areas, in a manner that makes it accessible for mathematically and non-mathematically inclined readers. (Journal of Chemical Biology, February 2009) This text presents physical chemistry through the use of biological and biochemical topics, examples and applications to biochemistry. It lays out the necessary calculus in a step by step fashion for students who are less mathematically inclined, leading them through fundamental concepts, such as a quantum mechanical description of the hydrogen atom rather than simply stating outcomes. Techniques are presented with an emphasis on learning by analyzing real data. Presents physical chemistry through the use of biological and biochemical topics, examples and applications to biochemistry Lays out the necessary calculus in a step by step fashion for students who are less mathematically inclined Presents techniques with an emphasis on learning by analyzing real data Features qualitative and quantitative problems at the end of each chapter All art available for download online and on CD-ROM

The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. «This book, it must be said, lives up to the words on its advertising cover: 'Bridging the gap between introductory, descriptive approaches and highly advanced theoretical treatises, it provides a practical, intermediate level discussion of a variety of forecasting tools, and explains how they relate to one another, both in theory and practice.' It does just that!» -Journal of the Royal Statistical Society «A well-written work that deals with statistical methods and models that can be used to produce short-term forecasts, this book has wide-ranging applications. It could be used in the context of a study of regression, forecasting, and time series analysis by PhD students; or to support a concentration in quantitative methods for MBA students; or as a work in applied statistics for advanced undergraduates.» -Choice Statistical Methods for Forecasting is a comprehensive, readable treatment of statistical methods and models used to produce short-term forecasts. The interconnections between the forecasting models and methods are thoroughly explained, and the gap between theory and practice is successfully bridged. Special topics are discussed, such as transfer function modeling; Kalman filtering; state space models; Bayesian forecasting; and methods for forecast evaluation, comparison, and control. The book provides time series, autocorrelation, and partial autocorrelation plots, as well as examples and exercises using real data. Statistical Methods for Forecasting serves as an outstanding textbook for advanced undergraduate and graduate courses in statistics, business, engineering, and the social sciences, as well as a working reference for professionals in business, industry, and government.

This updated and up-to-date version of the first edition continues with the really interesting stuff to spice up a standard biophysics and biophysical chemistry course. All relevant methods used in current cutting edge research including such recent developments as super-resolution microscopy and next-generation DNA sequencing techniques, as well as industrial applications, are explained. The text has been developed from a graduate course taught by the author for several years, and by presenting a mix of basic theory and real-life examples, he closes the gap between theory and experiment. The first part, on basic biophysical chemistry, surveys fundamental and spectroscopic techniques as well as biomolecular properties that represent the modern standard and are also the basis for the more sophisticated technologies discussed later in the book. The second part covers the latest bioanalytical techniques such as the mentioned super-resolution and next generation sequencing methods, confocal fluorescence microscopy, light sheet microscopy, two-photon microscopy and ultrafast spectroscopy, single molecule optical, electrical and force measurements, fluorescence correlation spectroscopy, optical tweezers, quantum dots and DNA origami techniques. Both the text and illustrations have been prepared in a clear and accessible style, with extended and updated exercises (and their solutions) accompanying each chapter. Readers with a basic understanding of biochemistry and/or biophysics will quickly gain an overview of cutting edge technology for the biophysical analysis of proteins, nucleic acids and other biomolecules and their interactions. Equally, any student contemplating a career in the chemical, pharmaceutical or bio-industry will greatly benefit from the technological knowledge presented. Questions of differing complexity testing the reader's understanding can be found at the end of each chapter with clearly described solutions available on the Wiley-VCH textbook homepage under: www.wiley-vch.de/textbooks

The subject of computational plasticity encapsulates the numerical methods used for the finite element simulation of the behaviour of a wide range of engineering materials considered to be plastic – i.e. those that undergo a permanent change of shape in response to an applied force. Computational Methods for Plasticity: Theory and Applications describes the theory of the associated numerical methods for the simulation of a wide range of plastic engineering materials; from the simplest infinitesimal plasticity theory to more complex damage mechanics and finite strain crystal plasticity models. It is split into three parts – basic concepts, small strains and large strains. Beginning with elementary theory and progressing to advanced, complex theory and computer implementation, it is suitable for use at both introductory and advanced levels. The book: Offers a self-contained text that allows the reader to learn computational plasticity theory and its implementation from one volume. Includes many numerical examples that illustrate the application of the methodologies described. Provides introductory material on related disciplines and procedures such as tensor analysis, continuum mechanics and finite elements for non-linear solid mechanics. Is accompanied by purpose-developed finite element software that illustrates many of the techniques discussed in the text, downloadable from the book’s companion website. This comprehensive text will appeal to postgraduate and graduate students of civil, mechanical, aerospace and materials engineering as well as applied mathematics and courses with computational mechanics components. It will also be of interest to research engineers, scientists and software developers working in the field of computational solid mechanics.

The first book on the innovative study of biointerfaces using biophysical chemistry The biophysical phenomena that occur on biointerfaces, or biological surfaces, hold a prominent place in the study of biology and medicine, and are crucial for research relating to implants, biosensors, drug delivery, proteomics, and many other important areas. Biophysical Chemistry of Biointerfaces takes the unique approach of studying biological systems in terms of the principles and methods of physics and chemistry, drawing its knowledge and experimental techniques from a wide variety of disciplines to offer new tools to better understand the intricate interactions of biointerfaces. Biophysical Chemistry of Biointerfaces: Provides a detailed description of the thermodynamics and electrostatics of soft particles Fully describes the biophysical chemistry of soft interfaces and surfaces (polymer-coated interfaces and surfaces) as a model for biointerfaces Delivers many approximate analytic formulas which can be used to describe various interfacial phenomena and analyze experimental data Offers detailed descriptions of cutting-edge topics such as the biophysical and interfacial chemistries of lipid membranes and gel surfaces, which serves as good model for biointerfaces in microbiology, hematology, and biotechnology Biophysical Chemistry of Biointerfaces pairs sound methodology with fresh insight on an emerging science to serve as an information-rich reference for professional chemists as well as a source of inspiration for graduate and postdoctoral students looking to distinguish themselves in this challenging field.

The first book on the innovative study of biointerfaces using biophysical chemistry The biophysical phenomena that occur on biointerfaces, or biological surfaces, hold a prominent place in the study of biology and medicine, and are crucial for research relating to implants, biosensors, drug delivery, proteomics, and many other important areas. Biophysical Chemistry of Biointerfaces takes the unique approach of studying biological systems in terms of the principles and methods of physics and chemistry, drawing its knowledge and experimental techniques from a wide variety of disciplines to offer new tools to better understand the intricate interactions of biointerfaces. Biophysical Chemistry of Biointerfaces: Provides a detailed description of the thermodynamics and electrostatics of soft particles Fully describes the biophysical chemistry of soft interfaces and surfaces (polymer-coated interfaces and surfaces) as a model for biointerfaces Delivers many approximate analytic formulas which can be used to describe various interfacial phenomena and analyze experimental data Offers detailed descriptions of cutting-edge topics such as the biophysical and interfacial chemistries of lipid membranes and gel surfaces, which serves as good model for biointerfaces in microbiology, hematology, and biotechnology Biophysical Chemistry of Biointerfaces pairs sound methodology with fresh insight on an emerging science to serve as an information-rich reference for professional chemists as well as a source of inspiration for graduate and postdoctoral students looking to distinguish themselves in this challenging field.

The mathematical and statistical tools needed in the rapidly growing quantitative finance field With the rapid growth in quantitative finance, practitioners must achieve a high level of proficiency in math and statistics. Mathematical Methods and Statistical Tools for Finance, part of the Frank J. Fabozzi Series, has been created with this in mind. Designed to provide the tools needed to apply finance theory to real world financial markets, this book offers a wealth of insights and guidance in practical applications. It contains applications that are broader in scope from what is covered in a typical book on mathematical techniques. Most books focus almost exclusively on derivatives pricing, the applications in this book cover not only derivatives and asset pricing but also risk management—including credit risk management—and portfolio management. Includes an overview of the essential math and statistical skills required to succeed in quantitative finance Offers the basic mathematical concepts that apply to the field of quantitative finance, from sets and distances to functions and variables The book also includes information on calculus, matrix algebra, differential equations, stochastic integrals, and much more Written by Sergio Focardi, one of the world's leading authors in high-level finance Drawing on the author's perspectives as a practitioner and academic, each chapter of this book offers a solid foundation in the mathematical tools and techniques need to succeed in today's dynamic world of finance.

The first time that such a complete systematic analysis of the mathematical and numerical techniques related to the orthogonal methods has been given. With the explosion of the wireless world, greater emphasis than ever before is being placed on the effective design of antennas. Orthogonal Methods for Array Synthesis outlines several procedures of orthogonal methods suitable for antenna array synthesis. The book presents a simple approach to the design of antenna arrays to enable the reader to use the classical Orthogonal Method for synthesis of linear arrays. This theory-based book, which includes rapid, effective solutions to design problems for communications applications and broadcasting, is amply illustrated with real-world examples and case studies. Also included in the book is the ORAMA MS Windows-compatible computer tool, patented by Professor Sahalos and his team. Provides comprehensive coverage of the basic principles of orthogonal methods including an analytical explanation of the orthogonal method (OM) and the orthogonal perturbation method (OP) Gives rapid, cost-effective solutions to antenna design problems for communications applications and broadcasting Illustrates all theory with practical applications gleaned from the author’s extensive experience in the field of orthogonal advanced methods for antennas Providing a complete guide to the theory and applications of the Orthogonal Methods, this book is a must-read for antenna engineers and graduate students of electrical and computer engineering and physics.

Praise for the Second Edition «As a comprehensive statistics reference book for quality improvement, it certainly is one of the best books available.» —Technometrics This new edition continues to provide the most current, proven statistical methods for quality control and quality improvement The use of quantitative methods offers numerous benefits in the fields of industry and business, both through identifying existing trouble spots and alerting management and technical personnel to potential problems. Statistical Methods for Quality Improvement, Third Edition guides readers through a broad range of tools and techniques that make it possible to quickly identify and resolve both current and potential trouble spots within almost any manufacturing or nonmanufacturing process. The book provides detailed coverage of the application of control charts, while also exploring critical topics such as regression, design of experiments, and Taguchi methods. In this new edition, the author continues to explain how to combine the many statistical methods explored in the book in order to optimize quality control and improvement. The book has been thoroughly revised and updated to reflect the latest research and practices in statistical methods and quality control, and new features include: Updated coverage of control charts, with newly added tools The latest research on the monitoring of linear profiles and other types of profiles Sections on generalized likelihood ratio charts and the effects of parameter estimation on the properties of CUSUM and EWMA procedures New discussions on design of experiments that include conditional effects and fraction of design space plots New material on Lean Six Sigma and Six Sigma programs and training Incorporating the latest software applications, the author has added coverage on how to use Minitab software to obtain probability limits for attribute charts. new exercises have been added throughout the book, allowing readers to put the latest statistical methods into practice. Updated references are also provided, shedding light on the current literature and providing resources for further study of the topic. Statistical Methods for Quality Improvement, Third Edition is an excellent book for courses on quality control and design of experiments at the upper-undergraduate and graduate levels. the book also serves as a valuable reference for practicing statisticians, engineers, and physical scientists interested in statistical quality improvement.

Statistical data are not always precise numbers, or vectors, or categories. Real data are frequently what is called fuzzy. Examples where this fuzziness is obvious are quality of life data, environmental, biological, medical, sociological and economics data. Also the results of measurements can be best described by using fuzzy numbers and fuzzy vectors respectively. Statistical analysis methods have to be adapted for the analysis of fuzzy data. In this book, the foundations of the description of fuzzy data are explained, including methods on how to obtain the characterizing function of fuzzy measurement results. Furthermore, statistical methods are then generalized to the analysis of fuzzy data and fuzzy a-priori information. Key Features: Provides basic methods for the mathematical description of fuzzy data, as well as statistical methods that can be used to analyze fuzzy data. Describes methods of increasing importance with applications in areas such as environmental statistics and social science. Complements the theory with exercises and solutions and is illustrated throughout with diagrams and examples. Explores areas such quantitative description of data uncertainty and mathematical description of fuzzy data. This work is aimed at statisticians working with fuzzy logic, engineering statisticians, finance researchers, and environmental statisticians. It is written for readers who are familiar with elementary stochastic models and basic statistical methods.