This book gives a practical introduction to numerical methods and presents BASIC subroutines for real-life computations in the areas of chemistry, biology, and pharmacology. The choice of BASIC as the programming language is motivated by its simplicity, its availability on all personal computers and by its power in data acquisition. While most of the scientific packages currently available in BASIC date back to the period of limited memory and speed, the subroutines presented here can handle a broad range of realistic problems with the power and sophistication needed by professionals and with simple, step-by-step instructions for students and beginners.Please note that a diskette containing the 37 program modules and 39 sample programs listed in the book is no longer available.The main task considered in the book is that of extracting useful information from measurements via modelling, simulation, and statistical data evaluations. Efficient and robust numerical methods have been chosen to solve related problems in numerical algebra, nonlinear equations and optimization, parameter estimation, signal processing, and differential equations. For each class of routines an introduction to the relevant theory and techniques is given, so that the reader will recognise and use the appropriate method for solving his or her particular problem. Simple examples illustrate the use and applicability of each method.

In analytical chemistry and pharmaceutical technology attention is increasingly focussed on improving the quality of methods and products. This book aims at fostering the awareness of the potential of existing mathematical and statistical methods to improve this quality. It provides procedures and ideas on how to make a product or a method less sensitive to small variations in influencing factors. Major issues covered are robustness and stability improvement and ruggedness testing. General strategies and a theoretical introduction to these methods are described, and thorough overviews of methods used in both application areas and descriptions of practical applications are given.Features of this book:• Gives a good overview of mathematical and statistical methods used in two application areas, i.e. pharmaceutical technology and analytical chemistry• Illustrates the different approaches available to attain robustness• Gives ideas on how to use methods in practical situations.The book is intended for those who develop and optimize, and are responsible for the overall quality of, analytical methods and pharmaceutical technological products and procedures.

This book comprises a large selection of papers presented at the second European Scientific Computing and Automation meeting (SCA 90 (Europe)) which was held in June 1990 in Maastricht, The Netherlands. The increasing use of computers for making measurements, interpreting data, and filing results brings a new unity to science. SCA concentrates on common computer-based tools which are useful in several disciplines. Practical problems in laboratory automation, robotics and information management with LIMS are covered in depth. The process of designing and acquiring a LIMS is described and standards for data transfer between instruments, between LIMS and instruments and between different LIMS are discussed. The applications of statistics and expert systems are covered in several chapters. Strategies for drug design are discussed with various practical examples. Finally the display of scientific results as images and computer-based animations is demonstrated by several examples with their color illustrations. The book should be of interest to those managing R&D projects, doing research in laboratories, acquiring or planning LIMS, designing instruments and laboratory automation systems and those involved in data analysis of scientific results.

Wavelets seem to be the most efficient tool in signal denoising and compression. They can be used in an unlimited number of applications in all fields of chemistry where the instrumental signals are the source of information about the studied chemical systems or phenomena, and in all cases where these signals have to be archived. The quality of the instrumental signals determines the quality of answer to the basic analytical questions: how many components are in the studied systems, what are these components like and what are their concentrations? Efficient compression of the signal sets can drastically speed up further processing such as data visualization, modelling (calibration and pattern recognition) and library search. Exploration of the possible applications of wavelets in analytical chemistry has just started and this book will significantly speed up the process. The first part, concentrating on theoretical aspects, is written in a tutorial-like manner, with simple numerical examples. For the reader's convenience, all basic terms are explained in detail and all unique properties of wavelets are pinpointed and compared with the other types of basis function. The second part presents applications of wavelets from many branches of chemistry which will stimulate chemists to further exploration of this exciting subject.

The majority of modern instruments are computerised and provide incredible amounts of data. Methods that take advantage of the flood of data are now available; importantly they do not emulate 'graph paper analyses' on the computer. Modern computational methods are able to give us insights into data, but analysis or data fitting in chemistry requires the quantitative understanding of chemical processes. The results of this analysis allows the modelling and prediction of processes under new conditions, therefore saving on extensive experimentation. Practical Data Analysis in Chemistry exemplifies every aspect of theory applicable to data analysis using a short program in a Matlab or Excel spreadsheet, enabling the reader to study the programs, play with them and observe what happens. Suitable data are generated for each example in short routines, this ensuring a clear understanding of the data structure. Chapter 2 includes a brief introduction to matrix algebra and its implementation in Matlab and Excel while Chapter 3 covers the theory required for the modelling of chemical processes. This is followed by an introduction to linear and non-linear least-squares fitting, each demonstrated with typical applications. Finally Chapter 5 comprises a collection of several methods for model-free data analyses.* Includes a solid introduction to the simulation of equilibrium processes and the simulation of complex kinetic processes.* Provides examples of routines that are easily adapted to the processes investigated by the reader* 'Model-based' analysis (linear and non-linear regression) and 'model-free' analysis are covered

Optimization problems occurring regularly in chemistry, vary from selecting the best wavelength design for optimal spectroscopic concentration predictions to geometry optimization of atomic clusters and protein folding. Numerous optimization tactics have been explored to solve these problems. While most optimizers maintain the ability to locate global optima for simple problems, few are robust against local optima convergence with regard to difficult or large scale optimization problems. Simulated annealing (SA) has shown a great tolerance to local optima convergence and is often called a global optimizer. The optimizaton algorithm has found wide use in numerous areas such as engineering, computer science, communication, image recognition, operation research, physics, and biology. Recently, SA and variations thereof have shown considerable success in solving numerous chemical optimization problems. The main thrust of this book is to demonstrate the use of SA in a wide range of chemical problems.The potentiality of SA, GSA and other modifications of SA to serve specific needs in a variety of chemical disciplines are covered. A detailed discussion on SA and GSA is given in Chapter 1, presenting the theoretical framework from which a computer program can be written by the reader. The remainder of the book describes applications of SA type algorithms to a diverse set of chemical problems. The final chapter contains an algorithm for GSA written in the MatLab programming environment. This program can be easily adapted to any optimization problem and with only slight modifications, can be altered to perform SA. A general flowchart is also given.

Most chemists, whether they are biochemists, organic, analytical, pharmaceutical or clinical chemists and many pharmacists and biologists need to perform chemical analysis. Consequently, they are not only confronted with carrying out the actual analysis, but also with problems such as method selection, experimental design, optimization, calibration, data acquisition and handling, and statistics in order to obtain maximum relevant chemical information. In other words: they are confronted with chemometrics. This book on chemometrics, written by some of the leaders in the field, aims to provide a thorough, up-to-date introduction to this subject. The reader is given the opportunity to acquaint himself with the tools used in this discipline and the way in which they are applied. Some practical examples are given and the reader is shown how to select the appropriate tools in a given situation.As such the book provides the means to approach and solve analytical problems strategically and systematically, without the need for the reader to become a fully-fledged chemometrician. The authors' aim was to write a tutorial book which would be useful to readers at every level in this field.