The aim of this volume is to brief researchers of the importance of data analysis in enzymology, of the modern methods that have developed concomitantly with computer hardware, and of the need to validate their computer programs with real and synthetic data to ascertain that the results produced are what they expected.
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Distributions of Estimated Model Parameters. Singular Value Decomposition: Application to Analysis of Experimental Data. Fourier Resolution Enhancement of Infrared Spectral Data. Maximum Likelihood Analysis of Fluorescence Data. Method of Moments and Treatment of Nonrandom Error. Laplace Deconvolution of Fluroescence Decay Surfaces. Interpolation Methods. Compartmental Analysis of Fluorescence Decay Surfaces of Excited-State Processes. Analysis of Discrete, Time-Sampled Data Using Fourier Series Method. Alternatives to Consider in
Fluorescence Decay Analysis. Practical Aspects of Kinetic Analysis. Compartmental Analysis of Enzyme-Catalyzed Reactions. Analysis of Site-Specific Interaction Parameters in Protein*b1DNA Complexes. Analysis of Circular Dichroism Spectra. Fluorescence Quenching Studies: Analysis of Nonlinear Stern*b1Volmer Data. Simultaneous Analysis for Testing of Models and Parameter Estimation. Numerical Analysis of Binding Data: Advantages, Practical Aspects, and Implications. Deconvolution Analysis for Pulsed-Laser Photoacoustics. Parameter Estimation in Binary Mixtures of Phospholipids.
Deconvolution Analysis of Hormone Data. Dynamic Programming Algorithms for Biological Sequence Comparison. Programs for Symbolic Mathematics in Biochemistry. Artificial Neural Networks. Fractal Applications in Biology: Scaling Time in Biochemical Networks. Author Index. Subject Index.