Data Analysis In Biochemistry And Biophysics

Data Analysis in Biochemistry and Biophysics

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

Computational Biochemistry and Biophysics

Covering theoretical methods and computational techniques in biomolecular research, this book focuses on approaches for the treatment of macromolecules, including proteins, nucleic acids, and bilayer membranes. It uses concepts in free energy calculations, conformational analysis, reaction rates, and transition pathways to calculate and interpret b

UCSF General Catalog