As analysis, in terms of detection limits and technological innovation, in chemical and biological fields has developed so computational techniques have advanced enabling greater understanding of the data. Indeed, it is now possible to simulate spectral data to an excellent level of accuracy, allowing chemists and biologists access to robust and reliable analytical methodologies both experimentally and theoretically.
This work will serve as a definitive overview of the field of computational simulation as applied to analytical chemistry and biology, drawing on recent advances as well as describing essential, established theory. Computational approaches provide additional depth to biochemical problems, as well as offering alternative explanations to atomic scale phenomena. Highlighting the innovative and wide-ranging breakthroughs made by leaders in computational spectrum prediction and the application of computational methodologies to analytical science, this book is for graduates and postgraduate researchers showing how computational analytical methods have become accessible across disciplines. Contributed chapters originate from a group of internationally-recognised leaders in the field, each applying computational techniques to develop our understanding of and supplement the data obtained from experimental analytical science.
Univariate and Multivariate Statistical Approaches to the Analysis and Interpretation of NMR-based Metabolomics Datasets of Increasing Complexity; Recent Advances in Computational NMR Spectrum Prediction; Computational Vibrational Spectroscopy: A Contemporary Perspective; Isotope Effects as Analytical Probes: Application of Computational Theory; Applications of Computational Intelligence Techniques in Chemical and Biochemical Analyiss; Computational Spectroscopy and Photophysics in Complex Biological Systems: Towards an in silico Photobiology; Bridging the Gap Between Atomistic Molecular Dynamics Simulations and Wet-lab Experimental Techniques: Applications to Membrane Proteins; Solid State Chemistry: Computational Chemical Analysis for Materials Science; Electron Spin Resonance for the Detection of Paramagnetic Species: from Fundamentals to Computational Methods for Simulation and Interpretation