@inbook{4849,
  title = {New Frontiers in Characterizing Structure and Dynamics by NMR},
  booktitle = {Computational Structural Biology: Methods and Applications},
  abstract = {Nuclear Magnetic Resonance (NMR) spectroscopy has emerged as the method of choice for studying
  both the structure and the dynamics of biological macromolecule in solution. Despite the maturity
  of the NMR method for structure determination, its application faces a number of challenges. The
  method is limited to systems of relatively small molecular mass, data collection times are long,
  data analysis remains a lengthy procedure, and it is difficult to evaluate the quality of the final
  structures. The last years have seen significant advances in experimental techniques to overcome
  or reduce some limitations.
  The function of bio-macromolecules is determined by both their 3D structure and conformational
  dynamics. These molecules are inherently flexible systems displaying a broad range of
  dynamics on time–scales from picoseconds to seconds. NMR is unique in its ability to obtain dynamic
  information on an atomic scale. The experimental information on structure and dynamics
  is intricately mixed. It is however difficult to unite both structural and dynamical information into
  one consistent model, and protocols for the determination of structure and dynamics are performed
  independently.
  This chapter deals with the challenges posed by the interpretation of NMR data on structure
  and dynamics. We will first relate the standard structure calculation methods to Bayesian probability
  theory. We will then briefly describe the advantages of a fully Bayesian treatment of structure
  calculation. Then, we will illustrate the advantages of using Bayesian reasoning at least partly in
  standard structure calculations. The final part will be devoted to interpretation of experimental
  data on dynamics.},
  pages = {655-680},
  editors = {Schwede, T. , M. C. Peitsch},
  publisher = {World Scientific},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  address = {New Jersey, NJ, USA},
  month = may,
  year = {2008},
  slug = {4849},
  author = {Nilges, M. and Markwick, P. and Malliavin, TE. and Rieping, W. and Habeck, M.},
  month_numeric = {5}
}