title: ISD: a software package for Bayesian NMR structure calculation.
abstract: The conventional approach to calculating biomolecular structures from nuclear magnetic resonance (NMR) data is often viewed as subjective due to its dependence on rules of thumb for deriving geometric constraints and suitable values for theory parameters from noisy experimental data. As a result, it can be difficult to judge the precision of an NMR structure in an objective manner. The inferential structure determination (ISD) framework, which has been introduced recently, addresses this problem by using Bayesian inference to derive a probability distribution that represents both the unknown structure and its uncertainty. It also determines additional unknowns, such as theory parameters, that normally need to be chosen empirically. Here we give an overview of the ISD software package, which implements this methodology.
  
  
  BACKGROUND
  http://www.bioc.cam.ac.uk/isd
authors.affiliation: Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge CB2 1GA, UK. wolfgang.rieping@bioc.cam.ac.uk
authors.forename: Wolfgang
authors.initials: W
authors.lastname: Rieping
authors.forename: Michael
authors.initials: M
authors.lastname: Nilges
authors.forename: Michael
authors.initials: M
authors.lastname: Habeck
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D001704:Biopolymers / Q000737:chemistry*; D003198:Computer Simulation; D003461:Crystallography / Q000379:methods*; D009682:Magnetic Resonance Spectroscopy / Q000379:methods*; D008956:Models, Chemical; D008958:Models, Molecular; D010363:Pattern Recognition, Automated / Q000379:methods*
chemical_list: D001704:Biopolymers