Bayesian Difference Refinement
نویسندگان
چکیده
منابع مشابه
Bayesian difference refinement.
Interest in a pair of highly isomorphous structures often focuses on the differences between them. In cases where substantial correlated model errors exist or where there are differences in the quality of the two experimental data sets (cases quite common in macromolecular crystallography), independent refinement of the two structures does not lead to the most accurate estimate of the differenc...
متن کاملTheory Refinement on Bayesian Networks
Theory refinement is the task of updating a domain theory in the light of new cases, to be done automatically or with some expert as sistance. The problem of theory refinement under uncertainty is reviewed here in the con text of Bayesian statistics, a theory of belief revision. The problem is reduced to an incre mental learning task as follows: the learning system is initially primed with a...
متن کاملFinding Bayesian Difference Networks
Often in biological analysis, identifying the differences in the interactions among attributes between two subpopulations—a difference network—is important. For example, identifying the gene interactions that differ between tumor and non-tumor patients would be extremely useful. We have developed a method based upon Bayesian network learning for finding interactions among attributes that appear...
متن کاملRefinement and Difference for Probabilistic Automata
This paper studies a difference operator for stochastic systems whose specifications are represented by Abstract Probabilistic Automata (APAs). In the case refinement fails between two specifications, the target of this operator is to produce a specification APA that represents all witness PAs of this failure. Our contribution is an algorithm that permits to approximate the difference of two de...
متن کاملBayesian weighting for macromolecular crystallographic refinement.
A simple weighting scheme for atomic refinement is discussed. The approach, called 'Bayesian weighting', is designed to be robust with respect to the bias that arises from the incomplete nature of the atomic model, which in macromolecular crystallography is typically quite serious. Bayesian weights are based on the mean-squared residual errors over shells of resolution, with centric and acentri...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Acta Crystallographica Section D Biological Crystallography
سال: 1996
ISSN: 0907-4449
DOI: 10.1107/s0907444996006725