title: Metainference: A Bayesian inference method for heterogeneous systems.
abstract: Modeling a complex system is almost invariably a challenging task. The incorporation of experimental observations can be used to improve the quality of a model and thus to obtain better predictions about the behavior of the corresponding system. This approach, however, is affected by a variety of different errors, especially when a system simultaneously populates an ensemble of different states and experimental data are measured as averages over such states. To address this problem, we present a Bayesian inference method, called "metainference," that is able to deal with errors in experimental measurements and with experimental measurements averaged over multiple states. To achieve this goal, metainference models a finite sample of the distribution of models using a replica approach, in the spirit of the replica-averaging modeling based on the maximum entropy principle. To illustrate the method, we present its application to a heterogeneous model system and to the determination of an ensemble of structures corresponding to the thermal fluctuations of a protein molecule. Metainference thus provides an approach to modeling complex systems with heterogeneous components and interconverting between different states by taking into account all possible sources of errors.
authors: Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, UK.
authors: Massimiliano
authors: M
authors: Bonomi
authors: Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, UK.
authors: Carlo
authors: 0000-0002-9923-8590
authors: C
authors: Camilloni
authors: Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, UK.; Institute for Research in Biomedicine, CH-6500 Bellinzona, Switzerland.
authors: Andrea
authors: 0000-0003-4063-4502
authors: A
authors: Cavalli
authors: Department of Chemistry, University of Cambridge, Cambridge CB2 1EW, UK.
authors: Michele
authors: M
authors: Vendruscolo
mesh_terms: D001499:Bayes Theorem; D019277:Entropy; D008962:Models, Theoretical; D011506:Proteins / Q000737:chemistry
chemical_list: D011506:Proteins
keywords: Statistical inference; maximum entropy principle; structural biology