title: Benchmarking and refining probability-based models for nucleosome-DNA interaction.
abstract: BACKGROUND
  In investigations of nucleosome positioning preferences, a model that assigns an affinity to a given sequence is necessary to make predictions. One important class of models, which treats a nucleosome sequence as a Markov chain, has been applied with success when informed with experimentally measured nucleosomal sequence preferences.
  
  
  RESULTS
  We find that we can also use such models as a fast approximative scheme for computationally expensive biophysical models, vastly increasing their reach. Employing these models in this way also allows us to benchmark them for the first time. Doing so for the approximative in silico models indirectly tells us about the accuracy we can expect of them when applied to real data.
  
  
  CONCLUSIONS
  We find that models presented in the literature should perform well, but this performance depends on factors such as the order of the Markov model, the preprocessing of the probability distributions on which the model is based, and the size and quality of the sequence ensemble from which those distributions are calculated.
authors.affiliation: Lorentz Institute, Leiden University, Niels Bohrweg 2, Leiden, 2333CA, The Netherlands. tompitak@lorentz.leidenuniv.nl.
authors.forename: Marco
authors.identifier: http://orcid.org/0000-0003-4275-2262
authors.initials: M
authors.lastname: Tompitak
authors.affiliation: Institute for Theoretical Physics, Utrecht University, Princetonplein 5, Utrecht, 3584CC, The Netherlands.
authors.forename: Gerard T
authors.initials: GT
authors.lastname: Barkema
authors.affiliation: Lorentz Institute, Leiden University, Niels Bohrweg 2, Leiden, 2333CA, The Netherlands.
authors.forename: Helmut
authors.initials: H
authors.lastname: Schiessel
mesh_terms: D000818:Animals; D001483:Base Sequence; D042002:Chromatin Assembly and Disassembly; D003198:Computer Simulation; D004247:DNA / Q000378:metabolism*; D006801:Humans; D008390:Markov Chains; D051379:Mice; D008954:Models, Biological; D015233:Models, Statistical; D009707:Nucleosomes / Q000378:metabolism*; D017422:Sequence Analysis, DNA
chemical_list: D009707:Nucleosomes; D004247:DNA
keywords: Modeling; Nucleosome positioning; Sequence analysis