Error-based Extraction of States and Energy Landscapes from Experimental Single-Molecule Time-Series

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dc.citation.journalTitleScientific Reportsen_US
dc.citation.volumeNumber5en_US
dc.contributor.authorTaylor, J. Nicholasen_US
dc.contributor.authorLi, Chun-Biuen_US
dc.contributor.authorCooper, David R.en_US
dc.contributor.authorLandes, Christy F.en_US
dc.contributor.authorKomatsuzaki, Tamikien_US
dc.date.accessioned2016-03-28T20:49:40Zen_US
dc.date.available2016-03-28T20:49:40Zen_US
dc.date.issued2015en_US
dc.description.abstractCharacterization of states, the essential components of the underlying energy landscapes, is one of the most intriguing subjects in single-molecule (SM) experiments due to the existence of noise inherent to the measurements. Here we present a method to extract the underlying state sequences from experimental SM time-series. Taking into account empirical error and the finite sampling of the time-series, the method extracts a steady-state network which provides an approximation of the underlying effective free energy landscape. The core of the method is the application of rate-distortion theory from information theory, allowing the individual data points to be assigned to multiple states simultaneously. We demonstrate the method's proficiency in its application to simulated trajectories as well as to experimental SM fluorescence resonance energy transfer (FRET) trajectories obtained from isolated agonist binding domains of the AMPA receptor, an ionotropic glutamate receptor that is prevalent in the central nervous system.en_US
dc.identifier.citationTaylor, J. Nicholas, Li, Chun-Biu, Cooper, David R., et al.. "Error-based Extraction of States and Energy Landscapes from Experimental Single-Molecule Time-Series." <i>Scientific Reports,</i> 5, (2015) Macmillan Publishers Limited: http://dx.doi.org/10.1038/srep09174.en_US
dc.identifier.doihttp://dx.doi.org/10.1038/srep09174en_US
dc.identifier.urihttps://hdl.handle.net/1911/88658en_US
dc.language.isoengen_US
dc.publisherMacmillan Publishers Limiteden_US
dc.rightsThis work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder in order to reproduce the material.en_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.titleError-based Extraction of States and Energy Landscapes from Experimental Single-Molecule Time-Seriesen_US
dc.typeJournal articleen_US
dc.type.dcmiTexten_US
dc.type.publicationpublisher versionen_US
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