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DEER data analysis software : a comparative guide

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dc.contributor.authorRussell, Hannah
dc.contributor.authorCura, Robyn
dc.contributor.authorLovett, Janet E.
dc.date.accessioned2022-06-01T08:30:08Z
dc.date.available2022-06-01T08:30:08Z
dc.date.issued2022-06-01
dc.identifier279545989
dc.identifierfb028d2f-b1c8-4685-abce-272f118f329e
dc.identifier85132844151
dc.identifier000811893200001
dc.identifier.citationRussell , H , Cura , R & Lovett , J E 2022 , ' DEER data analysis software : a comparative guide ' , Frontiers in Molecular Biosciences , vol. 9 , 915167 . https://doi.org/10.3389/fmolb.2022.915167en
dc.identifier.issn2296-889X
dc.identifier.otherORCID: /0000-0002-3561-450X/work/114023321
dc.identifier.urihttps://hdl.handle.net/10023/25475
dc.descriptionWe acknowledge financial support from EPSRC (studentship to HR EP/R513337/1 and The Royal Society (URF to JEL UR150698F). The UKRI block grant to St Andrews supported the journal charges for open access.en
dc.description.abstractPulsed Dipolar Spectroscopy (PDS) Electron Paramagnetic Resonance (EPR) experiments are popular techniques to measure dipolar coupling and therefore nanometre-scale distances and distance distributions between paramagnetic centres. The most common experiment is Double Electron Electron Resonance (DEER, also known as PELDOR), which is a well-tested and documented experiment. Until recently there were few methods to analyze data, however this has changed of late. The current plethora of DEER analysis packages may appear overwhelming to a new practitioner of DEER. In this work, six of the most popular packages are reviewed. This includes a brief guide for getting started with the environments, and qualitative testing and comparison of each using both simulated and experimental DEER data.
dc.format.extent17
dc.format.extent3697611
dc.language.isoeng
dc.relation.ispartofFrontiers in Molecular Biosciencesen
dc.subjectEPR/ESRen
dc.subjectDEER/PELDORen
dc.subjectPulsed dipolar spectroscopyen
dc.subjectDeerAnalysisen
dc.subjectDEERneten
dc.subjectTikhonov regularizationen
dc.subjectNeural networksen
dc.subjectGaussian modelsen
dc.subjectQA76 Computer softwareen
dc.subjectQC Physicsen
dc.subjectDASen
dc.subject.lccQA76en
dc.subject.lccQCen
dc.titleDEER data analysis software : a comparative guideen
dc.typeJournal articleen
dc.contributor.sponsorThe Royal Societyen
dc.contributor.institutionUniversity of St Andrews. School of Physics and Astronomyen
dc.contributor.institutionUniversity of St Andrews. Biomedical Sciences Research Complexen
dc.identifier.doi10.3389/fmolb.2022.915167
dc.description.statusPeer revieweden
dc.identifier.urlhttps://www.frontiersin.org/articles/10.3389/fmolb.2022.915167/abstracten
dc.identifier.grantnumberUF150698en


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