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dc.contributor.authorPintilie, Grigore D.
dc.contributor.authorZhang, Junjie
dc.contributor.authorGoddard, Thomas D.
dc.contributor.authorChiu, Wah
dc.contributor.authorGossard, David C.
dc.date.accessioned2015-10-13T17:26:07Z
dc.date.available2015-10-13T17:26:07Z
dc.date.issued2010-03
dc.date.submitted2010-03
dc.identifier.issn10478477
dc.identifier.issn1095-8657
dc.identifier.urihttp://hdl.handle.net/1721.1/99224
dc.description.abstractCryo-electron microscopy produces 3D density maps of molecular machines, which consist of various molecular components such as proteins and RNA. Segmentation of individual components in such maps is a challenging task, and is mostly accomplished interactively. We present an approach based on the immersive watershed method and grouping of the resulting regions using progressively smoothed maps. The method requires only three parameters: the segmentation threshold, a smoothing step size, and the number of smoothing steps. We first apply the method to maps generated from molecular structures and use a quantitative metric to measure the segmentation accuracy. The method does not attain perfect accuracy, however it produces single or small groups of regions that roughly match individual proteins or subunits. We also present two methods for fitting of structures into density maps, based on aligning the structures with single regions or small groups of regions. The first method aligns centers and principal axes, whereas the second aligns centers and then rotates the structure to find the best fit. We describe both interactive and automated ways of using these two methods. Finally, we show segmentation and fitting results for several experimentally-obtained density maps.en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Grant PN2EY016525)en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Grant R01GM079429)en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Grant P41RR02250)en_US
dc.description.sponsorshipNational Science Foundation (U.S.) (IIS-0705644)en_US
dc.language.isoen_US
dc.publisherElsevieren_US
dc.relation.isversionofhttp://dx.doi.org/10.1016/j.jsb.2010.03.007en_US
dc.rightsCreative Commons Attribution-Noncommercial-NoDerivativesen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.sourcePMCen_US
dc.titleQuantitative analysis of cryo-EM density map segmentation by watershed and scale-space filtering, and fitting of structures by alignment to regionsen_US
dc.typeArticleen_US
dc.identifier.citationPintilie, Grigore D., Junjie Zhang, Thomas D. Goddard, Wah Chiu, and David C. Gossard. “Quantitative Analysis of Cryo-EM Density Map Segmentation by Watershed and Scale-Space Filtering, and Fitting of Structures by Alignment to Regions.” Journal of Structural Biology 170, no. 3 (June 2010): 427–438.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineeringen_US
dc.contributor.mitauthorPintilie, Grigore D.en_US
dc.contributor.mitauthorGossard, David C.en_US
dc.relation.journalJournal of Structural Biologyen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsPintilie, Grigore D.; Zhang, Junjie; Goddard, Thomas D.; Chiu, Wah; Gossard, David C.en_US
dc.identifier.orcidhttps://orcid.org/0000-0001-7706-6954
mit.licensePUBLISHER_CCen_US
mit.metadata.statusComplete


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