{"id":{"repo_id":"cambridge","oai_identifier":"oai:www.repository.cam.ac.uk:1810/284086"},"canonical_url":"https://search.dev.ndltd.org/etd/cambridge/oai:www.repository.cam.ac.uk:1810/284086","repository":{"repo_id":"cambridge","name":"Cambridge University","base_url":"https://api.repository.cam.ac.uk/server/oai/request"},"display":{"title":"Helical Reconstruction in RELION","abstract":"Helical assemblies of proteins are ubiquitous in nature and they perform vital functions in a wide range of organisms. The recent development of direct electron detectors and other imaging techniques in cryo-electron microscopy (cryo-EM) has opened new possibilities in solving helical structures at atomic resolution. Existing software packages for helical processing often require experience in tuning many ad hoc parameters to achieve optimal reconstruction results. REgularised LIkelihood OptimisatioN (RELION), an open-source single-particle analysis package, reduces the need for user expertise by the formulation of an empirical Bayesian framework, and has yielded some of the highest resolution density maps in recent years. Prior information about the helical assemblies can be conveniently incorporated into the statistical framework of RELION and thereby improves the helical reconstructions. This PhD thesis describes the development of a helical processing computation workflow with reduced user intervention in RELION. Chapter 1 introduces the theoretical basis of cryo-EM data acquisition and single-particle data processing, the concepts of helical symmetry, and a previously described method for iterative real-space reconstruction of helical assemblies, to which the RELION implementation bears resemblance. Chapter 2 discusses multiple adaptations to RELION that are necessary for helical processing. Key elements include the imposition and local refinement of helical symmetry, masks on helical segments and references, expressions of angular and translational prior information, manual and automated segment picking as well as initial model generation for helices. Calculations have been performed on four test data sets showing that the developed methods in RELION yield results that are as good as or better than alternative approaches for the tests performed. Chapter 3 describes the same methodology adapted to helical sub-tomogram averaging in RELION. Chapter 4 introduces the local symmetry option developed for special types of filaments with pseudo-helical symmetry. The concept can be extended to general single-particle analysis as well. Chapter 5 describes four helical structures determined in collaboration with other research groups using helical RELION for data processing. Chapter 6 concludes the thesis with a brief summary and future prospects.","abstract_html":"Helical assemblies of proteins are ubiquitous in nature and they perform vital functions in a wide range of organisms. The recent development of direct electron detectors and other imaging techniques in cryo-electron microscopy (cryo-EM) has opened new possibilities in solving helical structures at atomic resolution. Existing software packages for helical processing often require experience in tuning many ad hoc parameters to achieve optimal reconstruction results. REgularised LIkelihood OptimisatioN (RELION), an open-source single-particle analysis package, reduces the need for user expertise by the formulation of an empirical Bayesian framework, and has yielded some of the highest resolution density maps in recent years. Prior information about the helical assemblies can be conveniently incorporated into the statistical framework of RELION and thereby improves the helical reconstructions. This PhD thesis describes the development of a helical processing computation workflow with reduced user intervention in RELION. Chapter 1 introduces the theoretical basis of cryo-EM data acquisition and single-particle data processing, the concepts of helical symmetry, and a previously described method for iterative real-space reconstruction of helical assemblies, to which the RELION implementation bears resemblance. Chapter 2 discusses multiple adaptations to RELION that are necessary for helical processing. Key elements include the imposition and local refinement of helical symmetry, masks on helical segments and references, expressions of angular and translational prior information, manual and automated segment picking as well as initial model generation for helices. Calculations have been performed on four test data sets showing that the developed methods in RELION yield results that are as good as or better than alternative approaches for the tests performed. Chapter 3 describes the same methodology adapted to helical sub-tomogram averaging in RELION. Chapter 4 introduces the local symmetry option developed for special types of filaments with pseudo-helical symmetry. The concept can be extended to general single-particle analysis as well. Chapter 5 describes four helical structures determined in collaboration with other research groups using helical RELION for data processing. Chapter 6 concludes the thesis with a brief summary and future prospects.","abstract_has_math":false,"creators":["He, Shaoda"],"institution":"University of Cambridge","degree_name":"Doctor of Philosophy (PhD)","degree_level":"Doctoral","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Scheres, Sjors"],"committee_chairs":[],"committee_members":[],"year":2018,"date_issued":"2018-11-24","date_published":"2018-11-24","updated_at":"2026-07-22T22:24:03Z","subjects":["cryo-EM","Helical Reconstruction","Structural Biology","RELION"],"languages":["en"],"rights":[],"rights_urls":["https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/f1eec70e-345c-4622-b5e4-44ca6a657cea/download","https://www.rioxx.net/licenses/all-rights-reserved/"],"identifier_entries":[]},"links":{"outbound_url":"https://doi.org/10.17863/CAM.31456","outbound_label":"DOI","outbound_source":"dc:identifier.doi"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Scheres, Sjors"]},{"key":"dc:contributor.sponsor","label":"Sponsor","values":["Cambridge Trust - LMB Scholarship"]},{"key":"dc:creator","label":"Author","values":["He, Shaoda"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.issued","label":"Date","values":["2018-11-24"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Cambridge"]},{"key":"dc:relation.isreferencedby.uri","label":"Dc Relation Isreferencedby URI","values":["https://www.repository.cam.ac.uk/handle/1810/284086"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Doctoral"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["Doctor of Philosophy (PhD)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["cryo-EM","Helical Reconstruction","Structural Biology","RELION"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/f1eec70e-345c-4622-b5e4-44ca6a657cea/download","https://www.rioxx.net/licenses/all-rights-reserved/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.doi","label":"DOI","values":["10.17863/CAM.31456"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/5061dabd-0c7c-44e1-a378-014c639405f3/download"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Helical assemblies of proteins are ubiquitous in nature and they perform vital functions in a wide range of organisms. 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Chapter 1 introduces the theoretical basis of cryo-EM data acquisition and single-particle data processing, the concepts of helical symmetry, and a previously described method for iterative real-space reconstruction of helical assemblies, to which the RELION implementation bears resemblance. Chapter 2 discusses multiple adaptations to RELION that are necessary for helical processing. Key elements include the imposition and local refinement of helical symmetry, masks on helical segments and references, expressions of angular and translational prior information, manual and automated segment picking as well as initial model generation for helices. Calculations have been performed on four test data sets showing that the developed methods in RELION yield results that are as good as or better than alternative approaches for the tests performed. Chapter 3 describes the same methodology adapted to helical sub-tomogram averaging in RELION. Chapter 4 introduces the local symmetry option developed for special types of filaments with pseudo-helical symmetry. The concept can be extended to general single-particle analysis as well. Chapter 5 describes four helical structures determined in collaboration with other research groups using helical RELION for data processing. Chapter 6 concludes the thesis with a brief summary and future prospects."]},{"key":"dc:format.checksum.md5","label":"Dc Format Checksum Md5","values":["fb4b628383a49e892148a6b983d87852","87eda9de84448d1f82354d60eee3eb5f"]},{"key":"dc:title","label":"Title","values":["Helical Reconstruction in RELION"]}]}],"canonical_facts":{"dc:contributor.advisor":["Scheres, Sjors"],"dc:contributor.sponsor":["Cambridge Trust - LMB Scholarship"],"dc:creator":["He, Shaoda"],"dc:date.issued":["2018-11-24"],"dc:description.abstract":["Helical assemblies of proteins are ubiquitous in nature and they perform vital functions in a wide range of organisms. The recent development of direct electron detectors and other imaging techniques in cryo-electron microscopy (cryo-EM) has opened new possibilities in solving helical structures at atomic resolution. Existing software packages for helical processing often require experience in tuning many ad hoc parameters to achieve optimal reconstruction results. REgularised LIkelihood OptimisatioN (RELION), an open-source single-particle analysis package, reduces the need for user expertise by the formulation of an empirical Bayesian framework, and has yielded some of the highest resolution density maps in recent years. Prior information about the helical assemblies can be conveniently incorporated into the statistical framework of RELION and thereby improves the helical reconstructions. This PhD thesis describes the development of a helical processing computation workflow with reduced user intervention in RELION. Chapter 1 introduces the theoretical basis of cryo-EM data acquisition and single-particle data processing, the concepts of helical symmetry, and a previously described method for iterative real-space reconstruction of helical assemblies, to which the RELION implementation bears resemblance. Chapter 2 discusses multiple adaptations to RELION that are necessary for helical processing. Key elements include the imposition and local refinement of helical symmetry, masks on helical segments and references, expressions of angular and translational prior information, manual and automated segment picking as well as initial model generation for helices. Calculations have been performed on four test data sets showing that the developed methods in RELION yield results that are as good as or better than alternative approaches for the tests performed. Chapter 3 describes the same methodology adapted to helical sub-tomogram averaging in RELION. Chapter 4 introduces the local symmetry option developed for special types of filaments with pseudo-helical symmetry. The concept can be extended to general single-particle analysis as well. Chapter 5 describes four helical structures determined in collaboration with other research groups using helical RELION for data processing. Chapter 6 concludes the thesis with a brief summary and future prospects."],"dc:format.checksum.md5":["fb4b628383a49e892148a6b983d87852","87eda9de84448d1f82354d60eee3eb5f"],"dc:identifier.doi":["10.17863/CAM.31456"],"dc:identifier.uri":["https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/5061dabd-0c7c-44e1-a378-014c639405f3/download"],"dc:language":["en"],"dc:publisher.institution":["University of Cambridge"],"dc:relation.isreferencedby.uri":["https://www.repository.cam.ac.uk/handle/1810/284086"],"dc:rights":["https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/f1eec70e-345c-4622-b5e4-44ca6a657cea/download","https://www.rioxx.net/licenses/all-rights-reserved/"],"dc:subject":["cryo-EM","Helical Reconstruction","Structural Biology","RELION"],"dc:title":["Helical Reconstruction in RELION"],"dc:type":["Thesis"],"dc:type.qualificationlevel":["Doctoral"],"dc:type.qualificationname":["Doctor of Philosophy (PhD)"]},"updated_at":"2026-07-22T22:24:03Z"}