{"id":"https://openalex.org/W4387346430","doi":"https://doi.org/10.1145/3584371.3613030","title":"Enhancing Cryo-EM Particle Picking Through Consistency Model-based Latent Space Denoiser","display_name":"Enhancing Cryo-EM Particle Picking Through Consistency Model-based Latent Space Denoiser","publication_year":2023,"publication_date":"2023-09-03","ids":{"openalex":"https://openalex.org/W4387346430","doi":"https://doi.org/10.1145/3584371.3613030"},"language":"en","primary_location":{"id":"doi:10.1145/3584371.3613030","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3584371.3613030","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3584371.3613030","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 14th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3584371.3613030","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5010016145","display_name":"Alif Bin Abdul Qayyum","orcid":"https://orcid.org/0009-0008-0706-2913"},"institutions":[{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Alif Bin Abdul Qayyum","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA"],"raw_orcid":"https://orcid.org/0009-0008-0706-2913","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA","institution_ids":["https://openalex.org/I91045830"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073946580","display_name":"Xiaoning Qian","orcid":"https://orcid.org/0000-0002-4347-2476"},"institutions":[{"id":"https://openalex.org/I200870766","display_name":"Brookhaven National Laboratory","ror":"https://ror.org/02ex6cf31","country_code":"US","type":"facility","lineage":["https://openalex.org/I1330989302","https://openalex.org/I200870766","https://openalex.org/I39565521","https://openalex.org/I4210142672"]},{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaoning Qian","raw_affiliation_strings":["Computational Science Initiative, Brookhaven National Laboratory, Upton, NY, USA","Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA","Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA Computational Science Initiative, Brookhaven National Laboratory, Upton, NY, USA"],"raw_orcid":"https://orcid.org/0000-0002-4347-2476","affiliations":[{"raw_affiliation_string":"Computational Science Initiative, Brookhaven National Laboratory, Upton, NY, USA","institution_ids":["https://openalex.org/I200870766"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA","institution_ids":["https://openalex.org/I91045830"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA Computational Science Initiative, Brookhaven National Laboratory, Upton, NY, USA","institution_ids":["https://openalex.org/I200870766","https://openalex.org/I91045830"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081620315","display_name":"Byung-Jun Yoon","orcid":"https://orcid.org/0000-0001-9328-1101"},"institutions":[{"id":"https://openalex.org/I200870766","display_name":"Brookhaven National Laboratory","ror":"https://ror.org/02ex6cf31","country_code":"US","type":"facility","lineage":["https://openalex.org/I1330989302","https://openalex.org/I200870766","https://openalex.org/I39565521","https://openalex.org/I4210142672"]},{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Byung-Jun Yoon","raw_affiliation_strings":["Computational Science Initiative, Brookhaven National Laboratory, Upton, NY, USA","Department of Electrical & Computer Engineering, Texas A&M University, College Station, TX, USA","Department of Electrical & Computer Engineering, Texas A&M University, College Station, TX, USA Computational Science Initiative, Brookhaven National Laboratory, Upton, NY, USA"],"raw_orcid":"https://orcid.org/0000-0001-9328-1101","affiliations":[{"raw_affiliation_string":"Computational Science Initiative, Brookhaven National Laboratory, Upton, NY, USA","institution_ids":["https://openalex.org/I200870766"]},{"raw_affiliation_string":"Department of Electrical & Computer Engineering, Texas A&M University, College Station, TX, USA","institution_ids":["https://openalex.org/I91045830"]},{"raw_affiliation_string":"Department of Electrical & Computer Engineering, Texas A&M University, College Station, TX, USA Computational Science Initiative, Brookhaven National Laboratory, Upton, NY, USA","institution_ids":["https://openalex.org/I200870766","https://openalex.org/I91045830"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5010016145"],"corresponding_institution_ids":["https://openalex.org/I91045830"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12261146,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10857","display_name":"Advanced Electron Microscopy Techniques and Applications","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1315","display_name":"Structural Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10857","display_name":"Advanced Electron Microscopy Techniques and Applications","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1315","display_name":"Structural Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12039","display_name":"Electron and X-Ray Spectroscopy Techniques","score":0.9902999997138977,"subfield":{"id":"https://openalex.org/subfields/2508","display_name":"Surfaces, Coatings and Films"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13114","display_name":"Image Processing Techniques and Applications","score":0.9825000166893005,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.8308113813400269},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6059151887893677},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.5852120518684387},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5835719108581543},{"id":"https://openalex.org/keywords/cryo-electron-microscopy","display_name":"Cryo-electron microscopy","score":0.5574119687080383},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5465121865272522},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.4772346317768097},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4344029426574707},{"id":"https://openalex.org/keywords/particle","display_name":"Particle (ecology)","score":0.4115503132343292},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3784797489643097},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.33012503385543823},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.18307945132255554}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8308113813400269},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6059151887893677},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5852120518684387},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5835719108581543},{"id":"https://openalex.org/C20702342","wikidata":"https://www.wikidata.org/wiki/Q5190506","display_name":"Cryo-electron microscopy","level":2,"score":0.5574119687080383},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5465121865272522},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.4772346317768097},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4344029426574707},{"id":"https://openalex.org/C2778517922","wikidata":"https://www.wikidata.org/wiki/Q7140482","display_name":"Particle (ecology)","level":2,"score":0.4115503132343292},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3784797489643097},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.33012503385543823},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.18307945132255554},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C46141821","wikidata":"https://www.wikidata.org/wiki/Q209402","display_name":"Nuclear magnetic resonance","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3584371.3613030","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3584371.3613030","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3584371.3613030","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 14th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3584371.3613030","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3584371.3613030","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3584371.3613030","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 14th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6357584807","display_name":null,"funder_award_id":"SC0012704","funder_id":"https://openalex.org/F4320306084","funder_display_name":"U.S. Department of Energy"},{"id":"https://openalex.org/G7642226822","display_name":null,"funder_award_id":"DE-SC0012704","funder_id":"https://openalex.org/F4320306084","funder_display_name":"U.S. Department of Energy"}],"funders":[{"id":"https://openalex.org/F4320306084","display_name":"U.S. Department of Energy","ror":"https://ror.org/01bj3aw27"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4387346430.pdf","grobid_xml":"https://content.openalex.org/works/W4387346430.grobid-xml"},"referenced_works_count":1,"referenced_works":["https://openalex.org/W3204128622"],"related_works":["https://openalex.org/W4321789545","https://openalex.org/W4365211920","https://openalex.org/W3014948380","https://openalex.org/W4309969736","https://openalex.org/W4394785709","https://openalex.org/W4380551139","https://openalex.org/W4317695495","https://openalex.org/W2770818364","https://openalex.org/W2953501176","https://openalex.org/W2965095304"],"abstract_inverted_index":{"Particle":[0],"picking,":[1],"which":[2],"aims":[3],"to":[4,20,75],"select":[5],"randomly":[6],"oriented":[7],"macro-molecular":[8],"particles":[9],"in":[10,44],"cryo-electron":[11],"microscopy":[12],"(cryo-EM)":[13],"images,":[14],"is":[15],"the":[16],"first":[17],"critical":[18],"step":[19],"ensuring":[21],"accurate":[22],"reconstruction":[23],"of":[24,56],"highresolution":[25],"three-dimensional":[26],"molecular":[27],"structures":[28],"from":[29],"noisy":[30],"cryo-EM":[31,45,77],"images.":[32],"To":[33],"date,":[34],"various":[35],"deep-learning":[36],"techniques":[37],"have":[38],"been":[39],"introduced":[40],"for":[41],"particle":[42,78],"picking":[43,79],"with":[46,69],"promising":[47],"results.":[48],"In":[49],"this":[50],"work,":[51],"we":[52],"propose":[53],"a":[54,70],"combination":[55],"two":[57],"generative":[58],"models,":[59],"spatial":[60],"variational":[61],"autoencoder":[62],"and":[63],"latent":[64,71],"space":[65,72],"consistency":[66],"model,":[67],"together":[68],"classifier":[73],"model":[74],"facilitate":[76],"by":[80],"removing":[81],"false":[82],"positive":[83],"picked":[84],"particles.":[85]},"counts_by_year":[],"updated_date":"2026-04-24T08:23:43.765630","created_date":"2025-10-10T00:00:00"}