{"id":"https://openalex.org/W3099776199","doi":"https://doi.org/10.1145/3388440.3412471","title":"Variational Autoencoders for Protein Structure Prediction","display_name":"Variational Autoencoders for Protein Structure Prediction","publication_year":2020,"publication_date":"2020-09-21","ids":{"openalex":"https://openalex.org/W3099776199","doi":"https://doi.org/10.1145/3388440.3412471","mag":"3099776199"},"language":"en","primary_location":{"id":"doi:10.1145/3388440.3412471","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3388440.3412471","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5077702067","display_name":"Fardina Fathmiul Alam","orcid":"https://orcid.org/0000-0002-5660-6840"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Fardina Fathmiul Alam","raw_affiliation_strings":["Dept of Computer Science, George Mason University"],"affiliations":[{"raw_affiliation_string":"Dept of Computer Science, George Mason University","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044722808","display_name":"Amarda Shehu","orcid":"https://orcid.org/0000-0001-5230-4610"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amarda Shehu","raw_affiliation_strings":["Dept of Computer Science, George Mason University"],"affiliations":[{"raw_affiliation_string":"Dept of Computer Science, George Mason University","institution_ids":["https://openalex.org/I162714631"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5077702067"],"corresponding_institution_ids":["https://openalex.org/I162714631"],"apc_list":null,"apc_paid":null,"fwci":0.9114,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.73474578,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10044","display_name":"Protein Structure and Dynamics","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular 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/T10044","display_name":"Protein Structure and Dynamics","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular 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/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9800000190734863,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular 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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9707000255584717,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular 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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7199252247810364},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6107571125030518},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5551326274871826},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.532114565372467},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46819007396698},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4611765146255493},{"id":"https://openalex.org/keywords/protein-structure-prediction","display_name":"Protein structure prediction","score":0.45204785466194153},{"id":"https://openalex.org/keywords/protein-tertiary-structure","display_name":"Protein tertiary structure","score":0.4254492521286011},{"id":"https://openalex.org/keywords/protein-structure","display_name":"Protein structure","score":0.2897801995277405}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7199252247810364},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6107571125030518},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5551326274871826},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.532114565372467},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46819007396698},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4611765146255493},{"id":"https://openalex.org/C18051474","wikidata":"https://www.wikidata.org/wiki/Q899656","display_name":"Protein structure prediction","level":3,"score":0.45204785466194153},{"id":"https://openalex.org/C75599170","wikidata":"https://www.wikidata.org/wiki/Q898483","display_name":"Protein tertiary structure","level":2,"score":0.4254492521286011},{"id":"https://openalex.org/C47701112","wikidata":"https://www.wikidata.org/wiki/Q735188","display_name":"Protein structure","level":2,"score":0.2897801995277405},{"id":"https://openalex.org/C46141821","wikidata":"https://www.wikidata.org/wiki/Q209402","display_name":"Nuclear magnetic resonance","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3388440.3412471","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3388440.3412471","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1995808589","https://openalex.org/W2037589601","https://openalex.org/W2077743314","https://openalex.org/W2139257751","https://openalex.org/W2149197198","https://openalex.org/W2171559274","https://openalex.org/W2173591891","https://openalex.org/W2201713963","https://openalex.org/W2212660284","https://openalex.org/W2343931134","https://openalex.org/W2389430365","https://openalex.org/W2780845733","https://openalex.org/W2801109052","https://openalex.org/W2808950571","https://openalex.org/W2891185006","https://openalex.org/W2906084236","https://openalex.org/W2949867299","https://openalex.org/W2951621517","https://openalex.org/W2952771283","https://openalex.org/W3010446265","https://openalex.org/W3104488039","https://openalex.org/W6688325169"],"related_works":["https://openalex.org/W2221737924","https://openalex.org/W51493542","https://openalex.org/W1533579197","https://openalex.org/W4252453648","https://openalex.org/W2915333504","https://openalex.org/W2804736179","https://openalex.org/W2802527233","https://openalex.org/W4206825711","https://openalex.org/W3127664026","https://openalex.org/W2371908581"],"abstract_inverted_index":{"The":[0,119],"universe":[1],"of":[2,12,17,55],"protein":[3,23,70],"structures":[4,52,81],"contains":[5],"many":[6],"dark":[7],"regions":[8],"beyond":[9,89],"the":[10,18,30,115],"reach":[11],"experimental":[13],"techniques.":[14],"Yet,":[15],"knowledge":[16],"tertiary":[19,141],"structure(s)":[20],"that":[21,50,78,126],"a":[22],"employs":[24],"to":[25,34,76],"interact":[26],"with":[27,114,129],"partners":[28],"in":[29,46,112],"cell":[31],"is":[32,73],"critical":[33],"understanding":[35],"its":[36],"biological":[37],"function(s)":[38],"and":[39,96,124],"dysfunction(s).":[40],"Great":[41],"progress":[42],"has":[43],"been":[44],"made":[45],"silico":[47],"by":[48],"methods":[49],"generate":[51],"as":[53],"part":[54],"an":[56],"optimization.":[57],"Recently,":[58],"generative":[59],"models":[60,137],"based":[61],"on":[62],"neural":[63],"networks":[64],"are":[65,82,122,135],"being":[66],"debuted":[67],"for":[68,138],"generating":[69,139],"structures.":[71,142],"There":[72],"typically":[74],"limited":[75],"showing":[77],"some":[79],"generated":[80],"credible.":[83],"In":[84],"this":[85,90],"paper,":[86],"we":[87],"go":[88],"objective.":[91],"We":[92,105],"design":[93],"variational":[94,133],"autoencoders":[95,134],"evaluate":[97,106],"whether":[98],"they":[99],"can":[100],"replace":[101],"existing,":[102],"established":[103],"methods.":[104],"various":[107],"architectures":[108],"via":[109],"rigorous":[110],"metrics":[111],"comparison":[113],"popular":[116],"Rosetta":[117],"framework.":[118],"presented":[120],"results":[121],"promising":[123],"show":[125],"once":[127],"seeded":[128],"sufficient,":[130],"physically-realistic":[131],"structures,":[132],"efficient":[136],"realistic":[140]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}