{"id":"https://openalex.org/W3202141932","doi":"https://doi.org/10.1021/acs.jcim.1c01021","title":"RealVS: Toward Enhancing the Precision of Top Hits in Ligand-Based Virtual Screening of Drug Leads from Large Compound Databases","display_name":"RealVS: Toward Enhancing the Precision of Top Hits in Ligand-Based Virtual Screening of Drug Leads from Large Compound Databases","publication_year":2021,"publication_date":"2021-10-07","ids":{"openalex":"https://openalex.org/W3202141932","doi":"https://doi.org/10.1021/acs.jcim.1c01021","mag":"3202141932","pmid":"https://pubmed.ncbi.nlm.nih.gov/34619030"},"language":"en","primary_location":{"id":"doi:10.1021/acs.jcim.1c01021","is_oa":false,"landing_page_url":"https://doi.org/10.1021/acs.jcim.1c01021","pdf_url":null,"source":{"id":"https://openalex.org/S167262187","display_name":"Journal of Chemical Information and Modeling","issn_l":"1549-9596","issn":["1549-9596","1549-960X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320006","host_organization_name":"American Chemical Society","host_organization_lineage":["https://openalex.org/P4310320006"],"host_organization_lineage_names":["American Chemical Society"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Chemical Information and Modeling","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5026015013","display_name":"Yueming Yin","orcid":"https://orcid.org/0000-0002-9060-3248"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yueming Yin","raw_affiliation_strings":["College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101788068","display_name":"Haifeng Hu","orcid":"https://orcid.org/0000-0002-6585-3106"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Haifeng Hu","raw_affiliation_strings":["College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China"],"raw_orcid":"https://orcid.org/0000-0002-6585-3106","affiliations":[{"raw_affiliation_string":"College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031803321","display_name":"Zhen Yang","orcid":"https://orcid.org/0000-0002-0785-9382"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Yang","raw_affiliation_strings":["National Engineering Research Center of Communications and Networking, Nanjing University of Posts and Telecommunications, Nanjing 210003, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Engineering Research Center of Communications and Networking, Nanjing University of Posts and Telecommunications, Nanjing 210003, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112689618","display_name":"Huajian Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huajian Xu","raw_affiliation_strings":["College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102847901","display_name":"Jiansheng Wu","orcid":"https://orcid.org/0000-0002-7941-9722"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiansheng Wu","raw_affiliation_strings":["School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing 210003, China"],"raw_orcid":"https://orcid.org/0000-0002-7941-9722","affiliations":[{"raw_affiliation_string":"School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing 210003, China","institution_ids":["https://openalex.org/I41198531"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5101788068","https://openalex.org/A5102847901"],"corresponding_institution_ids":["https://openalex.org/I41198531"],"apc_list":null,"apc_paid":null,"fwci":1.0549,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.80130431,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"61","issue":"10","first_page":"4924","last_page":"4939"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.9868000149726868,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"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/T10044","display_name":"Protein Structure and Dynamics","score":0.9279000163078308,"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/virtual-screening","display_name":"Virtual screening","score":0.858843207359314},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.6931707859039307},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6410011053085327},{"id":"https://openalex.org/keywords/cheminformatics","display_name":"Cheminformatics","score":0.6193363666534424},{"id":"https://openalex.org/keywords/applicability-domain","display_name":"Applicability domain","score":0.5328933000564575},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5036689639091492},{"id":"https://openalex.org/keywords/chemical-database","display_name":"Chemical database","score":0.4877334535121918},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.47360682487487793},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4733674228191376},{"id":"https://openalex.org/keywords/drug-discovery","display_name":"Drug discovery","score":0.46362045407295227},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4614464342594147},{"id":"https://openalex.org/keywords/quantitative-structure\u2013activity-relationship","display_name":"Quantitative structure\u2013activity relationship","score":0.3925448954105377},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3805444538593292},{"id":"https://openalex.org/keywords/bioinformatics","display_name":"Bioinformatics","score":0.20377233624458313},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.08659788966178894}],"concepts":[{"id":"https://openalex.org/C103697762","wikidata":"https://www.wikidata.org/wiki/Q4112105","display_name":"Virtual screening","level":3,"score":0.858843207359314},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.6931707859039307},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6410011053085327},{"id":"https://openalex.org/C68762167","wikidata":"https://www.wikidata.org/wiki/Q910164","display_name":"Cheminformatics","level":2,"score":0.6193363666534424},{"id":"https://openalex.org/C107908354","wikidata":"https://www.wikidata.org/wiki/Q4781456","display_name":"Applicability domain","level":3,"score":0.5328933000564575},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5036689639091492},{"id":"https://openalex.org/C203394866","wikidata":"https://www.wikidata.org/wiki/Q2881060","display_name":"Chemical database","level":2,"score":0.4877334535121918},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.47360682487487793},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4733674228191376},{"id":"https://openalex.org/C74187038","wikidata":"https://www.wikidata.org/wiki/Q1418791","display_name":"Drug discovery","level":2,"score":0.46362045407295227},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4614464342594147},{"id":"https://openalex.org/C164126121","wikidata":"https://www.wikidata.org/wiki/Q766383","display_name":"Quantitative structure\u2013activity relationship","level":2,"score":0.3925448954105377},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3805444538593292},{"id":"https://openalex.org/C60644358","wikidata":"https://www.wikidata.org/wiki/Q128570","display_name":"Bioinformatics","level":1,"score":0.20377233624458313},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.08659788966178894},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D004364","descriptor_name":"Pharmaceutical Preparations","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D004364","descriptor_name":"Pharmaceutical Preparations","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D004364","descriptor_name":"Pharmaceutical Preparations","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D008024","descriptor_name":"Ligands","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008024","descriptor_name":"Ligands","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008024","descriptor_name":"Ligands","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016208","descriptor_name":"Databases, Factual","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D055808","descriptor_name":"Drug Discovery","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D055808","descriptor_name":"Drug Discovery","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D055808","descriptor_name":"Drug Discovery","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1021/acs.jcim.1c01021","is_oa":false,"landing_page_url":"https://doi.org/10.1021/acs.jcim.1c01021","pdf_url":null,"source":{"id":"https://openalex.org/S167262187","display_name":"Journal of Chemical Information and Modeling","issn_l":"1549-9596","issn":["1549-9596","1549-960X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320006","host_organization_name":"American Chemical Society","host_organization_lineage":["https://openalex.org/P4310320006"],"host_organization_lineage_names":["American Chemical Society"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Chemical Information and Modeling","raw_type":"journal-article"},{"id":"pmid:34619030","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34619030","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of chemical information and modeling","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4300000071525574,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[{"id":"https://openalex.org/G1329238477","display_name":null,"funder_award_id":"61901229","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2535026932","display_name":"\u8bed\u97f3\u7684\u56fe\u4fe1\u53f7\u5904\u7406\u7406\u8bba\u4e0e\u6280\u672f\u7814\u7a76","funder_award_id":"62071242","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G274090707","display_name":null,"funder_award_id":"BK20201378","funder_id":"https://openalex.org/F4320325437","funder_display_name":"Jiangsu Science and Technology Department"},{"id":"https://openalex.org/G4630907718","display_name":null,"funder_award_id":"KYCX20_0738","funder_id":"https://openalex.org/F4320321605","funder_display_name":"Government of Jiangsu Province"},{"id":"https://openalex.org/G4947787081","display_name":"\u6837\u672c\u4fe1\u606f\u4e0d\u5145\u5206\u4e0b\u9776\u5411\u672a\u77e5\u7ed3\u6784GPCRs\u7684\u914d\u4f53\u865a\u62df\u7b5b\u9009\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61872198","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5664010555","display_name":null,"funder_award_id":"61571233","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6003542791","display_name":"\u57fa\u4e8e\u9002\u914d\u4f53\u4f20\u611f\u6570\u5b57PCR\u7684\u5355\u80de\u5916\u56ca\u6ce1\u68c0\u6d4b\u53ca\u80ba\u764c\u5173\u8054\u6027\u7814\u7a76","funder_award_id":"61971216","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321605","display_name":"Government of Jiangsu Province","ror":"https://ror.org/004svx814"},{"id":"https://openalex.org/F4320325437","display_name":"Jiangsu Science and Technology Department","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W74826915","https://openalex.org/W1498436455","https://openalex.org/W1578268327","https://openalex.org/W1731081199","https://openalex.org/W1986595033","https://openalex.org/W1987966112","https://openalex.org/W1990451437","https://openalex.org/W1999798000","https://openalex.org/W2025135899","https://openalex.org/W2029682253","https://openalex.org/W2033882981","https://openalex.org/W2042795504","https://openalex.org/W2062108517","https://openalex.org/W2078142106","https://openalex.org/W2085492035","https://openalex.org/W2087253837","https://openalex.org/W2100257305","https://openalex.org/W2121776789","https://openalex.org/W2126275775","https://openalex.org/W2154662590","https://openalex.org/W2161062388","https://openalex.org/W2168480393","https://openalex.org/W2187089797","https://openalex.org/W2213612645","https://openalex.org/W2271679886","https://openalex.org/W2290847742","https://openalex.org/W2434801324","https://openalex.org/W2471437780","https://openalex.org/W2473238561","https://openalex.org/W2580783751","https://openalex.org/W2593768305","https://openalex.org/W2606217927","https://openalex.org/W2606981059","https://openalex.org/W2751756351","https://openalex.org/W2790322107","https://openalex.org/W2894566366","https://openalex.org/W2902812092","https://openalex.org/W2902820054","https://openalex.org/W2907597838","https://openalex.org/W2911658570","https://openalex.org/W2937994991","https://openalex.org/W2955252073","https://openalex.org/W2956586889","https://openalex.org/W2963833291","https://openalex.org/W2968734407","https://openalex.org/W3005741613","https://openalex.org/W3012107310","https://openalex.org/W3087143908","https://openalex.org/W3096831136","https://openalex.org/W3100157108","https://openalex.org/W3122066254","https://openalex.org/W3124409690","https://openalex.org/W3134386172","https://openalex.org/W4405318654"],"related_works":["https://openalex.org/W2746158299","https://openalex.org/W1969085205","https://openalex.org/W1977382278","https://openalex.org/W4362464865","https://openalex.org/W2098840560","https://openalex.org/W4302604134","https://openalex.org/W1970841929","https://openalex.org/W2768880727","https://openalex.org/W2113146994","https://openalex.org/W2793396277"],"abstract_inverted_index":{"Accurate":[0],"modeling":[1],"of":[2,11,45,48,56,70,102,122,140,143,216,229,240,249,258,271],"compound":[3,98,245,275],"bioactivities":[4,29,69,205],"is":[5,59,248,260,277],"essential":[6],"for":[7,40,65,118,156,198,206,265],"the":[8,22,46,49,68,87,105,113,120,138,146,153,171,227],"virtual":[9,54,238,269],"screening":[10,55,154,239,270],"drug":[12,41,57,127,241],"leads.":[13],"In":[14],"real-world":[15,253],"scenarios,":[16],"pharmacists":[17],"tend":[18,183],"to":[19,36,84,136,168,184],"choose":[20],"from":[21,30,73,112,145,152,243,273],"top-k":[23],"hit":[24],"compounds":[25,72,144],"ranked":[26],"by":[27],"predicted":[28],"a":[31,74,80,213],"large":[32,75,214,244,274],"database":[33,155],"with":[34,97,126,203],"interest":[35],"continue":[37],"wet":[38],"experiments":[39],"discovery.":[42],"Significant":[43],"improvement":[44],"precision":[47,90,228],"top":[50,88,230],"hits":[51,231,272],"in":[52,236,252],"ligand-based":[53,237],"leads":[58,242],"more":[60],"valuable":[61],"than":[62],"conventional":[63],"schemes":[64],"accurately":[66],"predicting":[67],"all":[71],"database.":[76],"Here,":[77],"we":[78],"proposed":[79,167],"new":[81],"method,":[82],"RealVS,":[83],"significantly":[85,225],"improve":[86],"hits\u2019":[89],"and":[91,150,176],"learn":[92],"interpretable":[93],"key":[94,200],"substructures":[95,201],"associated":[96,125,202],"bioactivities.":[99],"The":[100,130,210,255],"features":[101,142],"RealVS":[103,259],"involve":[104],"following":[106],"points.":[107],"(1)":[108],"Abundant":[109],"transferable":[110],"information":[111],"source":[114],"domain":[115,132],"was":[116,134,166],"introduced":[117],"alleviating":[119],"insufficiency":[121],"inactive":[123,181],"ligands":[124,182],"targets.":[128],"(2)":[129],"adversarial":[131,177],"alignment":[133],"adopted":[135,197],"fit":[137],"distribution":[139],"generated":[141],"training":[147],"data":[148,218],"set":[149],"that":[151,221],"greater":[157],"model":[158,208],"generalization":[159],"ability.":[160],"(3)":[161],"A":[162],"novel":[163],"objective":[164],"function":[165],"simultaneously":[169],"optimize":[170],"classification":[172],"loss,":[173,175,178],"regression":[174,190],"where":[179,268],"most":[180],"be":[185],"screened":[186],"out":[187],"before":[188],"activity":[189],"prediction.":[191],"(4)":[192],"Graph":[193],"attention":[194],"networks":[195],"were":[196],"learning":[199],"ligand":[204],"better":[207],"interpretability.":[209],"results":[211],"on":[212],"number":[215],"benchmark":[217],"sets":[219],"show":[220],"our":[222],"method":[223],"has":[224],"improved":[226],"under":[232],"various":[233],"k":[234],"values":[235],"databases,":[246],"which":[247],"great":[250],"value":[251],"scenarios.":[254],"web":[256],"server":[257],"freely":[261],"available":[262],"at":[263],"noveldelta.com/RealVS":[264],"academic":[266],"purposes,":[267],"databases":[276],"accessible.":[278]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
