{"id":"https://openalex.org/W4319321503","doi":"https://doi.org/10.1186/s13321-023-00689-w","title":"How to approach machine learning-based prediction of drug/compound\u2013target interactions","display_name":"How to approach machine learning-based prediction of drug/compound\u2013target interactions","publication_year":2023,"publication_date":"2023-02-06","ids":{"openalex":"https://openalex.org/W4319321503","doi":"https://doi.org/10.1186/s13321-023-00689-w","pmid":"https://pubmed.ncbi.nlm.nih.gov/36747300"},"language":"en","primary_location":{"id":"doi:10.1186/s13321-023-00689-w","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13321-023-00689-w","pdf_url":"https://jcheminf.biomedcentral.com/counter/pdf/10.1186/s13321-023-00689-w","source":{"id":"https://openalex.org/S180838163","display_name":"Journal of Cheminformatics","issn_l":"1758-2946","issn":["1758-2946"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Cheminformatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://jcheminf.biomedcentral.com/counter/pdf/10.1186/s13321-023-00689-w","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054058101","display_name":"Heval Ata\u015f","orcid":"https://orcid.org/0000-0003-3180-7010"},"institutions":[{"id":"https://openalex.org/I66514158","display_name":"Hacettepe University","ror":"https://ror.org/04kwvgz42","country_code":"TR","type":"education","lineage":["https://openalex.org/I66514158"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"Heval Atas Guvenilir","raw_affiliation_strings":["Biological Data Science Laboratory, Department of Computer Engineering, Hacettepe University, Ankara, Turkey","Department of Health Informatics, Graduate School of Informatics, METU, Ankara, Turkey"],"affiliations":[{"raw_affiliation_string":"Biological Data Science Laboratory, Department of Computer Engineering, Hacettepe University, Ankara, Turkey","institution_ids":["https://openalex.org/I66514158"]},{"raw_affiliation_string":"Department of Health Informatics, Graduate School of Informatics, METU, Ankara, Turkey","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003981652","display_name":"Tunca Do\u011fan","orcid":"https://orcid.org/0000-0002-1298-9763"},"institutions":[{"id":"https://openalex.org/I66514158","display_name":"Hacettepe University","ror":"https://ror.org/04kwvgz42","country_code":"TR","type":"education","lineage":["https://openalex.org/I66514158"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Tunca Do\u011fan","raw_affiliation_strings":["Biological Data Science Laboratory, Department of Computer Engineering, Hacettepe University, Ankara, Turkey. tuncadogan@gmail.com","Department of Bioinformatics, Graduate School of Health Sciences, Hacettepe University, Ankara, Turkey. tuncadogan@gmail.com","Institute of Informatics, Hacettepe University, Ankara, Turkey. tuncadogan@gmail.com","Biological Data Science Laboratory, Department of Computer Engineering, Hacettepe University, Ankara, Turkey"],"affiliations":[{"raw_affiliation_string":"Biological Data Science Laboratory, Department of Computer Engineering, Hacettepe University, Ankara, Turkey. tuncadogan@gmail.com","institution_ids":["https://openalex.org/I66514158"]},{"raw_affiliation_string":"Department of Bioinformatics, Graduate School of Health Sciences, Hacettepe University, Ankara, Turkey. tuncadogan@gmail.com","institution_ids":["https://openalex.org/I66514158"]},{"raw_affiliation_string":"Institute of Informatics, Hacettepe University, Ankara, Turkey. tuncadogan@gmail.com","institution_ids":["https://openalex.org/I66514158"]},{"raw_affiliation_string":"Biological Data Science Laboratory, Department of Computer Engineering, Hacettepe University, Ankara, Turkey","institution_ids":["https://openalex.org/I66514158"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5054058101"],"corresponding_institution_ids":["https://openalex.org/I66514158"],"apc_list":{"value":1290,"currency":"GBP","value_usd":1582},"apc_paid":{"value":1290,"currency":"GBP","value_usd":1582},"fwci":7.2219,"has_fulltext":true,"cited_by_count":37,"citation_normalized_percentile":{"value":0.9763019,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"15","issue":"1","first_page":"16","last_page":"16"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9998999834060669,"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":0.9998999834060669,"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/T10044","display_name":"Protein Structure and Dynamics","score":0.9950000047683716,"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":0.9904999732971191,"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":0.807874858379364},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.7286310195922852},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7270948886871338},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7068560123443604},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5639507174491882},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5343548059463501},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5176092386245728},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4745691120624542},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4100213050842285}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.807874858379364},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7286310195922852},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7270948886871338},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7068560123443604},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5639507174491882},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5343548059463501},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5176092386245728},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4745691120624542},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4100213050842285},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1186/s13321-023-00689-w","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13321-023-00689-w","pdf_url":"https://jcheminf.biomedcentral.com/counter/pdf/10.1186/s13321-023-00689-w","source":{"id":"https://openalex.org/S180838163","display_name":"Journal of Cheminformatics","issn_l":"1758-2946","issn":["1758-2946"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Cheminformatics","raw_type":"journal-article"},{"id":"pmid:36747300","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36747300","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 cheminformatics","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:9901167","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9901167","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"J Cheminform","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:c6682b1be6c2439097c1459f640060f5","is_oa":true,"landing_page_url":"https://doaj.org/article/c6682b1be6c2439097c1459f640060f5","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Cheminformatics, Vol 15, Iss 1, Pp 1-36 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s13321-023-00689-w","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s13321-023-00689-w","pdf_url":"https://jcheminf.biomedcentral.com/counter/pdf/10.1186/s13321-023-00689-w","source":{"id":"https://openalex.org/S180838163","display_name":"Journal of Cheminformatics","issn_l":"1758-2946","issn":["1758-2946"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Cheminformatics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1702585728","display_name":null,"funder_award_id":"100/2000","funder_id":"https://openalex.org/F4320322626","funder_display_name":"T\u00fcrkiye Bilimsel ve Teknolojik Ara\u015ft\u0131rma Kurumu"},{"id":"https://openalex.org/G2652306973","display_name":null,"funder_award_id":"BIDEB 2211","funder_id":"https://openalex.org/F4320322626","funder_display_name":"T\u00fcrkiye Bilimsel ve Teknolojik Ara\u015ft\u0131rma Kurumu"},{"id":"https://openalex.org/G324628671","display_name":null,"funder_award_id":"YOK 100/2000","funder_id":"https://openalex.org/F4320322626","funder_display_name":"T\u00fcrkiye Bilimsel ve Teknolojik Ara\u015ft\u0131rma Kurumu"},{"id":"https://openalex.org/G349127512","display_name":null,"funder_award_id":"TUBITAK-BIDEB","funder_id":"https://openalex.org/F4320322626","funder_display_name":"T\u00fcrkiye Bilimsel ve Teknolojik Ara\u015ft\u0131rma Kurumu"},{"id":"https://openalex.org/G8042658919","display_name":null,"funder_award_id":"BIDEB","funder_id":"https://openalex.org/F4320322626","funder_display_name":"T\u00fcrkiye Bilimsel ve Teknolojik Ara\u015ft\u0131rma Kurumu"}],"funders":[{"id":"https://openalex.org/F4320322626","display_name":"T\u00fcrkiye Bilimsel ve Teknolojik Ara\u015ft\u0131rma Kurumu","ror":"https://ror.org/04w9kkr77"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4319321503.pdf"},"referenced_works_count":83,"referenced_works":["https://openalex.org/W1501531009","https://openalex.org/W1982267716","https://openalex.org/W1983478747","https://openalex.org/W1988037271","https://openalex.org/W1993711987","https://openalex.org/W1996423252","https://openalex.org/W2000671825","https://openalex.org/W2007965730","https://openalex.org/W2011301426","https://openalex.org/W2019488416","https://openalex.org/W2033882981","https://openalex.org/W2042084565","https://openalex.org/W2043338013","https://openalex.org/W2068819452","https://openalex.org/W2070930739","https://openalex.org/W2079745490","https://openalex.org/W2083582778","https://openalex.org/W2086286404","https://openalex.org/W2093788819","https://openalex.org/W2094403468","https://openalex.org/W2099071242","https://openalex.org/W2100076566","https://openalex.org/W2102461176","https://openalex.org/W2129434099","https://openalex.org/W2131681506","https://openalex.org/W2132022337","https://openalex.org/W2132292391","https://openalex.org/W2133197376","https://openalex.org/W2135209350","https://openalex.org/W2142325821","https://openalex.org/W2144377773","https://openalex.org/W2147863530","https://openalex.org/W2148145769","https://openalex.org/W2152800101","https://openalex.org/W2174991771","https://openalex.org/W2268071782","https://openalex.org/W2324589236","https://openalex.org/W2327079070","https://openalex.org/W2399767476","https://openalex.org/W2411478524","https://openalex.org/W2500660203","https://openalex.org/W2531200345","https://openalex.org/W2549144853","https://openalex.org/W2558999090","https://openalex.org/W2594183968","https://openalex.org/W2597806392","https://openalex.org/W2612935389","https://openalex.org/W2740946158","https://openalex.org/W2766155572","https://openalex.org/W2785947426","https://openalex.org/W2793168264","https://openalex.org/W2793997912","https://openalex.org/W2806547269","https://openalex.org/W2807567459","https://openalex.org/W2886544065","https://openalex.org/W2887905891","https://openalex.org/W2892210937","https://openalex.org/W2898402099","https://openalex.org/W2951433247","https://openalex.org/W2952209560","https://openalex.org/W2954364924","https://openalex.org/W2969180072","https://openalex.org/W2971227267","https://openalex.org/W2980789587","https://openalex.org/W2994270865","https://openalex.org/W2995514860","https://openalex.org/W2999309192","https://openalex.org/W2999481648","https://openalex.org/W2999554466","https://openalex.org/W3003896119","https://openalex.org/W3014805132","https://openalex.org/W3024894813","https://openalex.org/W3093397714","https://openalex.org/W3099768174","https://openalex.org/W3112376646","https://openalex.org/W3150635270","https://openalex.org/W3164680581","https://openalex.org/W3176163250","https://openalex.org/W3216192226","https://openalex.org/W3217661426","https://openalex.org/W3217681006","https://openalex.org/W4220991280","https://openalex.org/W4240082606"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W2745001401","https://openalex.org/W4321353415","https://openalex.org/W2130974462","https://openalex.org/W972276598","https://openalex.org/W4246352526","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W2087343574","https://openalex.org/W2121910908"],"abstract_inverted_index":{"The":[0,48],"identification":[1],"of":[2,9,50,61,70,80,116,145,238,280],"drug/compound-target":[3],"interactions":[4],"(DTIs)":[5],"constitutes":[6],"the":[7,39,59,68,74,83,128,143,292,312,319],"basis":[8],"drug":[10,348],"discovery,":[11],"for":[12,67,120,180,321],"which":[13,88],"computational":[14,118],"predictive":[15],"approaches":[16,126],"have":[17,343],"been":[18,103],"developed.":[19],"As":[20],"a":[21,36,98,113,189,256],"relatively":[22],"new":[23,322],"data-driven":[24,338],"paradigm,":[25],"proteochemometric":[26],"(PCM)":[27],"modeling":[28,183],"utilizes":[29],"both":[30,124],"protein":[31,121,263,307],"and":[32,42,55,77,96,127,134,139,150,163,170,187,201,214,219,242,250,271,289,323,336],"compound":[33,302],"properties":[34,72,277],"as":[35,176,255],"pair":[37],"at":[38],"input":[40,51,89],"level":[41],"processes":[43],"them":[44],"via":[45,94],"statistical/machine":[46],"learning.":[47],"representation":[49,84],"samples":[52,90],"(i.e.,":[53],"proteins":[54,281],"their":[56,221,285],"ligands)":[57],"in":[58,87,105,154,268,315,333,347],"form":[60],"quantitative":[62],"feature":[63],"vectors":[64],"is":[65],"crucial":[66],"extraction":[69],"interaction-related":[71,276],"during":[73,284,291],"artificial":[75],"learning":[76,85,100,153,293],"subsequent":[78],"prediction":[79,217,270,340],"DTIs.":[81],"Lately,":[82],"approach,":[86],"are":[91,282],"automatically":[92],"featurized":[93],"training":[95,200],"applying":[97],"machine/deep":[99],"model,":[101],"has":[102],"utilized":[104],"biomedical":[106],"sciences.":[107],"In":[108],"this":[109,328],"study,":[110],"we":[111,159,212],"performed":[112],"comprehensive":[114],"investigation":[115],"different":[117,199,224],"approaches/techniques":[119],"featurization":[122,210],"(including":[123],"conventional":[125],"novel":[129],"learned":[130,262],"embeddings),":[131],"data":[132,148,248],"preparation":[133],"exploration,":[135],"machine":[136],"learning-based":[137],"modeling,":[138],"performance":[140,222],"evaluation":[141],"with":[142,208],"aim":[144],"achieving":[146],"better":[147],"representations":[149],"more":[151],"successful":[152],"DTI":[155,182,216,269,316,339],"prediction.":[156],"For":[157],"this,":[158],"first":[160],"constructed":[161],"realistic":[162],"challenging":[164],"benchmark":[165],"datasets":[166,196,206,239],"on":[167,301],"small,":[168],"medium,":[169],"large":[171],"scales":[172],"to":[173,194,246,298,311],"be":[174,230,259],"used":[175],"reliable":[177],"gold":[178],"standards":[179],"specific":[181],"tasks.":[184],"We":[185,326],"developed":[186],"applied":[188],"network":[190],"analysis-based":[191],"splitting":[192,237],"strategy":[193],"divide":[195],"into":[197,240],"structurally":[198],"test":[202,243],"folds.":[203],"Using":[204],"these":[205],"together":[207],"various":[209],"methods,":[211],"trained":[213],"tested":[215],"models":[218,296],"evaluated":[220],"from":[223],"angles.":[225],"Our":[226],"main":[227],"findings":[228],"can":[229],"summarized":[231],"under":[232],"3":[233],"items:":[234],"(i)":[235],"random":[236],"train":[241],"folds":[244],"leads":[245],"near-complete":[247],"memorization":[249],"produce":[251],"highly":[252],"over-optimistic":[253],"results,":[254],"result,":[257],"should":[258],"avoided,":[260],"(ii)":[261],"sequence":[264],"embeddings":[265],"work":[266],"well":[267],"offer":[272],"high":[273],"potential,":[274],"despite":[275],"(e.g.,":[278],"structures)":[279],"unused":[283],"self-supervised":[286],"model":[287],"training,":[288],"(iii)":[290],"process,":[294],"PCM":[295],"tend":[297],"rely":[299],"heavily":[300],"features":[303],"while":[304],"partially":[305],"ignoring":[306],"features,":[308],"primarily":[309],"due":[310],"inherent":[313],"bias":[314],"data,":[317],"indicating":[318],"requirement":[320],"unbiased":[324],"datasets.":[325],"hope":[327],"study":[329],"will":[330],"aid":[331],"researchers":[332],"designing":[334],"robust":[335],"high-performing":[337],"systems":[341],"that":[342],"real-world":[344],"translational":[345],"value":[346],"discovery.":[349]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":16},{"year":2023,"cited_by_count":3}],"updated_date":"2026-04-17T18:11:37.981687","created_date":"2025-10-10T00:00:00"}