{"id":"https://openalex.org/W4415250858","doi":"https://doi.org/10.1109/hpec67600.2025.11196555","title":"A Hybrid Classical-Quantum Model for QSAR-Based Biodegradability Prediction","display_name":"A Hybrid Classical-Quantum Model for QSAR-Based Biodegradability Prediction","publication_year":2025,"publication_date":"2025-09-15","ids":{"openalex":"https://openalex.org/W4415250858","doi":"https://doi.org/10.1109/hpec67600.2025.11196555"},"language":"en","primary_location":{"id":"doi:10.1109/hpec67600.2025.11196555","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hpec67600.2025.11196555","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE High Performance Extreme Computing Conference (HPEC)","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/A5050202571","display_name":"Batuhan Hangun","orcid":"https://orcid.org/0000-0002-0271-6868"},"institutions":[{"id":"https://openalex.org/I4101805","display_name":"Y\u0131ld\u0131z Technical University","ror":"https://ror.org/0547yzj13","country_code":"TR","type":"education","lineage":["https://openalex.org/I4101805"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"Batuhan Hangun","raw_affiliation_strings":["Yildiz Technical University,Computer Engineering Department,&#x0130;stanbul,T&#x00FC;rkiye"],"affiliations":[{"raw_affiliation_string":"Yildiz Technical University,Computer Engineering Department,&#x0130;stanbul,T&#x00FC;rkiye","institution_ids":["https://openalex.org/I4101805"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Oguz Altun","orcid":null},"institutions":[{"id":"https://openalex.org/I4101805","display_name":"Y\u0131ld\u0131z Technical University","ror":"https://ror.org/0547yzj13","country_code":"TR","type":"education","lineage":["https://openalex.org/I4101805"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Oguz Altun","raw_affiliation_strings":["Yildiz Technical University,Computer Engineering Department,&#x0130;stanbul,T&#x00FC;rkiye"],"affiliations":[{"raw_affiliation_string":"Yildiz Technical University,Computer Engineering Department,&#x0130;stanbul,T&#x00FC;rkiye","institution_ids":["https://openalex.org/I4101805"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084311765","display_name":"\u00d6nder Eyecio\u011flu","orcid":"https://orcid.org/0000-0002-9735-5697"},"institutions":[{"id":"https://openalex.org/I76973811","display_name":"Bolu Abant \u0130zzet Baysal University","ror":"https://ror.org/01x1kqx83","country_code":"TR","type":"education","lineage":["https://openalex.org/I76973811"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Onder Eyecioglu","raw_affiliation_strings":["Bolu Abant Izzet Baysal University,Computer Engineering Department,Bolu,T&#x00FC;rkiye"],"affiliations":[{"raw_affiliation_string":"Bolu Abant Izzet Baysal University,Computer Engineering Department,Bolu,T&#x00FC;rkiye","institution_ids":["https://openalex.org/I76973811"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5050202571"],"corresponding_institution_ids":["https://openalex.org/I4101805"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.37791824,"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":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14249","display_name":"Water Quality Monitoring and Analysis","score":0.7802000045776367,"subfield":{"id":"https://openalex.org/subfields/2311","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T14249","display_name":"Water Quality Monitoring and Analysis","score":0.7802000045776367,"subfield":{"id":"https://openalex.org/subfields/2311","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.6789000034332275,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7073000073432922},{"id":"https://openalex.org/keywords/quantum","display_name":"Quantum","score":0.6204000115394592},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6035000085830688},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.47440001368522644},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.3720000088214874},{"id":"https://openalex.org/keywords/quantitative-structure\u2013activity-relationship","display_name":"Quantitative structure\u2013activity relationship","score":0.357699990272522},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.34940001368522644},{"id":"https://openalex.org/keywords/hybrid-system","display_name":"Hybrid system","score":0.33070001006126404}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7073000073432922},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6227999925613403},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.6204000115394592},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6035000085830688},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5472999811172485},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5055999755859375},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.47440001368522644},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3720000088214874},{"id":"https://openalex.org/C164126121","wikidata":"https://www.wikidata.org/wiki/Q766383","display_name":"Quantitative structure\u2013activity relationship","level":2,"score":0.357699990272522},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.34940001368522644},{"id":"https://openalex.org/C50897621","wikidata":"https://www.wikidata.org/wiki/Q2665508","display_name":"Hybrid system","level":2,"score":0.33070001006126404},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.33059999346733093},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.3287999927997589},{"id":"https://openalex.org/C186060115","wikidata":"https://www.wikidata.org/wiki/Q30336093","display_name":"Biological system","level":1,"score":0.328000009059906},{"id":"https://openalex.org/C2779094486","wikidata":"https://www.wikidata.org/wiki/Q18811578","display_name":"Quantum machine learning","level":4,"score":0.3230000138282776},{"id":"https://openalex.org/C58053490","wikidata":"https://www.wikidata.org/wiki/Q176555","display_name":"Quantum computer","level":3,"score":0.3174999952316284},{"id":"https://openalex.org/C47822265","wikidata":"https://www.wikidata.org/wiki/Q854457","display_name":"Complex system","level":2,"score":0.29760000109672546},{"id":"https://openalex.org/C2991951333","wikidata":"https://www.wikidata.org/wiki/Q188403","display_name":"Quantum chemical","level":3,"score":0.2799000144004822},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.27480000257492065},{"id":"https://openalex.org/C2779990667","wikidata":"https://www.wikidata.org/wiki/Q5953266","display_name":"Hybrid neural network","level":3,"score":0.2703999876976013},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2637999951839447},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.2630999982357025},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.25459998846054077},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2533999979496002},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2500999867916107}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/hpec67600.2025.11196555","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hpec67600.2025.11196555","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE High Performance Extreme Computing Conference (HPEC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2054716083","https://openalex.org/W2096885696","https://openalex.org/W2527330915","https://openalex.org/W3040892571","https://openalex.org/W3194990535","https://openalex.org/W4388166596","https://openalex.org/W4404691951","https://openalex.org/W4405937107","https://openalex.org/W4409132087"],"related_works":[],"abstract_inverted_index":{"Quantitative":[0],"Structure-Activity":[1],"Relationship":[2],"(QSAR)":[3],"analysis":[4],"is":[5,23],"a":[6,11,24,55,61,82,87,95,104,144,166],"computational":[7,173],"method":[8],"that":[9,71],"predicts":[10],"chemical\u2019s":[12],"properties,":[13],"such":[14],"as":[15],"its":[16,19],"biodegradability,":[17],"from":[18],"molecular":[20],"structure.":[21],"It":[22],"powerful,":[25],"cost-effective":[26],"alternative":[27,168],"to":[28,68,140,157,169],"traditional":[29],"lab":[30],"testing.":[31],"While":[32],"classical":[33,77,96,141,170],"machine":[34,58],"learning":[35,59],"(ML)":[36],"approaches":[37],"like":[38],"k-nearest":[39],"neighbor":[40],"(kNN)":[41],"and":[42,103,134],"support":[43],"vector":[44],"machines":[45],"(SVM)":[46],"have":[47],"been":[48],"successful":[49],"in":[50,172],"QSAR,":[51],"complex":[52,75],"problems":[53,70],"remain":[54],"challenge.":[56],"Quantum":[57],"(QML),":[60],"subfield":[62],"of":[63,120,123,126,129,132,137,147],"quantum":[64,105],"computing,":[65],"has":[66],"emerged":[67],"address":[69],"may":[72],"be":[73],"too":[74],"for":[76,86,100,109],"methods.":[78,159],"This":[79],"study":[80],"proposes":[81],"hybrid":[83,112,151],"classical-quantum":[84],"model":[85,93,113],"QSAR":[88],"biodegradability":[89],"classification":[90],"task.":[91],"Our":[92],"leverages":[94],"neural":[97,106],"network":[98,107],"(NN)":[99],"feature":[101],"extraction":[102],"(QNN)":[108],"classification.":[110],"The":[111],"yielded":[114],"promising":[115],"results,":[116],"achieving":[117],"an":[118,135],"accuracy":[119],"87.96%,":[121],"precision":[122],"84.29%,":[124],"recall":[125],"79.21%,":[127],"F1-Score":[128],"81.61%,":[130],"specificity":[131],"91.85%,":[133],"AUROC":[136],"0.92.":[138],"Compared":[139],"models":[142],"with":[143],"similar":[145],"number":[146],"trainable":[148],"parameters,":[149],"our":[150],"approach":[152],"achieved":[153],"performance":[154],"nearly":[155],"comparable":[156],"state-of-the-art":[158],"These":[160],"results":[161],"suggest":[162],"QML":[163],"could":[164],"become":[165],"strong":[167],"ML":[171],"chemistry.":[174]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-16T00:00:00"}
