{"id":"https://openalex.org/W3199399339","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533382","title":"Drug-drug Interaction Prediction with Common Structural Patterns","display_name":"Drug-drug Interaction Prediction with Common Structural Patterns","publication_year":2021,"publication_date":"2021-07-18","ids":{"openalex":"https://openalex.org/W3199399339","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533382","mag":"3199399339"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn52387.2021.9533382","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533382","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5041940943","display_name":"Jiongmin Zhang","orcid":"https://orcid.org/0000-0003-0772-6771"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiongmin Zhang","raw_affiliation_strings":["School of Computer Science and Technology, East China Normal University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103014741","display_name":"Xing Yang","orcid":"https://orcid.org/0009-0009-0959-3571"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xing Yang","raw_affiliation_strings":["School of Computer Science and Technology, East China Normal University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101444861","display_name":"Ying Qian","orcid":"https://orcid.org/0000-0003-4961-5842"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Qian","raw_affiliation_strings":["School of Computer Science and Technology, East China Normal University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I66867065"],"apc_list":null,"apc_paid":null,"fwci":0.4076,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.51988012,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"5","issue":null,"first_page":"1","last_page":"7"},"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/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9810000061988831,"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/T10375","display_name":"Pharmacogenetics and Drug Metabolism","score":0.9703999757766724,"subfield":{"id":"https://openalex.org/subfields/3004","display_name":"Pharmacology"},"field":{"id":"https://openalex.org/fields/30","display_name":"Pharmacology, Toxicology and Pharmaceutics"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7435204386711121},{"id":"https://openalex.org/keywords/substructure","display_name":"Substructure","score":0.6511471271514893},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5842547416687012},{"id":"https://openalex.org/keywords/drug","display_name":"Drug","score":0.5253397822380066},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5175008773803711},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.49392443895339966},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.4916999936103821},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4717351198196411},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4691426157951355},{"id":"https://openalex.org/keywords/drug-drug-interaction","display_name":"Drug-drug interaction","score":0.4473060965538025},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.44642025232315063},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.418804407119751},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.367348313331604},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3644408583641052},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.23614534735679626},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07246512174606323},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.06693968176841736},{"id":"https://openalex.org/keywords/pharmacology","display_name":"Pharmacology","score":0.06344595551490784}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7435204386711121},{"id":"https://openalex.org/C99679407","wikidata":"https://www.wikidata.org/wiki/Q56761637","display_name":"Substructure","level":2,"score":0.6511471271514893},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5842547416687012},{"id":"https://openalex.org/C2780035454","wikidata":"https://www.wikidata.org/wiki/Q8386","display_name":"Drug","level":2,"score":0.5253397822380066},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5175008773803711},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.49392443895339966},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.4916999936103821},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4717351198196411},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4691426157951355},{"id":"https://openalex.org/C2910466267","wikidata":"https://www.wikidata.org/wiki/Q718753","display_name":"Drug-drug interaction","level":3,"score":0.4473060965538025},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.44642025232315063},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.418804407119751},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.367348313331604},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3644408583641052},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.23614534735679626},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07246512174606323},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.06693968176841736},{"id":"https://openalex.org/C98274493","wikidata":"https://www.wikidata.org/wiki/Q128406","display_name":"Pharmacology","level":1,"score":0.06344595551490784},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"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":1,"locations":[{"id":"doi:10.1109/ijcnn52387.2021.9533382","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533382","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.49000000953674316,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1018047830","https://openalex.org/W1028735754","https://openalex.org/W1979845492","https://openalex.org/W1999638776","https://openalex.org/W2009313526","https://openalex.org/W2109482131","https://openalex.org/W2153972688","https://openalex.org/W2519887557","https://openalex.org/W2529996553","https://openalex.org/W2571868483","https://openalex.org/W2594153126","https://openalex.org/W2777416523","https://openalex.org/W2786016794","https://openalex.org/W2794139534","https://openalex.org/W2799720196","https://openalex.org/W2802200505","https://openalex.org/W2803303416","https://openalex.org/W2900758217","https://openalex.org/W2955251621","https://openalex.org/W2962711740","https://openalex.org/W2962767366","https://openalex.org/W2963360524","https://openalex.org/W2963858333","https://openalex.org/W2964015378","https://openalex.org/W2997021962","https://openalex.org/W2997799485","https://openalex.org/W3005232784","https://openalex.org/W3015490653","https://openalex.org/W3080834109","https://openalex.org/W3098269892","https://openalex.org/W3100993589","https://openalex.org/W3156030440","https://openalex.org/W4294558607","https://openalex.org/W4297733535","https://openalex.org/W6726873649","https://openalex.org/W6731896910","https://openalex.org/W6738964360","https://openalex.org/W6745537798","https://openalex.org/W6751555526","https://openalex.org/W6754929296","https://openalex.org/W6785692931"],"related_works":["https://openalex.org/W3153444835","https://openalex.org/W2153916713","https://openalex.org/W2023846184","https://openalex.org/W2703419385","https://openalex.org/W2329056228","https://openalex.org/W2284584236","https://openalex.org/W1979083399","https://openalex.org/W2344320748","https://openalex.org/W2374530195","https://openalex.org/W2953357932"],"abstract_inverted_index":{"Substructures":[0],"of":[1,86],"drugs":[2,11,48],"are":[3,16,23],"important":[4],"for":[5,49],"drug-drug":[6],"interaction":[7],"(DDI)":[8],"prediction":[9],"because":[10],"with":[12],"similar":[13,20],"chemical":[14,107],"structures":[15],"prone":[17],"to":[18,82,102],"share":[19],"properties.":[21],"There":[22],"common":[24,44,66],"substructures":[25],"(i.e.,":[26],"functional":[27],"groups)":[28],"that":[29,93],"play":[30],"significant":[31],"roles":[32],"in":[33],"DDI":[34,50],"prediction.":[35,51],"However,":[36],"the":[37,77,84],"existing":[38],"computational":[39],"methods":[40],"can't":[41],"fully":[42,64],"utilize":[43,65],"structural":[45,67,105],"patterns":[46,68],"between":[47,69],"In":[52],"this":[53],"paper,":[54],"we":[55],"develop":[56],"a":[57],"substructure-based":[58],"framework":[59],"named":[60],"StructDDI":[61,111],"which":[62],"can":[63],"drugs.":[70,87],"A":[71,88],"graph":[72],"processing":[73],"method":[74],"based":[75],"on":[76,114],"random":[78],"walk":[79],"is":[80,100],"proposed":[81,101,110],"generate":[83],"representation":[85],"novel":[89],"feature":[90],"extraction":[91],"component":[92],"includes":[94],"dual":[95],"convolutional":[96],"neural":[97],"networks":[98],"(CNNs)":[99],"automatically":[103],"summarize":[104],"and":[106,118],"representation.":[108],"The":[109],"was":[112],"evaluated":[113],"two":[115],"real-world":[116],"datasets":[117],"performed":[119],"better":[120],"than":[121],"state-of-the-art":[122],"baselines.":[123]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-08-09T07:27:16.801131","created_date":"2025-10-10T00:00:00"}
