{"id":"https://openalex.org/W4293518052","doi":"https://doi.org/10.1109/cibcb55180.2022.9863018","title":"DDIPred: Graph Convolutional Network-Based Drug-drug Interactions Prediction Using Drug Chemical Structure Embedding","display_name":"DDIPred: Graph Convolutional Network-Based Drug-drug Interactions Prediction Using Drug Chemical Structure Embedding","publication_year":2022,"publication_date":"2022-08-15","ids":{"openalex":"https://openalex.org/W4293518052","doi":"https://doi.org/10.1109/cibcb55180.2022.9863018"},"language":"en","primary_location":{"id":"doi:10.1109/cibcb55180.2022.9863018","doi":"https://doi.org/10.1109/cibcb55180.2022.9863018","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cibcb55180.2022.9863018","pdf_url":null,"source":{"id":"https://openalex.org/S7407088424","display_name":"IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)","raw_type":"proceedings-article"},"volume":null,"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/A5012758415","display_name":"Shaghayegh Sadeghi","orcid":"https://orcid.org/0000-0003-2346-1558","observed_orcids":["https://orcid.org/0000-0003-2346-1558"]},"institutions":[{"id":"https://openalex.org/I74413500","display_name":"University of Windsor","ror":"https://ror.org/01gw3d370","country_code":"CA","type":"education","lineage":["https://openalex.org/I74413500"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Shaghayegh Sadeghi","raw_affiliation_strings":["University of Windsor,School of Computer Science,Windsor,Canada","School of Computer Science, University of Windsor, Windsor, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Windsor,School of Computer Science,Windsor,Canada","institution_ids":["https://openalex.org/I74413500"]},{"raw_affiliation_string":"School of Computer Science, University of Windsor, Windsor, Canada","institution_ids":["https://openalex.org/I74413500"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070302649","display_name":"Alioune Ngom","orcid":"https://orcid.org/0000-0003-2092-2494","observed_orcids":["https://orcid.org/0000-0003-2092-2494"]},"institutions":[{"id":"https://openalex.org/I74413500","display_name":"University of Windsor","ror":"https://ror.org/01gw3d370","country_code":"CA","type":"education","lineage":["https://openalex.org/I74413500"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Alioune Ngom","raw_affiliation_strings":["University of Windsor,School of Computer Science,Windsor,Canada","School of Computer Science, University of Windsor, Windsor, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Windsor,School of Computer Science,Windsor,Canada","institution_ids":["https://openalex.org/I74413500"]},{"raw_affiliation_string":"School of Computer Science, University of Windsor, Windsor, Canada","institution_ids":["https://openalex.org/I74413500"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I74413500"],"apc_list":null,"apc_paid":null,"fwci":2.063,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.86841187,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"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/T10211","display_name":"Computational Drug Discovery Methods","score":0.9976000189781189,"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":0.9976000189781189,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.0003000000142492354,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.0003000000142492354,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/drug-drug-interactions","display_name":"drug-drug interactions","score":0.9120000004768372},{"id":"https://openalex.org/keywords/ddi-prediction","display_name":"DDI prediction","score":0.8109999895095825},{"id":"https://openalex.org/keywords/graph-convolutional-networks","display_name":"graph convolutional networks","score":0.9319999814033508},{"id":"https://openalex.org/keywords/selfies","display_name":"selfies","score":0.8799999952316284},{"id":"https://openalex.org/keywords/smiles-representation","display_name":"SMILES representation","score":0.7390000224113464},{"id":"https://openalex.org/keywords/doc2vec","display_name":"Doc2Vec","score":0.9909999966621399},{"id":"https://openalex.org/keywords/drug-interaction-networks","display_name":"drug interaction networks","score":0.6610000133514404},{"id":"https://openalex.org/keywords/drug-repurposing","display_name":"drug repurposing","score":0.8040000200271606},{"id":"https://openalex.org/keywords/drug-target-interactions","display_name":"drug-target interactions","score":0.6930000185966492}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7963303327560425},{"id":"https://openalex.org/C2780035454","wikidata":"https://www.wikidata.org/wiki/Q8386","display_name":"Drug","level":2,"score":0.7218449115753174},{"id":"https://openalex.org/C103637391","wikidata":"https://www.wikidata.org/wiki/Q5308921","display_name":"Drug repositioning","level":3,"score":0.624337375164032},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5607800483703613},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5451177954673767},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5325656533241272},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3918799161911011},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34217989444732666},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.31679224967956543},{"id":"https://openalex.org/C98274493","wikidata":"https://www.wikidata.org/wiki/Q128406","display_name":"Pharmacology","level":1,"score":0.16024842858314514},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.10592377185821533},{"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},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cibcb55180.2022.9863018","doi":"https://doi.org/10.1109/cibcb55180.2022.9863018","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cibcb55180.2022.9863018","pdf_url":null,"source":{"id":"https://openalex.org/S7407088424","display_name":"IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.504800021648407}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W168564468","https://openalex.org/W1975147762","https://openalex.org/W2011301426","https://openalex.org/W2131744502","https://openalex.org/W2173027866","https://openalex.org/W2529996553","https://openalex.org/W2767891136","https://openalex.org/W2777416523","https://openalex.org/W2802200505","https://openalex.org/W2913015533","https://openalex.org/W2997021962","https://openalex.org/W3009321976","https://openalex.org/W3024894285","https://openalex.org/W3035965352","https://openalex.org/W3045928028","https://openalex.org/W3094497296","https://openalex.org/W3099878876","https://openalex.org/W3157889929","https://openalex.org/W4211219865","https://openalex.org/W4214621766","https://openalex.org/W4214819330","https://openalex.org/W4294089543"],"related_works":["https://openalex.org/W4386033873","https://openalex.org/W4205564556","https://openalex.org/W2991849788","https://openalex.org/W3088680691","https://openalex.org/W4385288794","https://openalex.org/W4280614598","https://openalex.org/W7164085038","https://openalex.org/W2999886378","https://openalex.org/W4313532278","https://openalex.org/W4388034303"],"abstract_inverted_index":{"A":[0],"drug-drug":[1],"interaction":[2],"(DDI)":[3],"describes":[4],"a":[5,101,128,189],"circumstance":[6],"in":[7],"which":[8,90],"drugs":[9],"affect":[10],"the":[11,40,94,147,151,169],"activity":[12],"of":[13,42,130],"each":[14,20],"other.":[15],"Drugs":[16,34],"may":[17,35],"interact":[18,37],"with":[19,150],"other":[21,79,176],"to":[22,46,92,157],"cause":[23],"side":[24],"effects":[25],"that":[26],"are":[27,59,186],"unexpected":[28],"or":[29],"more":[30],"severe":[31],"than":[32],"anticipated.":[33],"also":[36],"and":[38,70,87,117,144,183],"oppose":[39],"results":[41],"one":[43,47],"another,":[44],"leading":[45],"(or":[48],"both)":[49],"medications":[50],"not":[51,68],"having":[52],"their":[53],"intended":[54],"effect.":[55],"Most":[56],"drug":[57,85,95,113],"interactions":[58],"negligible,":[60],"but":[61],"some":[62],"can":[63,75],"be":[64,76],"significantly":[65],"harmful":[66],"if":[67],"discovered":[69],"appropriately":[71],"overseen.":[72],"DDI":[73,105,152,171],"data":[74,185],"helpful":[77],"for":[78,104,121],"drug-related":[80],"research":[81],"topics":[82],"such":[83],"as":[84],"repurposing":[86],"drug-target":[88],"interaction,":[89],"leads":[91],"improving":[93],"development":[96],"process.":[97],"This":[98],"paper":[99],"presents":[100],"new":[102,123,159],"method":[103,162],"prediction":[106],"named":[107],"DDIPred.":[108],"It":[109],"is":[110,155],"based":[111],"on":[112,168],"chemical":[114],"structure":[115],"embedding":[116],"graph":[118],"convolutional":[119],"networks":[120],"predicting":[122],"DDIs.":[124,160],"DDIPred":[125],"First":[126],"extracts":[127],"representation":[129],"Simplified":[131],"Molecular":[132],"Input":[133],"Line":[134],"Entry":[135],"System":[136],"(SMILES)":[137],"strings":[138],"using":[139],"SELF-referencIng":[140],"Embedded":[141],"Strings":[142],"(SELFIES)":[143],"Doc2Vec.":[145],"Then":[146],"representation,":[148],"along":[149],"network":[153,172],"structure,":[154],"used":[156],"predict":[158],"Our":[161],"achieved":[163],"acceptable":[164],"performance":[165],"when":[166],"tested":[167],"BIOSNAP":[170],"dataset":[173],"while":[174],"outperforming":[175],"existing":[177],"methods.":[178],"Availability:":[179],"The":[180],"source":[181],"code":[182],"sample":[184],"available":[187],"via":[188],"Github":[190],"project":[191],"at":[192],"https://github.com/sshaghayeghs/DDIPred.":[193]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2022-08-30T00:00:00"}