{"id":"https://openalex.org/W4401585894","doi":"https://doi.org/10.1007/s40747-024-01602-0","title":"Molecular subgraph representation learning based on spatial structure transformer","display_name":"Molecular subgraph representation learning based on spatial structure transformer","publication_year":2024,"publication_date":"2024-08-14","ids":{"openalex":"https://openalex.org/W4401585894","doi":"https://doi.org/10.1007/s40747-024-01602-0"},"language":"en","primary_location":{"id":"doi:10.1007/s40747-024-01602-0","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1007/s40747-024-01602-0","pdf_url":"https://link.springer.com/content/pdf/10.1007/s40747-024-01602-0.pdf","source":{"id":"https://openalex.org/S3035462843","display_name":"Complex & Intelligent Systems","issn_l":"2198-6053","issn":["2198-6053","2199-4536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complex &amp; Intelligent Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://link.springer.com/content/pdf/10.1007/s40747-024-01602-0.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5112532308","display_name":"S. W. Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I178232147","display_name":"Guizhou University","ror":"https://ror.org/02wmsc916","country_code":"CN","type":"education","lineage":["https://openalex.org/I178232147"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shaoguang Zhang","raw_affiliation_strings":["State Key Laboratory of Public Big Data, Guizhou University, Guiyang, 550025, Guizhou, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Public Big Data, Guizhou University, Guiyang, 550025, Guizhou, China","institution_ids":["https://openalex.org/I178232147"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037067067","display_name":"Jianguang Lu","orcid":"https://orcid.org/0000-0002-2191-1570"},"institutions":[{"id":"https://openalex.org/I178232147","display_name":"Guizhou University","ror":"https://ror.org/02wmsc916","country_code":"CN","type":"education","lineage":["https://openalex.org/I178232147"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianguang Lu","raw_affiliation_strings":["State Key Laboratory of Public Big Data, Guizhou University, Guiyang, 550025, Guizhou, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Public Big Data, Guizhou University, Guiyang, 550025, Guizhou, China","institution_ids":["https://openalex.org/I178232147"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056315702","display_name":"Xianghong Tang","orcid":"https://orcid.org/0000-0003-1226-8365"},"institutions":[{"id":"https://openalex.org/I178232147","display_name":"Guizhou University","ror":"https://ror.org/02wmsc916","country_code":"CN","type":"education","lineage":["https://openalex.org/I178232147"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianghong Tang","raw_affiliation_strings":["State Key Laboratory of Public Big Data, Guizhou University, Guiyang, 550025, Guizhou, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Public Big Data, Guizhou University, Guiyang, 550025, Guizhou, China","institution_ids":["https://openalex.org/I178232147"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5112532308"],"corresponding_institution_ids":["https://openalex.org/I178232147"],"apc_list":{"value":1320,"currency":"GBP","value_usd":1619},"apc_paid":{"value":1320,"currency":"GBP","value_usd":1619},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10853765,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9986000061035156,"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"}},"topics":[{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9986000061035156,"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/T10211","display_name":"Computational Drug Discovery Methods","score":0.9973999857902527,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9897000193595886,"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/computational-intelligence","display_name":"Computational intelligence","score":0.6170005202293396},{"id":"https://openalex.org/keywords/induced-subgraph-isomorphism-problem","display_name":"Induced subgraph isomorphism problem","score":0.5695824027061462},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5466173887252808},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5127280950546265},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4322068691253662},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.42838332056999207},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4268264174461365},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4148372709751129},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.25194844603538513},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.21162068843841553},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.08810332417488098},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.0604226291179657}],"concepts":[{"id":"https://openalex.org/C139502532","wikidata":"https://www.wikidata.org/wiki/Q1122090","display_name":"Computational intelligence","level":2,"score":0.6170005202293396},{"id":"https://openalex.org/C191241153","wikidata":"https://www.wikidata.org/wiki/Q6027240","display_name":"Induced subgraph isomorphism problem","level":5,"score":0.5695824027061462},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5466173887252808},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5127280950546265},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4322068691253662},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.42838332056999207},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4268264174461365},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4148372709751129},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.25194844603538513},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.21162068843841553},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.08810332417488098},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0604226291179657},{"id":"https://openalex.org/C22149727","wikidata":"https://www.wikidata.org/wiki/Q7940747","display_name":"Voltage graph","level":4,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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":2,"locations":[{"id":"doi:10.1007/s40747-024-01602-0","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1007/s40747-024-01602-0","pdf_url":"https://link.springer.com/content/pdf/10.1007/s40747-024-01602-0.pdf","source":{"id":"https://openalex.org/S3035462843","display_name":"Complex & Intelligent Systems","issn_l":"2198-6053","issn":["2198-6053","2199-4536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complex &amp; Intelligent Systems","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:d09c4c94bc2b46cda84da9d273be2745","is_oa":true,"landing_page_url":"https://doaj.org/article/d09c4c94bc2b46cda84da9d273be2745","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":"Complex & Intelligent Systems, Vol 10, Iss 6, Pp 8197-8212 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s40747-024-01602-0","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1007/s40747-024-01602-0","pdf_url":"https://link.springer.com/content/pdf/10.1007/s40747-024-01602-0.pdf","source":{"id":"https://openalex.org/S3035462843","display_name":"Complex & Intelligent Systems","issn_l":"2198-6053","issn":["2198-6053","2199-4536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complex &amp; Intelligent Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322272","display_name":"Guizhou Science and Technology Department","ror":"https://ror.org/00kwnh405"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4401585894.pdf","grobid_xml":"https://content.openalex.org/works/W4401585894.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W1888005072","https://openalex.org/W2027482274","https://openalex.org/W2066043610","https://openalex.org/W2154851992","https://openalex.org/W2700550412","https://openalex.org/W2743104969","https://openalex.org/W2766856748","https://openalex.org/W2962756421","https://openalex.org/W2979750740","https://openalex.org/W3035664258","https://openalex.org/W3097300053","https://openalex.org/W3104097132","https://openalex.org/W3116278528","https://openalex.org/W3176315233","https://openalex.org/W3200354666","https://openalex.org/W4214868967","https://openalex.org/W4223942768","https://openalex.org/W4226427994","https://openalex.org/W4294310652","https://openalex.org/W4360591883","https://openalex.org/W4362520745","https://openalex.org/W4375947995","https://openalex.org/W4382501959","https://openalex.org/W4386453561","https://openalex.org/W4389856652","https://openalex.org/W4392617883","https://openalex.org/W4392913700","https://openalex.org/W4396242773","https://openalex.org/W6601843209","https://openalex.org/W6601955380","https://openalex.org/W6606697098","https://openalex.org/W6638553918"],"related_works":["https://openalex.org/W231720905","https://openalex.org/W1482551403","https://openalex.org/W2532922352","https://openalex.org/W2128390795","https://openalex.org/W2915540008","https://openalex.org/W2604893261","https://openalex.org/W3002471523","https://openalex.org/W2604114816","https://openalex.org/W2361654510","https://openalex.org/W2393701947"],"abstract_inverted_index":{"In":[0,114],"the":[1,58,69,90,102,106,116,120,135,140],"field":[2],"of":[3,29,122],"molecular":[4,12],"biology,":[5],"graph":[6,41,103,141,145],"representation":[7,42,146],"learning":[8,43],"is":[9],"crucial":[10],"for":[11],"structure":[13,31,49],"analysis.":[14],"However,":[15],"challenges":[16],"arise":[17],"in":[18],"recognising":[19],"functional":[20],"groups":[21],"and":[22,68,88],"distinguishing":[23],"isomers":[24],"due":[25],"to":[26],"a":[27,39,47],"lack":[28],"spatial":[30,48,81],"information.":[32],"To":[33],"address":[34],"these":[35],"problems,":[36],"we":[37],"design":[38],"novel":[40],"method":[44],"based":[45,100],"on":[46,101,130,139],"information":[50,83,99],"extraction":[51],"Transformer":[52,74],"(SSET).":[53],"The":[54,77,94],"SSET":[55,117,136],"model":[56,118],"comprises":[57],"Edge":[59],"Feature":[60],"Fusion":[61],"Subgraph":[62],"Spatial":[63],"Structure":[64],"Extractor":[65],"(ETSE)":[66],"module":[67,79,96],"Positional":[70],"Information":[71],"Encoding":[72],"Graph":[73],"(PEGT)":[75],"module.":[76],"ETSE":[78],"extracts":[80],"structural":[82],"by":[84,126],"fusing":[85],"edge":[86],"features":[87],"generating":[89],"most-value":[91],"subgraph":[92],"(Mv-subgraph).":[93],"PEGT":[95],"encodes":[97],"positional":[98],"transformer,":[104,142],"addressing":[105],"indistinguishability":[107],"problem":[108],"among":[109],"nodes":[110],"with":[111],"identical":[112],"features.":[113],"addition,":[115],"alleviates":[119],"burden":[121],"high":[123],"computational":[124],"complexity":[125],"using":[127],"subgraph.":[128],"Experiments":[129],"real":[131],"datasets":[132],"show":[133],"that":[134],"model,":[137],"built":[138],"considerably":[143],"improves":[144],"learning.":[147]},"counts_by_year":[],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}
