{"id":"https://openalex.org/W4390971258","doi":"https://doi.org/10.1109/bibm58861.2023.10385857","title":"Transformer and Snowball Graph Convolution Learning for Brain Functional Network Analysis","display_name":"Transformer and Snowball Graph Convolution Learning for Brain Functional Network Analysis","publication_year":2023,"publication_date":"2023-12-05","ids":{"openalex":"https://openalex.org/W4390971258","doi":"https://doi.org/10.1109/bibm58861.2023.10385857"},"language":"en","primary_location":{"id":"doi:10.1109/bibm58861.2023.10385857","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm58861.2023.10385857","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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/A5042282783","display_name":"Jinlong Hu","orcid":"https://orcid.org/0000-0003-3602-7603"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jinlong Hu","raw_affiliation_strings":["South China University of Technology,Guangdong Key Lab of Communication and Computer Network,School of Computer Science and Engineering,Guangzhou,China","School of Computer Science and Engineering, Guangdong Key Lab of Communication and Computer Network, South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"South China University of Technology,Guangdong Key Lab of Communication and Computer Network,School of Computer Science and Engineering,Guangzhou,China","institution_ids":["https://openalex.org/I90610280"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Guangdong Key Lab of Communication and Computer Network, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102600726","display_name":"Yangmin Huang","orcid":"https://orcid.org/0000-0002-1161-998X"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yangmin Huang","raw_affiliation_strings":["South China University of Technology,Guangdong Key Lab of Communication and Computer Network,School of Computer Science and Engineering,Guangzhou,China","School of Computer Science and Engineering, Guangdong Key Lab of Communication and Computer Network, South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"South China University of Technology,Guangdong Key Lab of Communication and Computer Network,School of Computer Science and Engineering,Guangzhou,China","institution_ids":["https://openalex.org/I90610280"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Guangdong Key Lab of Communication and Computer Network, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052760299","display_name":"Shoubin Dong","orcid":"https://orcid.org/0000-0003-0153-850X"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shoubin Dong","raw_affiliation_strings":["South China University of Technology,Guangdong Key Lab of Communication and Computer Network,School of Computer Science and Engineering,Guangzhou,China","School of Computer Science and Engineering, Guangdong Key Lab of Communication and Computer Network, South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"South China University of Technology,Guangdong Key Lab of Communication and Computer Network,School of Computer Science and Engineering,Guangzhou,China","institution_ids":["https://openalex.org/I90610280"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Guangdong Key Lab of Communication and Computer Network, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5042282783"],"corresponding_institution_ids":["https://openalex.org/I90610280"],"apc_list":null,"apc_paid":null,"fwci":0.5431,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.65861893,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2809","last_page":"2816"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9955999851226807,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9790999889373779,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6774358749389648},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.569094181060791},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5026731491088867},{"id":"https://openalex.org/keywords/power-graph-analysis","display_name":"Power graph analysis","score":0.48882123827934265},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.4286065697669983},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3743441104888916},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.31876033544540405},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.16107508540153503}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6774358749389648},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.569094181060791},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5026731491088867},{"id":"https://openalex.org/C106937863","wikidata":"https://www.wikidata.org/wiki/Q7236518","display_name":"Power graph analysis","level":3,"score":0.48882123827934265},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.4286065697669983},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3743441104888916},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.31876033544540405},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.16107508540153503},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm58861.2023.10385857","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm58861.2023.10385857","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null},{"id":"https://openalex.org/F4320334111","display_name":"Innovation Fund","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":68,"referenced_works":["https://openalex.org/W1497886497","https://openalex.org/W2122457251","https://openalex.org/W2167868121","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2314945771","https://openalex.org/W2526511911","https://openalex.org/W2896457183","https://openalex.org/W2899663614","https://openalex.org/W2921224201","https://openalex.org/W2951659295","https://openalex.org/W2962919115","https://openalex.org/W2963446712","https://openalex.org/W2964051675","https://openalex.org/W2964321699","https://openalex.org/W2990045899","https://openalex.org/W2998702685","https://openalex.org/W3000577518","https://openalex.org/W3042770487","https://openalex.org/W3092867907","https://openalex.org/W3094309150","https://openalex.org/W3099375322","https://openalex.org/W3133264589","https://openalex.org/W3169752883","https://openalex.org/W3178330258","https://openalex.org/W3183761761","https://openalex.org/W3197341760","https://openalex.org/W3199008037","https://openalex.org/W3211394146","https://openalex.org/W3214096813","https://openalex.org/W4205997088","https://openalex.org/W4226208698","https://openalex.org/W4281706128","https://openalex.org/W4286382578","https://openalex.org/W4287123803","https://openalex.org/W4288089799","https://openalex.org/W4288335984","https://openalex.org/W4294558607","https://openalex.org/W4295728955","https://openalex.org/W4306295096","https://openalex.org/W4381051478","https://openalex.org/W4385245566","https://openalex.org/W6720006811","https://openalex.org/W6726873649","https://openalex.org/W6738964360","https://openalex.org/W6739901393","https://openalex.org/W6753331806","https://openalex.org/W6754929296","https://openalex.org/W6755207826","https://openalex.org/W6755977528","https://openalex.org/W6757817989","https://openalex.org/W6760045743","https://openalex.org/W6761472960","https://openalex.org/W6761665040","https://openalex.org/W6763882751","https://openalex.org/W6769627184","https://openalex.org/W6772776185","https://openalex.org/W6779733120","https://openalex.org/W6779961489","https://openalex.org/W6784460448","https://openalex.org/W6784741312","https://openalex.org/W6787995345","https://openalex.org/W6796801894","https://openalex.org/W6804049574","https://openalex.org/W6810465265","https://openalex.org/W6811246986","https://openalex.org/W6838252289","https://openalex.org/W6846041338"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4224009465","https://openalex.org/W4368755543","https://openalex.org/W4377142566","https://openalex.org/W3088104186","https://openalex.org/W1543023114","https://openalex.org/W4245709619","https://openalex.org/W85088162","https://openalex.org/W2294734161","https://openalex.org/W3081531507"],"abstract_inverted_index":{"Advanced":[0],"deep":[1],"learning":[2,52],"methods,":[3],"especially":[4],"graph":[5,46,57,61,86],"neural":[6],"networks":[7,34],"(GNNs),":[8],"are":[9],"increasingly":[10],"expected":[11],"to":[12,71],"learn":[13],"from":[14,118],"brain":[15,21,37,79,114],"functional":[16,38,80,115],"network":[17,39,116],"data":[18],"and":[19,31,75,122,127,138],"predict":[20],"disorders.":[22],"In":[23],"this":[24],"paper,":[25],"we":[26],"proposed":[27,109],"a":[28,96],"novel":[29],"Transformer":[30,43,62,92],"snowball":[32,47,58,64,85],"encoding":[33,65],"(TSEN)":[35],"for":[36,51,101],"classification,":[40],"which":[41,67,94],"introduced":[42,84],"architecture":[44],"with":[45,60],"connection":[48,59],"into":[49],"GNNs":[50],"whole-graph":[53],"representation.":[54],"TSEN":[55,82,132],"combined":[56],"by":[63,111],"layers,":[66],"enhanced":[68],"the":[69,108,128,134,139],"power":[70],"capture":[72],"multi-scale":[73],"information":[74],"global":[76],"patterns":[77,104],"of":[78],"networks.":[81],"also":[83],"convolution":[87],"as":[88],"position":[89],"embedding":[90],"in":[91],"structure,":[93],"was":[95],"simple":[97],"yet":[98],"effective":[99],"method":[100],"capturing":[102],"local":[103],"naturally.":[105],"We":[106],"evaluated":[107],"model":[110],"two":[112],"large-scale":[113],"datasets":[117],"autism":[119],"spectrum":[120],"disorder":[121,125],"major":[123],"depressive":[124],"respectively,":[126],"results":[129],"demonstrated":[130],"that":[131],"outperformed":[133],"state-of-the-art":[135],"GNN":[136,142],"models":[137],"graph-transformer":[140],"based":[141],"models.":[143]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}