{"id":"https://openalex.org/W7126096752","doi":"https://doi.org/10.1109/bibm66473.2025.11357085","title":"AGFN: A Multi-Source Data Fusion Transformer Framework for Multi-Trait Genetic Prediction in Oyster Aquaculture","display_name":"AGFN: A Multi-Source Data Fusion Transformer Framework for Multi-Trait Genetic Prediction in Oyster Aquaculture","publication_year":2025,"publication_date":"2025-12-15","ids":{"openalex":"https://openalex.org/W7126096752","doi":"https://doi.org/10.1109/bibm66473.2025.11357085"},"language":null,"primary_location":{"id":"doi:10.1109/bibm66473.2025.11357085","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11357085","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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/A5124287743","display_name":"Meng Huang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Meng Huang","raw_affiliation_strings":["School of Computer Engineering, Jiangsu Ocean University,Lianyungang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Engineering, Jiangsu Ocean University,Lianyungang,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124174402","display_name":"Yu He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu He","raw_affiliation_strings":["School of Computer Engineering, Jiangsu Ocean University,Lianyungang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Engineering, Jiangsu Ocean University,Lianyungang,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101624436","display_name":"Yiheng Zhang","orcid":"https://orcid.org/0009-0002-2426-0838"},"institutions":[{"id":"https://openalex.org/I163340411","display_name":"Hohai University","ror":"https://ror.org/01wd4xt90","country_code":"CN","type":"education","lineage":["https://openalex.org/I163340411"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiheng Zhang","raw_affiliation_strings":["School of Earth Sciences and Engineering Hohai University,Nanjing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Earth Sciences and Engineering Hohai University,Nanjing,China","institution_ids":["https://openalex.org/I163340411"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124156802","display_name":"Ming Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ming Li","raw_affiliation_strings":["School of Computer Engineering, Jiangsu Ocean University,Lianyungang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Engineering, Jiangsu Ocean University,Lianyungang,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124180275","display_name":"Kang Mei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kang Mei","raw_affiliation_strings":["School of Computer Engineering, Jiangsu Ocean University,Lianyungang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Engineering, Jiangsu Ocean University,Lianyungang,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124203590","display_name":"Jian Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jian Zhang","raw_affiliation_strings":["School of Computer Engineering, Jiangsu Ocean University,Lianyungang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Engineering, Jiangsu Ocean University,Lianyungang,China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124211259","display_name":"Heng Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Heng Zhang","raw_affiliation_strings":["School of Computer Engineering, Jiangsu Ocean University,Lianyungang,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Engineering, Jiangsu Ocean University,Lianyungang,China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"6865","last_page":"6872"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11088","display_name":"Marine Bivalve and Aquaculture Studies","score":0.3249000012874603,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"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/T11088","display_name":"Marine Bivalve and Aquaculture Studies","score":0.3249000012874603,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"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/T10594","display_name":"Genetic and phenotypic traits in livestock","score":0.22830000519752502,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"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/T10261","display_name":"Genetic Associations and Epidemiology","score":0.06939999759197235,"subfield":{"id":"https://openalex.org/subfields/1311","display_name":"Genetics"},"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/principal-component-analysis","display_name":"Principal component analysis","score":0.4553999900817871},{"id":"https://openalex.org/keywords/inbreeding","display_name":"Inbreeding","score":0.4291999936103821},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.41690000891685486},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.3513000011444092},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.321399986743927},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.31690001487731934},{"id":"https://openalex.org/keywords/imputation","display_name":"Imputation (statistics)","score":0.31450000405311584},{"id":"https://openalex.org/keywords/genetic-association","display_name":"Genetic association","score":0.3046000003814697}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49000000953674316},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.48750001192092896},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.4553999900817871},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4496000111103058},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4390000104904175},{"id":"https://openalex.org/C2777782036","wikidata":"https://www.wikidata.org/wiki/Q38978","display_name":"Inbreeding","level":3,"score":0.4291999936103821},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.41690000891685486},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.3513000011444092},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.32670000195503235},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.321399986743927},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.31690001487731934},{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.31450000405311584},{"id":"https://openalex.org/C186413461","wikidata":"https://www.wikidata.org/wiki/Q744727","display_name":"Genetic association","level":5,"score":0.3046000003814697},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.3043999969959259},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.29089999198913574},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.2874999940395355},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2808000147342682},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.2782999873161316},{"id":"https://openalex.org/C2776364969","wikidata":"https://www.wikidata.org/wiki/Q107411","display_name":"Oyster","level":2,"score":0.27320000529289246},{"id":"https://openalex.org/C201797286","wikidata":"https://www.wikidata.org/wiki/Q4914986","display_name":"Biological data","level":2,"score":0.27090001106262207},{"id":"https://openalex.org/C86909935","wikidata":"https://www.wikidata.org/wiki/Q188989","display_name":"Aquaculture","level":3,"score":0.2612999975681305},{"id":"https://openalex.org/C106208931","wikidata":"https://www.wikidata.org/wiki/Q1098876","display_name":"Genome-wide association study","level":5,"score":0.25619998574256897},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.2549999952316284}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm66473.2025.11357085","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm66473.2025.11357085","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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":26,"referenced_works":["https://openalex.org/W2061187129","https://openalex.org/W2064013109","https://openalex.org/W2295598076","https://openalex.org/W2344526199","https://openalex.org/W2796468311","https://openalex.org/W2799606843","https://openalex.org/W2890596376","https://openalex.org/W2912579174","https://openalex.org/W3050571019","https://openalex.org/W3136884885","https://openalex.org/W3202451896","https://openalex.org/W4289315862","https://openalex.org/W4308775252","https://openalex.org/W4367175106","https://openalex.org/W4376139821","https://openalex.org/W4383264661","https://openalex.org/W4385201870","https://openalex.org/W4385417243","https://openalex.org/W4385781686","https://openalex.org/W4388105985","https://openalex.org/W4389452928","https://openalex.org/W4392562517","https://openalex.org/W4399128848","https://openalex.org/W4403585866","https://openalex.org/W4404421433","https://openalex.org/W4408995517"],"related_works":[],"abstract_inverted_index":{"Oyster":[0],"weight":[1],"and":[2,18,37,83,87,102,125,166,192,223,241],"morphological":[3],"traits":[4,36,64],"are":[5,25,243],"core":[6],"economic":[7],"indicators":[8],"in":[9,65,161,172,216],"aquaculture,":[10],"with":[11,131],"complex":[12],"phenotypes":[13],"regulated":[14],"by":[15,27],"polygenic":[16],"networks":[17],"environmental":[19],"interactions.":[20],"Current":[21],"single-trait":[22],"prediction":[23,138,204,215],"models":[24],"limited":[26],"their":[28],"inability":[29],"to":[30,61,119,134,158,178,203],"account":[31],"for":[32,212,231],"genetic":[33,214],"correlations":[34],"between":[35],"the":[38,114,127,154,179,188,219],"implicit":[39],"effects":[40],"of":[41,122,156],"pedigree":[42,84,123,189],"structures.":[43],"In":[44],"this":[45],"work,":[46],"we":[47,92,112],"propose":[48],"a":[49,136,209,224],"novel":[50,210],"multisource":[51],"data":[52,124,190,221,242],"fusion":[53,222],"Transformer":[54],"framework,":[55],"Aquaculture":[56],"Genetic":[57],"Fusion":[58],"Network":[59],"(AGFN),":[60],"predict":[62],"multiple":[63],"oyster":[66],"aquaculture.":[67],"The":[68],"proposed":[69],"AGFN":[70,144],"synergistically":[71],"integrates":[72],"genotypic":[73],"(Single":[74],"Nucleotide":[75],"Polymorphism,":[76],"SNP),":[77],"multi-phenotypic":[78],"(six":[79],"economically":[80],"important":[81],"traits),":[82],"(kinship":[85],"matrix":[86],"inbreeding":[88],"coefficient)":[89],"data.":[90],"Specifically,":[91],"combine":[93,126],"biological":[94],"prior":[95],"knowledge":[96,238],"from":[97],"genome-wide":[98],"association":[99],"studies":[100,185],"(GWAS)":[101],"latent":[103],"interaction":[104],"testing":[105],"(LIT)":[106],"analysis":[107,117],"through":[108,218,236],"SNP":[109,193],"embedding.":[110],"Then,":[111],"apply":[113],"principal":[115],"component":[116],"(PCA)":[118],"reduce":[120],"dimensionality":[121],"multi-head":[128],"self-attention":[129,225],"mechanism":[130,226],"residual":[132],"network":[133],"construct":[135],"multi-task":[137],"framework.":[139],"Experimental":[140],"results":[141],"demonstrate":[142],"that":[143,187],"outperforms":[145],"six":[146],"state-of-the-art":[147],"methods":[148],"across":[149],"all":[150],"evaluated":[151],"traits,":[152],"achieving":[153],"improvements":[155],"up":[157],"15":[159],"%":[160],"Mean":[162],"Squared":[163],"Error":[164],"(MSE)":[165],"<tex":[167,197],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[168,198],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\mathbf{1":[169],"2}":[170],"\\boldsymbol{\\%}$</tex>":[171],"Pearson":[173],"Correlation":[174],"Coefficient":[175],"(PCC)":[176],"compared":[177],"best":[180],"baseline":[181],"model.":[182],"Systematic":[183],"ablation":[184],"validate":[186],"integration":[191],"embedding":[194],"module":[195],"contribute":[196],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\sim":[199],"9":[200],"\\%$</tex>":[201],"enhancements":[202],"accuracy.":[205],"This":[206],"work":[207],"establishes":[208],"paradigm":[211],"multi-trait":[213],"aquaculture":[217],"multi-source":[220],"construction,":[227],"offering":[228],"substantial":[229],"potential":[230],"accelerating":[232],"precision":[233],"breeding":[234],"programs":[235],"interdisciplinary":[237],"innovation.":[239],"Codes":[240],"available":[244],"at":[245],"https://github.com/heyu02292030-star/AGFNcode.":[246]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-01-30T00:00:00"}