{"id":"https://openalex.org/W4226445327","doi":"https://doi.org/10.1109/access.2022.3171341","title":"Predicting Phenotypes From High-Dimensional Genomes Using Gradient Boosting Decision Trees","display_name":"Predicting Phenotypes From High-Dimensional Genomes Using Gradient Boosting Decision Trees","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4226445327","doi":"https://doi.org/10.1109/access.2022.3171341"},"language":"en","primary_location":{"id":"doi:10.1109/access.2022.3171341","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3171341","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09765485.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09765485.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5049064091","display_name":"Tingxi Yu","orcid":"https://orcid.org/0000-0002-1844-3956"},"institutions":[{"id":"https://openalex.org/I119868032","display_name":"Shanxi Agricultural University","ror":"https://ror.org/05e9f5362","country_code":"CN","type":"education","lineage":["https://openalex.org/I119868032"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tingxi Yu","raw_affiliation_strings":["College of Software, Shanxi Agricultural University, Taigu, Shanxi, China","ORCiD"],"raw_orcid":"https://orcid.org/0000-0002-1844-3956","affiliations":[{"raw_affiliation_string":"College of Software, Shanxi Agricultural University, Taigu, Shanxi, China","institution_ids":["https://openalex.org/I119868032"]},{"raw_affiliation_string":"ORCiD","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100335909","display_name":"Li Wang","orcid":"https://orcid.org/0000-0001-9917-6345"},"institutions":[{"id":"https://openalex.org/I119868032","display_name":"Shanxi Agricultural University","ror":"https://ror.org/05e9f5362","country_code":"CN","type":"education","lineage":["https://openalex.org/I119868032"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Wang","raw_affiliation_strings":["College of Software, Shanxi Agricultural University, Taigu, Shanxi, China","ORCiD"],"raw_orcid":"https://orcid.org/0000-0001-9917-6345","affiliations":[{"raw_affiliation_string":"College of Software, Shanxi Agricultural University, Taigu, Shanxi, China","institution_ids":["https://openalex.org/I119868032"]},{"raw_affiliation_string":"ORCiD","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031533403","display_name":"Wuping Zhang","orcid":"https://orcid.org/0000-0002-4354-4409"},"institutions":[{"id":"https://openalex.org/I119868032","display_name":"Shanxi Agricultural University","ror":"https://ror.org/05e9f5362","country_code":"CN","type":"education","lineage":["https://openalex.org/I119868032"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wuping Zhang","raw_affiliation_strings":["College of Software, Shanxi Agricultural University, Taigu, Shanxi, China","ORCiD"],"raw_orcid":"https://orcid.org/0000-0002-4354-4409","affiliations":[{"raw_affiliation_string":"College of Software, Shanxi Agricultural University, Taigu, Shanxi, China","institution_ids":["https://openalex.org/I119868032"]},{"raw_affiliation_string":"ORCiD","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005349434","display_name":"Guofang Xing","orcid":"https://orcid.org/0000-0002-4834-6209"},"institutions":[{"id":"https://openalex.org/I119868032","display_name":"Shanxi Agricultural University","ror":"https://ror.org/05e9f5362","country_code":"CN","type":"education","lineage":["https://openalex.org/I119868032"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guofang Xing","raw_affiliation_strings":["College of Agriculture, Shanxi Agricultural University, Taigu, Shanxi, China","ORCiD"],"raw_orcid":"https://orcid.org/0000-0002-4834-6209","affiliations":[{"raw_affiliation_string":"College of Agriculture, Shanxi Agricultural University, Taigu, Shanxi, China","institution_ids":["https://openalex.org/I119868032"]},{"raw_affiliation_string":"ORCiD","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102291570","display_name":"Jiwan Han","orcid":null},"institutions":[{"id":"https://openalex.org/I119868032","display_name":"Shanxi Agricultural University","ror":"https://ror.org/05e9f5362","country_code":"CN","type":"education","lineage":["https://openalex.org/I119868032"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiwan Han","raw_affiliation_strings":["College of Software, Shanxi Agricultural University, Taigu, Shanxi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Software, Shanxi Agricultural University, Taigu, Shanxi, China","institution_ids":["https://openalex.org/I119868032"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101951917","display_name":"Fuzhong Li","orcid":"https://orcid.org/0000-0001-9695-8309"},"institutions":[{"id":"https://openalex.org/I119868032","display_name":"Shanxi Agricultural University","ror":"https://ror.org/05e9f5362","country_code":"CN","type":"education","lineage":["https://openalex.org/I119868032"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fuzhong Li","raw_affiliation_strings":["College of Software, Shanxi Agricultural University, Taigu, Shanxi, China","ORCiD"],"raw_orcid":"https://orcid.org/0000-0001-9695-8309","affiliations":[{"raw_affiliation_string":"College of Software, Shanxi Agricultural University, Taigu, Shanxi, China","institution_ids":["https://openalex.org/I119868032"]},{"raw_affiliation_string":"ORCiD","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084329953","display_name":"Chunqing Cao","orcid":"https://orcid.org/0000-0002-1717-2090"},"institutions":[{"id":"https://openalex.org/I119868032","display_name":"Shanxi Agricultural University","ror":"https://ror.org/05e9f5362","country_code":"CN","type":"education","lineage":["https://openalex.org/I119868032"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunqing Cao","raw_affiliation_strings":["College of Software, Shanxi Agricultural University, Taigu, Shanxi, China","ORCiD"],"raw_orcid":"https://orcid.org/0000-0002-1717-2090","affiliations":[{"raw_affiliation_string":"College of Software, Shanxi Agricultural University, Taigu, Shanxi, China","institution_ids":["https://openalex.org/I119868032"]},{"raw_affiliation_string":"ORCiD","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I119868032"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.4415,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.82409003,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"10","issue":null,"first_page":"48126","last_page":"48140"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10594","display_name":"Genetic and phenotypic traits in livestock","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10594","display_name":"Genetic and phenotypic traits in livestock","score":0.9998999834060669,"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/T11468","display_name":"Genetic Mapping and Diversity in Plants and Animals","score":0.998199999332428,"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/T11229","display_name":"Genetics and Plant Breeding","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6548121571540833},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5704217553138733},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5288708806037903},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.5236461162567139},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5023045539855957},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.44489237666130066},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.4383324682712555},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.43147820234298706},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2519526183605194}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6548121571540833},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5704217553138733},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5288708806037903},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.5236461162567139},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5023045539855957},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.44489237666130066},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.4383324682712555},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.43147820234298706},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2519526183605194},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2022.3171341","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3171341","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09765485.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:2bcd4fa89c6b4b668b2e46a332d482ee","is_oa":true,"landing_page_url":"https://doaj.org/article/2bcd4fa89c6b4b668b2e46a332d482ee","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 10, Pp 48126-48140 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2022.3171341","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3171341","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09765485.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320335577","display_name":"Major Research Plan","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4226445327.pdf","grobid_xml":"https://content.openalex.org/works/W4226445327.grobid-xml"},"referenced_works_count":56,"referenced_works":["https://openalex.org/W30651129","https://openalex.org/W1019830208","https://openalex.org/W1180844366","https://openalex.org/W1505191356","https://openalex.org/W1605688901","https://openalex.org/W1928998639","https://openalex.org/W1988538876","https://openalex.org/W1997751006","https://openalex.org/W2019961888","https://openalex.org/W2034846276","https://openalex.org/W2041000916","https://openalex.org/W2050029156","https://openalex.org/W2064013109","https://openalex.org/W2067715889","https://openalex.org/W2075417464","https://openalex.org/W2125223451","https://openalex.org/W2142220815","https://openalex.org/W2160608514","https://openalex.org/W2215288704","https://openalex.org/W2262801583","https://openalex.org/W2268306343","https://openalex.org/W2439742035","https://openalex.org/W2462855334","https://openalex.org/W2467418041","https://openalex.org/W2474077935","https://openalex.org/W2478484820","https://openalex.org/W2514173981","https://openalex.org/W2539922013","https://openalex.org/W2760544538","https://openalex.org/W2781702232","https://openalex.org/W2785490704","https://openalex.org/W2808363286","https://openalex.org/W2810433267","https://openalex.org/W2810986024","https://openalex.org/W2887039631","https://openalex.org/W2906431954","https://openalex.org/W2923682152","https://openalex.org/W2932347607","https://openalex.org/W2935703330","https://openalex.org/W2962800573","https://openalex.org/W2962928958","https://openalex.org/W2983803089","https://openalex.org/W3000045279","https://openalex.org/W3000982932","https://openalex.org/W3002262829","https://openalex.org/W3009346076","https://openalex.org/W3036780692","https://openalex.org/W3102943483","https://openalex.org/W3111396840","https://openalex.org/W3118630218","https://openalex.org/W3200488575","https://openalex.org/W3206378387","https://openalex.org/W3208289863","https://openalex.org/W4233341945","https://openalex.org/W4247498554","https://openalex.org/W6747869919"],"related_works":["https://openalex.org/W2125652721","https://openalex.org/W1540371141","https://openalex.org/W4231274751","https://openalex.org/W1549363203","https://openalex.org/W2154063878","https://openalex.org/W2556012038","https://openalex.org/W1489772951","https://openalex.org/W3108206494","https://openalex.org/W2739726746","https://openalex.org/W4242380336"],"abstract_inverted_index":{"xsxsGenomic":[0],"selection":[1,299],"(GS)":[2],"is":[3,191,203,219],"an":[4],"emerging":[5],"technique":[6],"for":[7,241],"predicting":[8],"unknown":[9],"phenotypes":[10],"using":[11,90],"genome-wide":[12],"marker":[13,302],"coverage,":[14],"allowing":[15],"the":[16,42,48,54,79,91,97,119,134,156,161,165,170,174,183,187,207,212,216,224,229,234,238,244,260,277,282,284,288,290,294,297,309,313],"use":[17,65],"of":[18,45,50,81,121,133,151,158,164,173,186,215,223,233,269,279,286,293,300,304,312],"efficient":[19],"computational":[20,171,213],"models":[21,76,140,190,273],"to":[22,41,69,77,117,124,195,252],"select":[23,125,253],"individuals":[24,126,254],"with":[25,100,127,255],"high":[26,128,256],"phenotypic":[27,82,129,257],"values":[28,83,258],"as":[29],"candidate":[30],"breeding":[31,39],"populations.":[32],"However,":[33],"GS":[34,93,105],"remains":[35],"challenging":[36],"inefficient":[37],"crop":[38],"due":[40],"limited":[43],"size":[44,306],"training":[46],"populations,":[47],"nature":[49],"genotype-environment":[51],"interactions,":[52],"and":[53,95,142,193,199,211,262,271,281],"complex":[55],"interaction":[56],"patterns":[57],"between":[58],"molecular":[59],"markers.":[60,86],"In":[61],"this":[62],"study,":[63],"we":[64],"ensemble":[66],"learning":[67],"algorithms":[68],"construct":[70],"gradient":[71],"boosted":[72],"decision":[73],"tree":[74],"(GBDT)":[75],"achieve":[78],"prediction":[80,162,184,201,231,267,291,310],"from":[84],"genotypic":[85],"We":[87],"trained":[88],"GBDT":[89,208,217,245,270],"wheat":[92],"dataset":[94],"compared":[96],"predictive":[98],"performance":[99,185,232,311],"six":[101],"other":[102],"widely":[103],"used":[104,116],"models.":[106,264,314],"The":[107,131,266],"mean":[108],"normalized":[109],"discounted":[110],"cumulative":[111],"gain":[112],"(MNDCG)":[113],"method":[114],"was":[115,237,274],"evaluate":[118],"ability":[120,251],"each":[122],"model":[123,167,175,209,218,236,246],"values.":[130],"results":[132],"study":[135],"show":[136],"that:":[137],"(1)":[138],"Bayesian":[139,166,189,225,263],"converge":[141],"reach":[143],"a":[144,148,196,249],"steady-state":[145],"only":[146],"when":[147],"sufficient":[149],"number":[150,157,285],"iterations":[152,159,180],"are":[153,181],"set.":[154],"As":[155],"increases,":[160,168],"accuracy":[163,202,268,292],"but":[169,240],"efficiency":[172,214],"decreases":[176],"significantly.":[177],"When":[178],"200,000":[179],"performed,":[182],"five":[188],"similar":[192],"converges":[194],"smooth":[197],"state,":[198],"their":[200],"7.60%":[204],"better":[205],"than":[206,259],"overall,":[210],"70":[220],"times":[221],"that":[222],"model.":[226],"(2)":[227],"Overall,":[228],"overall":[230],"RRBLUP":[235,261,272],"best,":[239],"some":[242],"traits,":[243],"still":[247],"had":[248],"higher":[250,283,289],"(3)":[265],"influenced":[275],"by":[276],"subset":[278],"markers,":[280],"markers":[287],"models,":[295],"so":[296],"reasonable":[298],"genetic":[301],"data":[303],"appropriate":[305],"could":[307],"improve":[308]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}