{"id":"https://openalex.org/W3039131048","doi":"https://doi.org/10.1109/access.2020.3005444","title":"Efficient ResNet Model to Predict Protein-Protein Interactions With GPU Computing","display_name":"Efficient ResNet Model to Predict Protein-Protein Interactions With GPU Computing","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3039131048","doi":"https://doi.org/10.1109/access.2020.3005444","mag":"3039131048"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3005444","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3005444","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09127430.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/ielx7/6287639/8948470/09127430.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5052623756","display_name":"Shengyu Lu","orcid":"https://orcid.org/0000-0003-1389-7251"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shengyu Lu","raw_affiliation_strings":["School of Informatics, Xiamen University, Xiamen, China"],"raw_orcid":"https://orcid.org/0000-0003-1389-7251","affiliations":[{"raw_affiliation_string":"School of Informatics, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102714385","display_name":"Qingqi Hong","orcid":"https://orcid.org/0000-0002-9996-6870"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingqi Hong","raw_affiliation_strings":["School of Informatics, Xiamen University, Xiamen, China"],"raw_orcid":"https://orcid.org/0000-0002-9996-6870","affiliations":[{"raw_affiliation_string":"School of Informatics, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047225086","display_name":"Beizhan Wang","orcid":"https://orcid.org/0000-0002-2846-5411"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Beizhan Wang","raw_affiliation_strings":["School of Informatics, Xiamen University, Xiamen, China"],"raw_orcid":"https://orcid.org/0000-0002-2846-5411","affiliations":[{"raw_affiliation_string":"School of Informatics, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101406826","display_name":"Hongji Wang","orcid":"https://orcid.org/0000-0003-3235-9598"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongji Wang","raw_affiliation_strings":["School of Informatics, Xiamen University, Xiamen, China"],"raw_orcid":"https://orcid.org/0000-0003-3235-9598","affiliations":[{"raw_affiliation_string":"School of Informatics, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I191208505"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.6509,"has_fulltext":true,"cited_by_count":15,"citation_normalized_percentile":{"value":0.66586854,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"8","issue":null,"first_page":"127834","last_page":"127844"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9991999864578247,"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"}},"topics":[{"id":"https://openalex.org/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9991999864578247,"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"}},{"id":"https://openalex.org/T10044","display_name":"Protein Structure and Dynamics","score":0.9979000091552734,"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"}},{"id":"https://openalex.org/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9975000023841858,"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/computer-science","display_name":"Computer science","score":0.88282710313797},{"id":"https://openalex.org/keywords/residual-neural-network","display_name":"Residual neural network","score":0.4835178852081299},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.48062390089035034},{"id":"https://openalex.org/keywords/general-purpose-computing-on-graphics-processing-units","display_name":"General-purpose computing on graphics processing units","score":0.479645311832428},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47139766812324524},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4624185264110565},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45364922285079956},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.4272482991218567},{"id":"https://openalex.org/keywords/graphics","display_name":"Graphics","score":0.4140564203262329},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3988657593727112},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33874887228012085}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.88282710313797},{"id":"https://openalex.org/C2944601119","wikidata":"https://www.wikidata.org/wiki/Q43744058","display_name":"Residual neural network","level":3,"score":0.4835178852081299},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.48062390089035034},{"id":"https://openalex.org/C50630238","wikidata":"https://www.wikidata.org/wiki/Q971505","display_name":"General-purpose computing on graphics processing units","level":3,"score":0.479645311832428},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47139766812324524},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4624185264110565},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45364922285079956},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.4272482991218567},{"id":"https://openalex.org/C21442007","wikidata":"https://www.wikidata.org/wiki/Q1027879","display_name":"Graphics","level":2,"score":0.4140564203262329},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3988657593727112},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33874887228012085},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.3005444","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3005444","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09127430.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:622d6b15d740417aafa35b6a2bcb6df8","is_oa":true,"landing_page_url":"https://doaj.org/article/622d6b15d740417aafa35b6a2bcb6df8","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 8, Pp 127834-127844 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3005444","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3005444","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09127430.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":[{"id":"https://metadata.un.org/sdg/12","display_name":"Responsible consumption and production","score":0.5}],"awards":[{"id":"https://openalex.org/G3993335450","display_name":null,"funder_award_id":"207220180073","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5486953125","display_name":null,"funder_award_id":"207220180073","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G8792508095","display_name":null,"funder_award_id":"61502402","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3039131048.pdf","grobid_xml":"https://content.openalex.org/works/W3039131048.grobid-xml"},"referenced_works_count":69,"referenced_works":["https://openalex.org/W1598796236","https://openalex.org/W1810943226","https://openalex.org/W1893455912","https://openalex.org/W1910131649","https://openalex.org/W1924770834","https://openalex.org/W1940872118","https://openalex.org/W1982267716","https://openalex.org/W1984580598","https://openalex.org/W1985919127","https://openalex.org/W1990740967","https://openalex.org/W2085809045","https://openalex.org/W2095512461","https://openalex.org/W2097697746","https://openalex.org/W2104703176","https://openalex.org/W2120615054","https://openalex.org/W2130942839","https://openalex.org/W2159094603","https://openalex.org/W2171469118","https://openalex.org/W2176950688","https://openalex.org/W2194775991","https://openalex.org/W2249392746","https://openalex.org/W2252215182","https://openalex.org/W2410873723","https://openalex.org/W2444465431","https://openalex.org/W2465246611","https://openalex.org/W2472454274","https://openalex.org/W2506377511","https://openalex.org/W2517714857","https://openalex.org/W2547150868","https://openalex.org/W2556888587","https://openalex.org/W2558580397","https://openalex.org/W2566370974","https://openalex.org/W2615066396","https://openalex.org/W2616246685","https://openalex.org/W2617750324","https://openalex.org/W2618265628","https://openalex.org/W2626129225","https://openalex.org/W2701971652","https://openalex.org/W2780936345","https://openalex.org/W2794004073","https://openalex.org/W2800686208","https://openalex.org/W2804331675","https://openalex.org/W2841071937","https://openalex.org/W2890911678","https://openalex.org/W2904726360","https://openalex.org/W2944679105","https://openalex.org/W2951690294","https://openalex.org/W2963251476","https://openalex.org/W2963616439","https://openalex.org/W2963616706","https://openalex.org/W2963706121","https://openalex.org/W2964046515","https://openalex.org/W2964348125","https://openalex.org/W2971987084","https://openalex.org/W2999481648","https://openalex.org/W3000982932","https://openalex.org/W3026528364","https://openalex.org/W6635679246","https://openalex.org/W6638273328","https://openalex.org/W6640212811","https://openalex.org/W6640362995","https://openalex.org/W6679436768","https://openalex.org/W6687483927","https://openalex.org/W6729752019","https://openalex.org/W6732491067","https://openalex.org/W6740114376","https://openalex.org/W6753369179","https://openalex.org/W6754350045","https://openalex.org/W6767236565"],"related_works":["https://openalex.org/W3196952692","https://openalex.org/W2984708981","https://openalex.org/W2755231872","https://openalex.org/W4300939921","https://openalex.org/W4383097772","https://openalex.org/W2964350391","https://openalex.org/W2274287116","https://openalex.org/W2897517148","https://openalex.org/W2983358626","https://openalex.org/W2964137095"],"abstract_inverted_index":{"Protein-protein":[0],"interactions":[1],"(PPI)":[2],"play":[3],"an":[4,99],"important":[5],"role":[6],"in":[7,197],"the":[8,22,42,49,85,89,104,116,125,133,146,160,166,170,173,183,186,194,198,203],"cell":[9],"activities":[10,26],"of":[11,24,51,71,92,127,132,172,182,200],"organisms.":[12],"The":[13,141],"deep":[14,136],"research":[15],"about":[16],"PPI":[17,33,82,111],"can":[18,47,149,189,206],"help":[19],"humans":[20],"understand":[21],"mechanism":[23],"life":[25],"and":[27,56,66,138,153],"apply":[28],"protein":[29],"functions":[30],"better.":[31,208],"Nowadays,":[32],"prediction":[34],"algorithms":[35,62],"based":[36,102],"on":[37,103,159],"amino":[38,121],"acid":[39,122],"sequences":[40],"using":[41],"recurrent":[43],"neural":[44],"network":[45,106],"(RNN)":[46],"overcome":[48],"disadvantages":[50],"traditional":[52],"biological":[53],"experimental":[54,142],"methods":[55],"achieve":[57,190],"high":[58,151],"accuracy.":[59],"However,":[60],"these":[61],"are":[63],"usually":[64],"time-consuming":[65],"cannot":[67],"take":[68],"full":[69],"advantage":[70],"graphics":[72],"processing":[73],"units":[74],"(GPU)":[75],"with":[76,135,165],"efficient":[77,100],"computation":[78],"performance":[79],"to":[80,109,119,193],"accelerate":[81],"prediction,":[83],"because":[84],"RNN":[86],"model":[87,108],"considers":[88],"time":[90,156],"series":[91],"sequences.":[93],"In":[94],"this":[95],"paper,":[96],"we":[97],"propose":[98],"algorithm":[101,114,148,175,188,205],"residual":[105],"(ResNet)":[107],"predict":[110],"(ResPPI).":[112],"Our":[113],"uses":[115],"embedding":[117],"method":[118],"represent":[120],"sequences,":[123],"combining":[124],"advantages":[126],"powerful":[128],"feature":[129],"extraction":[130],"capabilities":[131],"ResNet":[134],"layers":[137],"GPU":[139,162],"performance.":[140],"results":[143],"show":[144],"that":[145,181],"ResPPI":[147,174,187,204],"ensure":[150],"accuracy":[152,192],"reduce":[154],"training":[155],"greatly.":[157],"Based":[158],"ordinary":[161],"device,":[163],"compared":[164],"state-of-the-art":[167],"LSTM":[168],"model,":[169],"speed":[171],"is":[176],"five":[177],"times":[178],"faster":[179],"than":[180],"LSTM,":[184],"whereas":[185],"similar":[191],"LSTM.":[195],"Besides,":[196],"case":[199],"unbalanced":[201],"datasets,":[202],"perform":[207]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
