{"id":"https://openalex.org/W2104270782","doi":"https://doi.org/10.1109/ijcnn.2008.4634050","title":"COX-2 activity prediction in Chinese medicine using neural network based ensemble learning methods","display_name":"COX-2 activity prediction in Chinese medicine using neural network based ensemble learning methods","publication_year":2008,"publication_date":"2008-06-01","ids":{"openalex":"https://openalex.org/W2104270782","doi":"https://doi.org/10.1109/ijcnn.2008.4634050","mag":"2104270782"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2008.4634050","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2008.4634050","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)","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/A5100318412","display_name":"Wei Li","orcid":"https://orcid.org/0000-0003-2543-2558"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wei Li","raw_affiliation_strings":["State Key Laboratory on Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science, Tsinghua University, Beijing, China","Department of Computer Science, Tsinghua University, Beijing,"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory on Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Computer Science, Tsinghua University, Beijing,","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100940879","display_name":"Yannan Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yannan Zhao","raw_affiliation_strings":["State Key Laboratory on Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science, Tsinghua University, Beijing, China","Department of Computer Science, Tsinghua University, Beijing,"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory on Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Computer Science, Tsinghua University, Beijing,","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073169805","display_name":"Yixu Song","orcid":"https://orcid.org/0000-0002-3477-4886"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yixu Song","raw_affiliation_strings":["State Key Laboratory on Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science, Tsinghua University, Beijing, China","Department of Computer Science, Tsinghua University, Beijing,"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory on Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Computer Science, Tsinghua University, Beijing,","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103364416","display_name":"Zehong Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zehong Yang","raw_affiliation_strings":["State Key Laboratory on Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science, Tsinghua University, Beijing, China","Department of Computer Science, Tsinghua University, Beijing,"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory on Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Department of Computer Science, Tsinghua University, Beijing,","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100318412"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12367627,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"1","issue":null,"first_page":"1853","last_page":"1858"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9987999796867371,"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"}},"topics":[{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9987999796867371,"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/T11709","display_name":"Traditional Chinese Medicine Analysis","score":0.9739000201225281,"subfield":{"id":"https://openalex.org/subfields/2707","display_name":"Complementary and alternative medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10836","display_name":"Metabolomics and Mass Spectrometry Studies","score":0.9412999749183655,"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/boosting","display_name":"Boosting (machine learning)","score":0.8398422598838806},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7297474145889282},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7158008813858032},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6825088262557983},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.6550813317298889},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6130601167678833},{"id":"https://openalex.org/keywords/quantitative-structure\u2013activity-relationship","display_name":"Quantitative structure\u2013activity relationship","score":0.6032226085662842},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.6023848652839661},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.5802029371261597},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.4950641691684723},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.46416595578193665},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17702075839042664},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.12408262491226196}],"concepts":[{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.8398422598838806},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7297474145889282},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7158008813858032},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6825088262557983},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.6550813317298889},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6130601167678833},{"id":"https://openalex.org/C164126121","wikidata":"https://www.wikidata.org/wiki/Q766383","display_name":"Quantitative structure\u2013activity relationship","level":2,"score":0.6032226085662842},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6023848652839661},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.5802029371261597},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.4950641691684723},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.46416595578193665},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17702075839042664},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12408262491226196}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2008.4634050","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2008.4634050","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W132373643","https://openalex.org/W164621462","https://openalex.org/W421463624","https://openalex.org/W1966280301","https://openalex.org/W1977405994","https://openalex.org/W1988790447","https://openalex.org/W2010852340","https://openalex.org/W2032389990","https://openalex.org/W2099897773","https://openalex.org/W2102831150","https://openalex.org/W2112076978","https://openalex.org/W2151269043","https://openalex.org/W2157124852","https://openalex.org/W2163646378","https://openalex.org/W2164598857","https://openalex.org/W2164921999","https://openalex.org/W2318794083","https://openalex.org/W2350288754","https://openalex.org/W2911964244","https://openalex.org/W3106889297","https://openalex.org/W6606774046","https://openalex.org/W6676769703","https://openalex.org/W7000324425"],"related_works":["https://openalex.org/W2967733078","https://openalex.org/W3204430031","https://openalex.org/W3137904399","https://openalex.org/W4310492845","https://openalex.org/W2885778889","https://openalex.org/W4310224730","https://openalex.org/W2766514146","https://openalex.org/W4289703016","https://openalex.org/W2885516856","https://openalex.org/W4296079469"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"neural":[3,38],"network":[4],"based":[5,69],"ensemble":[6,27],"learning":[7,28],"methods":[8],"are":[9,35,52],"introduced":[10],"in":[11,17,57],"predicting":[12],"activities":[13],"of":[14,61,74],"COX-2":[15],"inhibitors":[16],"Chinese":[18,62],"medicine":[19,63],"Quantitative":[20],"Structure-Activity":[21],"Relationship":[22],"(QSAR)":[23],"research.":[24],"Three":[25],"different":[26],"methods:":[29],"bagging,":[30],"boosting":[31],"and":[32,54],"random":[33],"subspace":[34],"tested":[36],"using":[37],"networks":[39],"as":[40],"basic":[41],"regression":[42],"rules.":[43],"Experiments":[44],"show":[45],"that":[46],"all":[47],"three":[48],"methods,":[49],"especially":[50],"boosting,":[51],"fast":[53],"effective":[55],"ways":[56],"the":[58],"activity":[59],"prediction":[60],"QSAR":[64],"research,":[65],"which":[66],"is":[67],"generally":[68],"on":[70],"a":[71],"small":[72],"amount":[73],"training":[75],"samples.":[76]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}