{"id":"https://openalex.org/W2610646689","doi":"https://doi.org/10.1021/acs.jcim.7b00244","title":"Deep Learning Based Regression and Multiclass Models for Acute Oral Toxicity Prediction with Automatic Chemical Feature Extraction","display_name":"Deep Learning Based Regression and Multiclass Models for Acute Oral Toxicity Prediction with Automatic Chemical Feature Extraction","publication_year":2017,"publication_date":"2017-10-11","ids":{"openalex":"https://openalex.org/W2610646689","doi":"https://doi.org/10.1021/acs.jcim.7b00244","mag":"2610646689","pmid":"https://pubmed.ncbi.nlm.nih.gov/29019671"},"language":"en","primary_location":{"id":"doi:10.1021/acs.jcim.7b00244","is_oa":false,"landing_page_url":"https://doi.org/10.1021/acs.jcim.7b00244","pdf_url":null,"source":{"id":"https://openalex.org/S167262187","display_name":"Journal of Chemical Information and Modeling","issn_l":"1549-9596","issn":["1549-9596","1549-960X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320006","host_organization_name":"American Chemical Society","host_organization_lineage":["https://openalex.org/P4310320006"],"host_organization_lineage_names":["American Chemical Society"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Chemical Information and Modeling","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5004269850","display_name":"Youjun Xu","orcid":"https://orcid.org/0000-0002-3086-9781"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]},{"id":"https://openalex.org/I4210116048","display_name":"Beijing National Laboratory for Molecular Sciences","ror":"https://ror.org/02601yx74","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210116048"]},{"id":"https://openalex.org/I4210160507","display_name":"Center for Life Sciences","ror":"https://ror.org/05kje8j93","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570","https://openalex.org/I4210160507","https://openalex.org/I99065089"]},{"id":"https://openalex.org/I4391768210","display_name":"State Key Laboratory for Structural Chemistry of Unstable and Stable Species","ror":"https://ror.org/03mw4pt79","country_code":null,"type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210155088","https://openalex.org/I4391768210"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Youjun Xu","raw_affiliation_strings":["Center for Quantitative Biology, Academy for Advanced Interdisciplinary\rStudies, \u2021Beijing National Laboratory for Molecular Sciences, State Key Laboratory\rfor Structural Chemistry of Unstable and Stable Species, College of\rChemistry and Molecular Engineering, and \u00b6Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Quantitative Biology, Academy for Advanced Interdisciplinary\rStudies, \u2021Beijing National Laboratory for Molecular Sciences, State Key Laboratory\rfor Structural Chemistry of Unstable and Stable Species, College of\rChemistry and Molecular Engineering, and \u00b6Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China","institution_ids":["https://openalex.org/I20231570","https://openalex.org/I4210116048","https://openalex.org/I4210160507","https://openalex.org/I4391768210"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047704083","display_name":"Jianfeng Pei","orcid":"https://orcid.org/0000-0002-8482-1185"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]},{"id":"https://openalex.org/I4210116048","display_name":"Beijing National Laboratory for Molecular Sciences","ror":"https://ror.org/02601yx74","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210116048"]},{"id":"https://openalex.org/I4210160507","display_name":"Center for Life Sciences","ror":"https://ror.org/05kje8j93","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570","https://openalex.org/I4210160507","https://openalex.org/I99065089"]},{"id":"https://openalex.org/I4391768210","display_name":"State Key Laboratory for Structural Chemistry of Unstable and Stable Species","ror":"https://ror.org/03mw4pt79","country_code":null,"type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210155088","https://openalex.org/I4391768210"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jianfeng Pei","raw_affiliation_strings":["Center for Quantitative Biology, Academy for Advanced Interdisciplinary\rStudies, \u2021Beijing National Laboratory for Molecular Sciences, State Key Laboratory\rfor Structural Chemistry of Unstable and Stable Species, College of\rChemistry and Molecular Engineering, and \u00b6Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China"],"raw_orcid":"https://orcid.org/0000-0002-8482-1185","affiliations":[{"raw_affiliation_string":"Center for Quantitative Biology, Academy for Advanced Interdisciplinary\rStudies, \u2021Beijing National Laboratory for Molecular Sciences, State Key Laboratory\rfor Structural Chemistry of Unstable and Stable Species, College of\rChemistry and Molecular Engineering, and \u00b6Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China","institution_ids":["https://openalex.org/I20231570","https://openalex.org/I4210116048","https://openalex.org/I4210160507","https://openalex.org/I4391768210"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064049271","display_name":"Luhua Lai","orcid":"https://orcid.org/0000-0002-8343-7587"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]},{"id":"https://openalex.org/I4210116048","display_name":"Beijing National Laboratory for Molecular Sciences","ror":"https://ror.org/02601yx74","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210116048"]},{"id":"https://openalex.org/I4210160507","display_name":"Center for Life Sciences","ror":"https://ror.org/05kje8j93","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570","https://openalex.org/I4210160507","https://openalex.org/I99065089"]},{"id":"https://openalex.org/I4391768210","display_name":"State Key Laboratory for Structural Chemistry of Unstable and Stable Species","ror":"https://ror.org/03mw4pt79","country_code":null,"type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210155088","https://openalex.org/I4391768210"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Luhua Lai","raw_affiliation_strings":["Center for Quantitative Biology, Academy for Advanced Interdisciplinary\rStudies, \u2021Beijing National Laboratory for Molecular Sciences, State Key Laboratory\rfor Structural Chemistry of Unstable and Stable Species, College of\rChemistry and Molecular Engineering, and \u00b6Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China"],"raw_orcid":"https://orcid.org/0000-0002-8343-7587","affiliations":[{"raw_affiliation_string":"Center for Quantitative Biology, Academy for Advanced Interdisciplinary\rStudies, \u2021Beijing National Laboratory for Molecular Sciences, State Key Laboratory\rfor Structural Chemistry of Unstable and Stable Species, College of\rChemistry and Molecular Engineering, and \u00b6Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China","institution_ids":["https://openalex.org/I20231570","https://openalex.org/I4210116048","https://openalex.org/I4210160507","https://openalex.org/I4391768210"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5047704083","https://openalex.org/A5064049271"],"corresponding_institution_ids":["https://openalex.org/I20231570","https://openalex.org/I4210116048","https://openalex.org/I4210160507","https://openalex.org/I4391768210"],"apc_list":{"value":4500,"currency":"USD","value_usd":4500},"apc_paid":null,"fwci":18.811,"has_fulltext":false,"cited_by_count":263,"citation_normalized_percentile":{"value":0.99567557,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"57","issue":"11","first_page":"2672","last_page":"2685"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9991000294685364,"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":0.9991000294685364,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7353984117507935},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.7327483892440796},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6176792979240417},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6110197901725769},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.606910765171051},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5080316066741943},{"id":"https://openalex.org/keywords/chemical-space","display_name":"Chemical space","score":0.487301230430603},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4858660101890564},{"id":"https://openalex.org/keywords/multiclass-classification","display_name":"Multiclass classification","score":0.438648521900177},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.435477614402771},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43545955419540405},{"id":"https://openalex.org/keywords/cross-validation","display_name":"Cross-validation","score":0.4274723529815674},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.28824323415756226},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2079836130142212},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.154801607131958},{"id":"https://openalex.org/keywords/drug-discovery","display_name":"Drug discovery","score":0.1296309530735016},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.12826037406921387}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7353984117507935},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.7327483892440796},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6176792979240417},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6110197901725769},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.606910765171051},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5080316066741943},{"id":"https://openalex.org/C99726746","wikidata":"https://www.wikidata.org/wiki/Q906396","display_name":"Chemical space","level":3,"score":0.487301230430603},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4858660101890564},{"id":"https://openalex.org/C123860398","wikidata":"https://www.wikidata.org/wiki/Q6934605","display_name":"Multiclass classification","level":3,"score":0.438648521900177},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.435477614402771},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43545955419540405},{"id":"https://openalex.org/C27181475","wikidata":"https://www.wikidata.org/wiki/Q541014","display_name":"Cross-validation","level":2,"score":0.4274723529815674},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.28824323415756226},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2079836130142212},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.154801607131958},{"id":"https://openalex.org/C74187038","wikidata":"https://www.wikidata.org/wiki/Q1418791","display_name":"Drug discovery","level":2,"score":0.1296309530735016},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.12826037406921387},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000284","descriptor_name":"Administration, Oral","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000284","descriptor_name":"Administration, Oral","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000284","descriptor_name":"Administration, Oral","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001331","descriptor_name":"Automation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001331","descriptor_name":"Automation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001331","descriptor_name":"Automation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007928","descriptor_name":"Lethal Dose 50","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007928","descriptor_name":"Lethal Dose 50","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007928","descriptor_name":"Lethal Dose 50","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012044","descriptor_name":"Regression Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012044","descriptor_name":"Regression Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012044","descriptor_name":"Regression Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015233","descriptor_name":"Models, Statistical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D015233","descriptor_name":"Models, Statistical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D015233","descriptor_name":"Models, Statistical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D018675","descriptor_name":"Toxicity Tests","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D018675","descriptor_name":"Toxicity Tests","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D018675","descriptor_name":"Toxicity Tests","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D048088","descriptor_name":"Informatics","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D048088","descriptor_name":"Informatics","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D048088","descriptor_name":"Informatics","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1021/acs.jcim.7b00244","is_oa":false,"landing_page_url":"https://doi.org/10.1021/acs.jcim.7b00244","pdf_url":null,"source":{"id":"https://openalex.org/S167262187","display_name":"Journal of Chemical Information and Modeling","issn_l":"1549-9596","issn":["1549-9596","1549-960X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320006","host_organization_name":"American Chemical Society","host_organization_lineage":["https://openalex.org/P4310320006"],"host_organization_lineage_names":["American Chemical Society"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Chemical Information and Modeling","raw_type":"journal-article"},{"id":"pmid:29019671","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/29019671","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of chemical information and modeling","raw_type":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.4099999964237213}],"awards":[{"id":"https://openalex.org/G2721886344","display_name":null,"funder_award_id":"2015CB910302","funder_id":"https://openalex.org/F4320321540","funder_display_name":"Ministry of Science and Technology of the People's Republic of China"},{"id":"https://openalex.org/G2815554813","display_name":null,"funder_award_id":"21673010","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3761634645","display_name":"\u86cb\u767d\u8d28\u522b\u6784\u8c03\u63a7\u673a\u5236\u7814\u7a76","funder_award_id":"21633001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7620890158","display_name":null,"funder_award_id":"2016YFA0502303","funder_id":"https://openalex.org/F4320321540","funder_display_name":"Ministry of Science and Technology of the People's Republic 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/F4320321540","display_name":"Ministry of Science and Technology of the People's Republic of China","ror":"https://ror.org/027s68j25"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W1586651324","https://openalex.org/W1964513093","https://openalex.org/W1964953537","https://openalex.org/W1966785965","https://openalex.org/W1977573154","https://openalex.org/W1982597534","https://openalex.org/W1985167300","https://openalex.org/W1988037271","https://openalex.org/W2000189060","https://openalex.org/W2008764714","https://openalex.org/W2014858249","https://openalex.org/W2016053056","https://openalex.org/W2019855719","https://openalex.org/W2035536473","https://openalex.org/W2039369430","https://openalex.org/W2043189747","https://openalex.org/W2046589863","https://openalex.org/W2048080607","https://openalex.org/W2049293086","https://openalex.org/W2050081822","https://openalex.org/W2064767911","https://openalex.org/W2076498053","https://openalex.org/W2087091908","https://openalex.org/W2096560421","https://openalex.org/W2097851570","https://openalex.org/W2097998348","https://openalex.org/W2101234009","https://openalex.org/W2134164499","https://openalex.org/W2144354855","https://openalex.org/W2158585626","https://openalex.org/W2160344370","https://openalex.org/W2189911347","https://openalex.org/W2190612770","https://openalex.org/W2200017991","https://openalex.org/W2213443318","https://openalex.org/W2215622313","https://openalex.org/W2234529989","https://openalex.org/W2250904038","https://openalex.org/W2269909407","https://openalex.org/W2290847742","https://openalex.org/W2304933537","https://openalex.org/W2523246573","https://openalex.org/W2613825731","https://openalex.org/W2735246657","https://openalex.org/W2737373109","https://openalex.org/W2914585913","https://openalex.org/W2919115771","https://openalex.org/W2970501782","https://openalex.org/W3100157108","https://openalex.org/W4234674466","https://openalex.org/W4236617412","https://openalex.org/W4243990219","https://openalex.org/W4255434014","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2100523380","https://openalex.org/W2141738404","https://openalex.org/W1907816360","https://openalex.org/W2019678805","https://openalex.org/W2134888474","https://openalex.org/W2080355854","https://openalex.org/W1800458610","https://openalex.org/W2384527366","https://openalex.org/W2388825802","https://openalex.org/W4206358301"],"abstract_inverted_index":{"Median":[0],"lethal":[1],"death,":[2],"LD":[3],"50,":[4],"is":[5,214],"a":[6,182],"general":[7],"indicator":[8],"of":[9,48,95,110,128,156,185,205,227],"compound":[10],"acute":[11],"oral":[12],"toxicity":[13,222],"(AOT).":[14],"Various":[15],"in":[16,217],"silico":[17],"methods":[18,168],"were":[19,102,112],"developed":[20,33],"for":[21,144,159,212],"AOT":[22,50,213],"prediction":[23,108,126],"to":[24,44,188],"reduce":[25],"costs":[26],"and":[27,58,81,90,104,106,114,120,132,138,142,153,197,219],"time.":[28],"In":[29],"this":[30],"study,":[31],"we":[32],"an":[34],"improved":[35],"molecular":[36],"graph":[37],"encoding":[38],"convolutional":[39],"neural":[40],"networks":[41],"(MGE-CNN)":[42],"architecture":[43,211],"construct":[45],"three":[46],"types":[47],"high-quality":[49],"models:":[51],"regression":[52],"model":[53,56,60],"(deepAOT-R),":[54],"multiclassification":[55],"(deepAOT-C),":[57],"multitask":[59],"(deepAOT-CR).":[61],"These":[62],"predictive":[63],"models":[64,158,233],"highly":[65],"outperformed":[66],"previously":[67],"reported":[68],"models.":[69],"For":[70],"the":[71,87,98,107,135,190,206],"two":[72,124,231],"external":[73,125],"data":[74],"sets":[75,118],"containing":[76],"1673":[77],"(test":[78,83],"set":[79,84,100,146],"I)":[80],"375":[82],"II)":[85],"compounds,":[86],"R":[88,136],"2":[89,137],"mean":[91],"absolute":[92],"errors":[93],"(MAEs)":[94],"deepAOT-R":[96],"on":[97,116],"test":[99,117,145],"I":[101,119],"0.864":[103],"0.195,":[105],"accuracies":[109,127],"deepAOT-C":[111],"95.5%":[113],"96.3%":[115],"II,":[121],"respectively.":[122,148],"The":[123,230],"deepAOT-CR":[129],"are":[130,140,234],"95.0%":[131],"94.1%,":[133],"while":[134],"MAE":[139],"0.861":[141],"0.204":[143],"I,":[147],"We":[149,176],"then":[150],"performed":[151,178],"forward":[152],"backward":[154],"exploration":[155],"deepAOT":[157,232],"deep":[160,186,209],"fingerprints,":[161],"which":[162],"could":[163],"support":[164],"shallow":[165],"machine":[166],"learning":[167,210],"more":[169],"efficiently":[170],"than":[171],"traditional":[172],"fingerprints":[173],"or":[174,223,239],"descriptors.":[175],"further":[177],"automatic":[179],"feature":[180],"learning,":[181,187],"key":[183],"essence":[184],"map":[189],"corresponding":[191],"activation":[192],"values":[193],"into":[194],"fragment":[195],"space":[196],"derive":[198],"AOT-related":[199],"chemical":[200,228],"substructures":[201],"by":[202],"reverse":[203],"mining":[204],"features.":[207],"Our":[208],"generally":[215],"applicable":[216],"predicting":[218],"exploring":[220],"other":[221],"property":[224],"end":[225],"points":[226],"compounds.":[229],"freely":[235],"available":[236],"at":[237],"http://repharma.pku.edu.cn/DLAOT/DLAOThome.php":[238],"http://www.pkumdl.cn/DLAOT/DLAOThome.php":[240],".":[241]},"counts_by_year":[{"year":2026,"cited_by_count":13},{"year":2025,"cited_by_count":23},{"year":2024,"cited_by_count":31},{"year":2023,"cited_by_count":44},{"year":2022,"cited_by_count":29},{"year":2021,"cited_by_count":36},{"year":2020,"cited_by_count":39},{"year":2019,"cited_by_count":25},{"year":2018,"cited_by_count":23}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}