{"id":"https://openalex.org/W3109675364","doi":"https://doi.org/10.1021/acs.jcim.0c00884","title":"Critical Assessment of Artificial Intelligence Methods for Prediction of hERG Channel Inhibition in the \u201cBig Data\u201d Era","display_name":"Critical Assessment of Artificial Intelligence Methods for Prediction of hERG Channel Inhibition in the \u201cBig Data\u201d Era","publication_year":2020,"publication_date":"2020-12-01","ids":{"openalex":"https://openalex.org/W3109675364","doi":"https://doi.org/10.1021/acs.jcim.0c00884","mag":"3109675364","pmid":"https://pubmed.ncbi.nlm.nih.gov/33259212"},"language":"en","primary_location":{"id":"doi:10.1021/acs.jcim.0c00884","is_oa":false,"landing_page_url":"https://doi.org/10.1021/acs.jcim.0c00884","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":true,"oa_status":"green","oa_url":"https://figshare.com/articles/journal_contribution/Critical_Assessment_of_Artificial_Intelligence_Methods_for_Prediction_of_hERG_Channel_Inhibition_in_the_Big_Data_Era/13315308","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5042866883","display_name":"Vishal B. Siramshetty","orcid":"https://orcid.org/0000-0002-5980-8288"},"institutions":[{"id":"https://openalex.org/I4210148682","display_name":"National Center for Advancing Translational Sciences","ror":"https://ror.org/04pw6fb54","country_code":"US","type":"government","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I4210148682"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vishal B. Siramshetty","raw_affiliation_strings":["National Center for Advancing Translational Sciences (NCATS), 9800 Medical Center Drive, Rockville, Maryland 20850, United States"],"affiliations":[{"raw_affiliation_string":"National Center for Advancing Translational Sciences (NCATS), 9800 Medical Center Drive, Rockville, Maryland 20850, United States","institution_ids":["https://openalex.org/I4210148682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061179559","display_name":"\u00d0\u1eafc-Trung Nguy\u1ec5n","orcid":"https://orcid.org/0000-0003-2591-9948"},"institutions":[{"id":"https://openalex.org/I4210148682","display_name":"National Center for Advancing Translational Sciences","ror":"https://ror.org/04pw6fb54","country_code":"US","type":"government","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I4210148682"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dac-Trung Nguyen","raw_affiliation_strings":["National Center for Advancing Translational Sciences (NCATS), 9800 Medical Center Drive, Rockville, Maryland 20850, United States"],"affiliations":[{"raw_affiliation_string":"National Center for Advancing Translational Sciences (NCATS), 9800 Medical Center Drive, Rockville, Maryland 20850, United States","institution_ids":["https://openalex.org/I4210148682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079873012","display_name":"Natalia J. Martinez","orcid":"https://orcid.org/0000-0002-0663-9011"},"institutions":[{"id":"https://openalex.org/I4210148682","display_name":"National Center for Advancing Translational Sciences","ror":"https://ror.org/04pw6fb54","country_code":"US","type":"government","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I4210148682"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Natalia J. Martinez","raw_affiliation_strings":["National Center for Advancing Translational Sciences (NCATS), 9800 Medical Center Drive, Rockville, Maryland 20850, United States"],"affiliations":[{"raw_affiliation_string":"National Center for Advancing Translational Sciences (NCATS), 9800 Medical Center Drive, Rockville, Maryland 20850, United States","institution_ids":["https://openalex.org/I4210148682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036261394","display_name":"Noel Southall","orcid":"https://orcid.org/0000-0003-4500-880X"},"institutions":[{"id":"https://openalex.org/I4210148682","display_name":"National Center for Advancing Translational Sciences","ror":"https://ror.org/04pw6fb54","country_code":"US","type":"government","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I4210148682"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Noel T. Southall","raw_affiliation_strings":["National Center for Advancing Translational Sciences (NCATS), 9800 Medical Center Drive, Rockville, Maryland 20850, United States"],"affiliations":[{"raw_affiliation_string":"National Center for Advancing Translational Sciences (NCATS), 9800 Medical Center Drive, Rockville, Maryland 20850, United States","institution_ids":["https://openalex.org/I4210148682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059969497","display_name":"Anton Simeonov","orcid":"https://orcid.org/0000-0002-4523-9977"},"institutions":[{"id":"https://openalex.org/I4210148682","display_name":"National Center for Advancing Translational Sciences","ror":"https://ror.org/04pw6fb54","country_code":"US","type":"government","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I4210148682"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anton Simeonov","raw_affiliation_strings":["National Center for Advancing Translational Sciences (NCATS), 9800 Medical Center Drive, Rockville, Maryland 20850, United States"],"affiliations":[{"raw_affiliation_string":"National Center for Advancing Translational Sciences (NCATS), 9800 Medical Center Drive, Rockville, Maryland 20850, United States","institution_ids":["https://openalex.org/I4210148682"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080525121","display_name":"Alexey Zakharov","orcid":"https://orcid.org/0000-0003-2466-1711"},"institutions":[{"id":"https://openalex.org/I4210148682","display_name":"National Center for Advancing Translational Sciences","ror":"https://ror.org/04pw6fb54","country_code":"US","type":"government","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I4210148682"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Alexey V. Zakharov","raw_affiliation_strings":["National Center for Advancing Translational Sciences (NCATS), 9800 Medical Center Drive, Rockville, Maryland 20850, United States"],"affiliations":[{"raw_affiliation_string":"National Center for Advancing Translational Sciences (NCATS), 9800 Medical Center Drive, Rockville, Maryland 20850, United States","institution_ids":["https://openalex.org/I4210148682"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5080525121"],"corresponding_institution_ids":["https://openalex.org/I4210148682"],"apc_list":null,"apc_paid":null,"fwci":5.6299,"has_fulltext":false,"cited_by_count":74,"citation_normalized_percentile":{"value":0.96729535,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"60","issue":"12","first_page":"6007","last_page":"6019"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9995999932289124,"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":0.9995999932289124,"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/T11948","display_name":"Machine Learning in Materials Science","score":0.9955000281333923,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10217","display_name":"Cardiac electrophysiology and arrhythmias","score":0.9599999785423279,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/herg","display_name":"hERG","score":0.9767904877662659},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6808334589004517},{"id":"https://openalex.org/keywords/chembl","display_name":"chEMBL","score":0.6704024076461792},{"id":"https://openalex.org/keywords/chemical-space","display_name":"Chemical space","score":0.656271755695343},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6078693866729736},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5767806172370911},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.576275110244751},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.5036768317222595},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4480729401111603},{"id":"https://openalex.org/keywords/drug-discovery","display_name":"Drug discovery","score":0.446260929107666},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4417089819908142},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.41520261764526367},{"id":"https://openalex.org/keywords/potassium-channel","display_name":"Potassium channel","score":0.24726799130439758},{"id":"https://openalex.org/keywords/bioinformatics","display_name":"Bioinformatics","score":0.1823054850101471},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.11908692121505737}],"concepts":[{"id":"https://openalex.org/C2779362680","wikidata":"https://www.wikidata.org/wiki/Q905000","display_name":"hERG","level":3,"score":0.9767904877662659},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6808334589004517},{"id":"https://openalex.org/C63222358","wikidata":"https://www.wikidata.org/wiki/Q6120337","display_name":"chEMBL","level":3,"score":0.6704024076461792},{"id":"https://openalex.org/C99726746","wikidata":"https://www.wikidata.org/wiki/Q906396","display_name":"Chemical space","level":3,"score":0.656271755695343},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6078693866729736},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5767806172370911},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.576275110244751},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.5036768317222595},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4480729401111603},{"id":"https://openalex.org/C74187038","wikidata":"https://www.wikidata.org/wiki/Q1418791","display_name":"Drug discovery","level":2,"score":0.446260929107666},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4417089819908142},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.41520261764526367},{"id":"https://openalex.org/C83743174","wikidata":"https://www.wikidata.org/wiki/Q423778","display_name":"Potassium channel","level":2,"score":0.24726799130439758},{"id":"https://openalex.org/C60644358","wikidata":"https://www.wikidata.org/wiki/Q128570","display_name":"Bioinformatics","level":1,"score":0.1823054850101471},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.11908692121505737},{"id":"https://openalex.org/C12554922","wikidata":"https://www.wikidata.org/wiki/Q7100","display_name":"Biophysics","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000077558","descriptor_name":"Big Data","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000077558","descriptor_name":"Big Data","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000077558","descriptor_name":"Big Data","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D026902","descriptor_name":"Potassium Channel Blockers","qualifier_ui":"Q000494","qualifier_name":"pharmacology","is_major_topic":true},{"descriptor_ui":"D026902","descriptor_name":"Potassium Channel Blockers","qualifier_ui":"Q000494","qualifier_name":"pharmacology","is_major_topic":true},{"descriptor_ui":"D026902","descriptor_name":"Potassium Channel Blockers","qualifier_ui":"Q000494","qualifier_name":"pharmacology","is_major_topic":true},{"descriptor_ui":"D051638","descriptor_name":"Ether-A-Go-Go Potassium Channels","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D051638","descriptor_name":"Ether-A-Go-Go Potassium Channels","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D051638","descriptor_name":"Ether-A-Go-Go Potassium Channels","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D055808","descriptor_name":"Drug Discovery","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D055808","descriptor_name":"Drug Discovery","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D055808","descriptor_name":"Drug Discovery","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":3,"locations":[{"id":"doi:10.1021/acs.jcim.0c00884","is_oa":false,"landing_page_url":"https://doi.org/10.1021/acs.jcim.0c00884","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:33259212","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33259212","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":null},{"id":"pmh:oai:figshare.com:article/13315308","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/Critical_Assessment_of_Artificial_Intelligence_Methods_for_Prediction_of_hERG_Channel_Inhibition_in_the_Big_Data_Era/13315308","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:figshare.com:article/13315308","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/Critical_Assessment_of_Artificial_Intelligence_Methods_for_Prediction_of_hERG_Channel_Inhibition_in_the_Big_Data_Era/13315308","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Text"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320337472","display_name":"National Center for Advancing Translational Sciences","ror":"https://ror.org/04pw6fb54"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":79,"referenced_works":["https://openalex.org/W1689711448","https://openalex.org/W1902237438","https://openalex.org/W1968098810","https://openalex.org/W1971256926","https://openalex.org/W1977362373","https://openalex.org/W1988195734","https://openalex.org/W1991537916","https://openalex.org/W1999798000","https://openalex.org/W2007697155","https://openalex.org/W2010992635","https://openalex.org/W2028070629","https://openalex.org/W2038481443","https://openalex.org/W2040826404","https://openalex.org/W2046126409","https://openalex.org/W2050273205","https://openalex.org/W2053351731","https://openalex.org/W2055221845","https://openalex.org/W2064675550","https://openalex.org/W2065682273","https://openalex.org/W2066047676","https://openalex.org/W2073907102","https://openalex.org/W2090240212","https://openalex.org/W2096541451","https://openalex.org/W2101234009","https://openalex.org/W2112411768","https://openalex.org/W2113242816","https://openalex.org/W2125271591","https://openalex.org/W2132267388","https://openalex.org/W2144381908","https://openalex.org/W2145957401","https://openalex.org/W2147670638","https://openalex.org/W2160305962","https://openalex.org/W2165545792","https://openalex.org/W2176516200","https://openalex.org/W2264043469","https://openalex.org/W2306570595","https://openalex.org/W2412746331","https://openalex.org/W2467309505","https://openalex.org/W2481808473","https://openalex.org/W2502949459","https://openalex.org/W2529996553","https://openalex.org/W2560974817","https://openalex.org/W2578240541","https://openalex.org/W2588652753","https://openalex.org/W2594183968","https://openalex.org/W2604296437","https://openalex.org/W2610148085","https://openalex.org/W2735073377","https://openalex.org/W2766761250","https://openalex.org/W2773987374","https://openalex.org/W2794063970","https://openalex.org/W2794245536","https://openalex.org/W2799462250","https://openalex.org/W2801991413","https://openalex.org/W2804885211","https://openalex.org/W2806715130","https://openalex.org/W2886791556","https://openalex.org/W2900694120","https://openalex.org/W2901476322","https://openalex.org/W2911107164","https://openalex.org/W2914969288","https://openalex.org/W2915175970","https://openalex.org/W2940278604","https://openalex.org/W2947920041","https://openalex.org/W2949335953","https://openalex.org/W2953128081","https://openalex.org/W2959123242","https://openalex.org/W2963729575","https://openalex.org/W2964308564","https://openalex.org/W2969759649","https://openalex.org/W2969849947","https://openalex.org/W2971690404","https://openalex.org/W2989615256","https://openalex.org/W2995165731","https://openalex.org/W3014154196","https://openalex.org/W3033251065","https://openalex.org/W3098269892","https://openalex.org/W3100751385","https://openalex.org/W4229590462"],"related_works":["https://openalex.org/W2815914914","https://openalex.org/W3005441379","https://openalex.org/W4207063555","https://openalex.org/W2604173773","https://openalex.org/W2997728144","https://openalex.org/W2055221845","https://openalex.org/W4210747027","https://openalex.org/W2770765812","https://openalex.org/W3117153716","https://openalex.org/W2791678506"],"abstract_inverted_index":{"The":[0,120,175,191,203,223,234],"rise":[1],"of":[2,21,43,58,74,77,93,205,263],"novel":[3,275],"artificial":[4],"intelligence":[5],"(AI)":[6],"methods":[7,110,265],"necessitates":[8],"their":[9],"benchmarking":[10],"against":[11],"classical":[12,100,221],"machine":[13],"learning":[14,85],"for":[15,55,71],"a":[16,39,50,90,168,240,284],"typical":[17],"drug-discovery":[18],"project.":[19],"Inhibition":[20],"the":[22,32,44,56,72,129,134,154,186,197,214,220,230,261,268],"potassium":[23],"ion":[24],"channel,":[25],"whose":[26],"alpha":[27],"subunit":[28],"is":[29,49],"encoded":[30],"by":[31,127],"human":[33],"<i>ether-\u00e0-go-go</i>-related":[34],"gene":[35],"(hERG),":[36],"leads":[37],"to":[38,67,248,266],"prolonged":[40],"QT":[41],"interval":[42],"cardiac":[45],"action":[46],"potential":[47,262],"and":[48,104,107,115,200,253,273,282],"significant":[51],"safety":[52],"pharmacology":[53],"target":[54],"development":[57],"new":[59,285],"medicines.":[60],"Several":[61],"computational":[62],"approaches":[63,101],"have":[64],"been":[65],"employed":[66],"develop":[68],"prediction":[69,96],"models":[70,97,176,206,236,250],"assessment":[73],"hERG":[75,94,130],"liabilities":[76],"small":[78],"molecules":[79],"including":[80,153],"recent":[81],"work":[82],"using":[83],"deep":[84],"methods.":[86,222],"Here,":[87],"we":[88,257],"perform":[89],"comprehensive":[91],"comparison":[92,204],"effect":[95],"based":[98,207],"on":[99,167,180,209,227,260],"(random":[102],"forests":[103],"gradient":[105],"boosting)":[106],"modern":[108],"AI":[109,264],"[deep":[111],"neural":[112,117],"networks":[113,118],"(DNNs)":[114],"recurrent":[116],"(RNNs)].":[119],"training":[121],"set":[122],"(\u223c9000":[123],"compounds)":[124],"was":[125],"compiled":[126],"integrating":[128],"bioactivity":[131],"data":[132,139,270],"from":[133,141,163,251],"ChEMBL":[135],"database":[136],"with":[137,196],"experimental":[138],"generated":[140],"an":[142],"<i>in-house</i>,":[143],"high-throughput":[144],"thallium":[145,188],"flux":[146,189],"assay.":[147,190],"We":[148],"utilized":[149],"different":[150],"molecular":[151],"descriptors":[152,211],"latent":[155,210],"descriptors,":[156],"which":[157],"are":[158],"real-value":[159],"continuous":[160],"vectors":[161],"derived":[162],"chemical":[164,170,276,286],"autoencoders":[165],"trained":[166],"large":[169],"space":[171],"(>1.5":[172],"million":[173],"compounds).":[174],"were":[177,194,237],"prospectively":[178],"validated":[179],"\u223c840":[181],"<i>in-house</i>":[182],"compounds":[183],"screened":[184],"in":[185,271,279],"same":[187],"best":[192,235],"results":[193],"obtained":[195],"XGBoost":[198],"method":[199],"RDKit":[201],"descriptors.":[202],"only":[208],"revealed":[212],"that":[213,225,243],"DNNs":[215],"performed":[216],"significantly":[217],"better":[218],"than":[219],"RNNs":[224],"operate":[226],"SMILES":[228],"provided":[229],"highest":[231],"model":[232,242],"sensitivity.":[233],"merged":[238],"into":[239],"consensus":[241],"offered":[244],"superior":[245],"performance":[246],"compared":[247],"reference":[249],"academic":[252],"commercial":[254],"domains.":[255],"Furthermore,":[256],"shed":[258],"light":[259],"exploit":[267],"big":[269],"chemistry":[272],"generate":[274],"representations":[277],"useful":[278],"predictive":[280],"modeling":[281],"tailoring":[283],"space.":[287]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":20},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":12},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-03-06T13:50:29.536080","created_date":"2025-10-10T00:00:00"}