{"id":"https://openalex.org/W2045736857","doi":"https://doi.org/10.1021/ci9000794","title":"Bias-Correction of Regression Models: A Case Study on hERG Inhibition","display_name":"Bias-Correction of Regression Models: A Case Study on hERG Inhibition","publication_year":2009,"publication_date":"2009-05-12","ids":{"openalex":"https://openalex.org/W2045736857","doi":"https://doi.org/10.1021/ci9000794","mag":"2045736857","pmid":"https://pubmed.ncbi.nlm.nih.gov/19435326"},"language":"en","primary_location":{"id":"doi:10.1021/ci9000794","is_oa":false,"landing_page_url":"https://doi.org/10.1021/ci9000794","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":"public-domain","license_id":"https://openalex.org/licenses/public-domain","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://zenodo.org/record/3424183","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5043469569","display_name":"Katja Hansen","orcid":null},"institutions":[{"id":"https://openalex.org/I1330995197","display_name":"Boehringer Ingelheim (Germany)","ror":"https://ror.org/00q32j219","country_code":"DE","type":"company","lineage":["https://openalex.org/I1330995197"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Katja Hansen","raw_affiliation_strings":["University of Technology, Berlin, Germany, Departments of Drug Discovery Support and Lead Discovery, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach a.d. Riss, Germany, and idalab GmbH, Berlin, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Technology, Berlin, Germany, Departments of Drug Discovery Support and Lead Discovery, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach a.d. Riss, Germany, and idalab GmbH, Berlin, Germany","institution_ids":["https://openalex.org/I1330995197"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011904999","display_name":"Fabian Rathke","orcid":"https://orcid.org/0000-0003-3508-4470"},"institutions":[{"id":"https://openalex.org/I1330995197","display_name":"Boehringer Ingelheim (Germany)","ror":"https://ror.org/00q32j219","country_code":"DE","type":"company","lineage":["https://openalex.org/I1330995197"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Fabian Rathke","raw_affiliation_strings":["University of Technology, Berlin, Germany, Departments of Drug Discovery Support and Lead Discovery, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach a.d. Riss, Germany, and idalab GmbH, Berlin, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Technology, Berlin, Germany, Departments of Drug Discovery Support and Lead Discovery, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach a.d. Riss, Germany, and idalab GmbH, Berlin, Germany","institution_ids":["https://openalex.org/I1330995197"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044997850","display_name":"Timon Schroeter","orcid":null},"institutions":[{"id":"https://openalex.org/I1330995197","display_name":"Boehringer Ingelheim (Germany)","ror":"https://ror.org/00q32j219","country_code":"DE","type":"company","lineage":["https://openalex.org/I1330995197"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Timon Schroeter","raw_affiliation_strings":["University of Technology, Berlin, Germany, Departments of Drug Discovery Support and Lead Discovery, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach a.d. Riss, Germany, and idalab GmbH, Berlin, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Technology, Berlin, Germany, Departments of Drug Discovery Support and Lead Discovery, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach a.d. Riss, Germany, and idalab GmbH, Berlin, Germany","institution_ids":["https://openalex.org/I1330995197"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045351161","display_name":"Georg Rast","orcid":"https://orcid.org/0000-0002-8307-7796"},"institutions":[{"id":"https://openalex.org/I1330995197","display_name":"Boehringer Ingelheim (Germany)","ror":"https://ror.org/00q32j219","country_code":"DE","type":"company","lineage":["https://openalex.org/I1330995197"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Georg Rast","raw_affiliation_strings":["University of Technology, Berlin, Germany, Departments of Drug Discovery Support and Lead Discovery, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach a.d. Riss, Germany, and idalab GmbH, Berlin, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Technology, Berlin, Germany, Departments of Drug Discovery Support and Lead Discovery, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach a.d. Riss, Germany, and idalab GmbH, Berlin, Germany","institution_ids":["https://openalex.org/I1330995197"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011361588","display_name":"Thomas Fox","orcid":"https://orcid.org/0000-0002-1054-4701"},"institutions":[{"id":"https://openalex.org/I1330995197","display_name":"Boehringer Ingelheim (Germany)","ror":"https://ror.org/00q32j219","country_code":"DE","type":"company","lineage":["https://openalex.org/I1330995197"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Thomas Fox","raw_affiliation_strings":["University of Technology, Berlin, Germany, Departments of Drug Discovery Support and Lead Discovery, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach a.d. Riss, Germany, and idalab GmbH, Berlin, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Technology, Berlin, Germany, Departments of Drug Discovery Support and Lead Discovery, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach a.d. Riss, Germany, and idalab GmbH, Berlin, Germany","institution_ids":["https://openalex.org/I1330995197"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029948268","display_name":"Jan M. Kriegl","orcid":null},"institutions":[{"id":"https://openalex.org/I1330995197","display_name":"Boehringer Ingelheim (Germany)","ror":"https://ror.org/00q32j219","country_code":"DE","type":"company","lineage":["https://openalex.org/I1330995197"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Jan M. Kriegl","raw_affiliation_strings":["University of Technology, Berlin, Germany, Departments of Drug Discovery Support and Lead Discovery, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach a.d. Riss, Germany, and idalab GmbH, Berlin, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Technology, Berlin, Germany, Departments of Drug Discovery Support and Lead Discovery, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach a.d. Riss, Germany, and idalab GmbH, Berlin, Germany","institution_ids":["https://openalex.org/I1330995197"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5104050565","display_name":"Sebastian Mika","orcid":null},"institutions":[{"id":"https://openalex.org/I1330995197","display_name":"Boehringer Ingelheim (Germany)","ror":"https://ror.org/00q32j219","country_code":"DE","type":"company","lineage":["https://openalex.org/I1330995197"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Sebastian Mika","raw_affiliation_strings":["University of Technology, Berlin, Germany, Departments of Drug Discovery Support and Lead Discovery, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach a.d. Riss, Germany, and idalab GmbH, Berlin, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Technology, Berlin, Germany, Departments of Drug Discovery Support and Lead Discovery, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach a.d. Riss, Germany, and idalab GmbH, Berlin, Germany","institution_ids":["https://openalex.org/I1330995197"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5029948268","https://openalex.org/A5104050565"],"corresponding_institution_ids":["https://openalex.org/I1330995197"],"apc_list":null,"apc_paid":null,"fwci":3.9,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.93457226,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"49","issue":"6","first_page":"1486","last_page":"1496"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9993000030517578,"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":0.9993000030517578,"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/T11423","display_name":"Pesticide Residue Analysis and Safety","score":0.9908000230789185,"subfield":{"id":"https://openalex.org/subfields/1106","display_name":"Food 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"}},{"id":"https://openalex.org/T11178","display_name":"Receptor Mechanisms and Signaling","score":0.98580002784729,"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/herg","display_name":"hERG","score":0.7428532838821411},{"id":"https://openalex.org/keywords/cross-validation","display_name":"Cross-validation","score":0.6555557250976562},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.6090850830078125},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5772140026092529},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.5441979765892029},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.5087390542030334},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4916711449623108},{"id":"https://openalex.org/keywords/quantitative-structure\u2013activity-relationship","display_name":"Quantitative structure\u2013activity relationship","score":0.4811231195926666},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4685681164264679},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4529974162578583},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.44428786635398865},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.43426331877708435},{"id":"https://openalex.org/keywords/applicability-domain","display_name":"Applicability domain","score":0.42944738268852234},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35667356848716736},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3535648584365845},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3204893469810486},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.28904470801353455}],"concepts":[{"id":"https://openalex.org/C2779362680","wikidata":"https://www.wikidata.org/wiki/Q905000","display_name":"hERG","level":3,"score":0.7428532838821411},{"id":"https://openalex.org/C27181475","wikidata":"https://www.wikidata.org/wiki/Q541014","display_name":"Cross-validation","level":2,"score":0.6555557250976562},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.6090850830078125},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5772140026092529},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5441979765892029},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.5087390542030334},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4916711449623108},{"id":"https://openalex.org/C164126121","wikidata":"https://www.wikidata.org/wiki/Q766383","display_name":"Quantitative structure\u2013activity relationship","level":2,"score":0.4811231195926666},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4685681164264679},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4529974162578583},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.44428786635398865},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.43426331877708435},{"id":"https://openalex.org/C107908354","wikidata":"https://www.wikidata.org/wiki/Q4781456","display_name":"Applicability domain","level":3,"score":0.42944738268852234},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35667356848716736},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3535648584365845},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3204893469810486},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28904470801353455},{"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/C83743174","wikidata":"https://www.wikidata.org/wiki/Q423778","display_name":"Potassium channel","level":2,"score":0.0},{"id":"https://openalex.org/C12554922","wikidata":"https://www.wikidata.org/wiki/Q7100","display_name":"Biophysics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[{"descriptor_ui":"D004353","descriptor_name":"Drug Evaluation, Preclinical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004353","descriptor_name":"Drug Evaluation, Preclinical","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004353","descriptor_name":"Drug Evaluation, Preclinical","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":"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":"D015203","descriptor_name":"Reproducibility of Results","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015203","descriptor_name":"Reproducibility of Results","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015203","descriptor_name":"Reproducibility of Results","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D020128","descriptor_name":"Inhibitory Concentration 50","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D020128","descriptor_name":"Inhibitory Concentration 50","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D020128","descriptor_name":"Inhibitory Concentration 50","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D021281","descriptor_name":"Quantitative Structure-Activity Relationship","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D021281","descriptor_name":"Quantitative Structure-Activity Relationship","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D021281","descriptor_name":"Quantitative Structure-Activity Relationship","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D026902","descriptor_name":"Potassium Channel Blockers","qualifier_ui":"Q000494","qualifier_name":"pharmacology","is_major_topic":false},{"descriptor_ui":"D026902","descriptor_name":"Potassium Channel Blockers","qualifier_ui":"Q000494","qualifier_name":"pharmacology","is_major_topic":false},{"descriptor_ui":"D026902","descriptor_name":"Potassium Channel Blockers","qualifier_ui":"Q000494","qualifier_name":"pharmacology","is_major_topic":false},{"descriptor_ui":"D026902","descriptor_name":"Potassium Channel Blockers","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":false},{"descriptor_ui":"D026902","descriptor_name":"Potassium Channel Blockers","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":false},{"descriptor_ui":"D026902","descriptor_name":"Potassium Channel Blockers","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":false},{"descriptor_ui":"D051638","descriptor_name":"Ether-A-Go-Go Potassium Channels","qualifier_ui":"Q000037","qualifier_name":"antagonists & inhibitors","is_major_topic":false},{"descriptor_ui":"D051638","descriptor_name":"Ether-A-Go-Go Potassium Channels","qualifier_ui":"Q000037","qualifier_name":"antagonists & inhibitors","is_major_topic":false},{"descriptor_ui":"D051638","descriptor_name":"Ether-A-Go-Go Potassium Channels","qualifier_ui":"Q000037","qualifier_name":"antagonists & inhibitors","is_major_topic":false}],"locations_count":3,"locations":[{"id":"doi:10.1021/ci9000794","is_oa":false,"landing_page_url":"https://doi.org/10.1021/ci9000794","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":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Chemical Information and Modeling","raw_type":"journal-article"},{"id":"pmid:19435326","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/19435326","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:zenodo.org:3424183","is_oa":true,"landing_page_url":"https://zenodo.org/record/3424183","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:zenodo.org:3424183","is_oa":true,"landing_page_url":"https://zenodo.org/record/3424183","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[{"score":0.6700000166893005,"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"},{"id":"https://openalex.org/F4320338370","display_name":"FP7 Information and Communication Technologies","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W181484868","https://openalex.org/W1480376833","https://openalex.org/W1964357740","https://openalex.org/W1972043917","https://openalex.org/W1985912434","https://openalex.org/W1986511007","https://openalex.org/W1989485111","https://openalex.org/W1992229282","https://openalex.org/W1995849691","https://openalex.org/W2005737523","https://openalex.org/W2006671852","https://openalex.org/W2017016867","https://openalex.org/W2017448415","https://openalex.org/W2018285323","https://openalex.org/W2019137778","https://openalex.org/W2020935478","https://openalex.org/W2026544535","https://openalex.org/W2031372687","https://openalex.org/W2034151123","https://openalex.org/W2038094422","https://openalex.org/W2038706465","https://openalex.org/W2040826404","https://openalex.org/W2043113066","https://openalex.org/W2043440279","https://openalex.org/W2045103635","https://openalex.org/W2045517587","https://openalex.org/W2051790677","https://openalex.org/W2052017927","https://openalex.org/W2069323057","https://openalex.org/W2077582053","https://openalex.org/W2085087514","https://openalex.org/W2094015791","https://openalex.org/W2097582882","https://openalex.org/W2107375130","https://openalex.org/W2108995755","https://openalex.org/W2118689184","https://openalex.org/W2137689619","https://openalex.org/W2138095345","https://openalex.org/W2148603752","https://openalex.org/W2156140776","https://openalex.org/W2160384674","https://openalex.org/W2163863644","https://openalex.org/W2165453268","https://openalex.org/W2167917621","https://openalex.org/W2213612645","https://openalex.org/W2911964244","https://openalex.org/W3047442941","https://openalex.org/W4211049957","https://openalex.org/W4238793347","https://openalex.org/W4245139594","https://openalex.org/W4253853981","https://openalex.org/W4388297464"],"related_works":["https://openalex.org/W2746158299","https://openalex.org/W1969085205","https://openalex.org/W1977382278","https://openalex.org/W2090257471","https://openalex.org/W1970841929","https://openalex.org/W3005120176","https://openalex.org/W2562984628","https://openalex.org/W2033669961","https://openalex.org/W2055461258","https://openalex.org/W2083497194"],"abstract_inverted_index":{"In":[0],"the":[1,11,14,105,109,137,152],"present":[2],"work":[3],"we":[4],"develop":[5,29],"a":[6,25,51,124,132,174],"predictive":[7],"QSAR":[8],"model":[9,138],"for":[10,34],"blockade":[12],"of":[13,55,75,92,104,136,142],"hERG":[15,41],"channel.":[16],"Additionally,":[17],"this":[18],"specific":[19],"end":[20],"point":[21],"is":[22,128],"used":[23],"as":[24,97,157],"test":[26],"scenario":[27],"to":[28,130,145,169],"and":[30,59,72],"evaluate":[31],"several":[32,143],"techniques":[33,71,144],"fusing":[35],"predictions":[36],"from":[37,99,159,165],"multiple":[38,147],"regression":[39],"models.":[40],"inhibition":[42],"models":[43,87,149],"which":[44],"are":[45,48,65],"presented":[46],"here":[47],"based":[49],"on":[50,108],"combined":[52],"data":[53],"set":[54],"roughly":[56,93],"550":[57],"proprietary":[58],"110":[60],"public":[61],"domain":[62],"compounds.":[63],"Models":[64],"built":[66],"using":[67,173],"various":[68],"statistical":[69],"learning":[70],"different":[73],"sets":[74],"molecular":[76],"descriptors.":[77],"Single":[78],"Support":[79],"Vector":[80],"Regression,":[81],"Gaussian":[82],"Process,":[83],"or":[84],"Random":[85],"Forest":[86],"achieve":[88],"root":[89,153],"mean-squared":[90],"errors":[91],"0.6":[94],"log":[95],"units":[96],"determined":[98,158],"leave-group-out":[100,115],"cross-validation.":[101],"An":[102],"analysis":[103],"evaluation":[106,141],"strategy":[107],"performance":[110],"estimates":[111],"shows":[112,150],"that":[113,151],"standard":[114],"cross-validation":[116,126,161],"yields":[117],"overly":[118],"optimistic":[119],"results.":[120],"As":[121],"an":[122],"alternative,":[123],"clustered":[125,160],"scheme":[127],"introduced":[129],"obtain":[131],"more":[133],"realistic":[134],"estimate":[135],"performance.":[139],"The":[140],"combine":[146],"prediction":[148],"mean":[154],"squared":[155],"error":[156],"can":[162],"be":[163],"reduced":[164],"0.73":[166],"+/-":[167,171],"0.01":[168,172],"0.57":[170],"local":[175],"bias":[176],"correction":[177],"strategy.":[178]},"counts_by_year":[{"year":2021,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":5},{"year":2012,"cited_by_count":3}],"updated_date":"2026-06-16T07:32:37.131356","created_date":"2025-10-10T00:00:00"}