{"id":"https://openalex.org/W2005772498","doi":"https://doi.org/10.1021/ci900406x","title":"Gaussian Processes for Classification: QSAR Modeling of ADMET and Target Activity","display_name":"Gaussian Processes for Classification: QSAR Modeling of ADMET and Target Activity","publication_year":2010,"publication_date":"2010-04-30","ids":{"openalex":"https://openalex.org/W2005772498","doi":"https://doi.org/10.1021/ci900406x","mag":"2005772498","pmid":"https://pubmed.ncbi.nlm.nih.gov/20433177"},"language":"en","primary_location":{"id":"doi:10.1021/ci900406x","is_oa":false,"landing_page_url":"https://doi.org/10.1021/ci900406x","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/A5076682119","display_name":"Olga Obrezanova","orcid":"https://orcid.org/0000-0002-2144-4634"},"institutions":[{"id":"https://openalex.org/I4210090988","display_name":"Optibrium (United Kingdom)","ror":"https://ror.org/00djq1r46","country_code":"GB","type":"company","lineage":["https://openalex.org/I4210090988"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Olga Obrezanova","raw_affiliation_strings":["Optibrium Ltd., 7226 IQ Cambridge, Beach Drive, Cambridge, CB25 9TL, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Optibrium Ltd., 7226 IQ Cambridge, Beach Drive, Cambridge, CB25 9TL, United Kingdom","institution_ids":["https://openalex.org/I4210090988"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044158268","display_name":"Matthew Segall","orcid":"https://orcid.org/0000-0002-2105-6535"},"institutions":[{"id":"https://openalex.org/I4210090988","display_name":"Optibrium (United Kingdom)","ror":"https://ror.org/00djq1r46","country_code":"GB","type":"company","lineage":["https://openalex.org/I4210090988"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Matthew D. Segall","raw_affiliation_strings":["Optibrium Ltd., 7226 IQ Cambridge, Beach Drive, Cambridge, CB25 9TL, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Optibrium Ltd., 7226 IQ Cambridge, Beach Drive, Cambridge, CB25 9TL, United Kingdom","institution_ids":["https://openalex.org/I4210090988"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5076682119"],"corresponding_institution_ids":["https://openalex.org/I4210090988"],"apc_list":null,"apc_paid":null,"fwci":5.90024272,"has_fulltext":false,"cited_by_count":71,"citation_normalized_percentile":{"value":0.96174778,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"50","issue":"6","first_page":"1053","last_page":"1061"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9997000098228455,"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":0.9997000098228455,"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/T10836","display_name":"Metabolomics and Mass Spectrometry Studies","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11948","display_name":"Machine Learning in Materials Science","score":0.9538000226020813,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.7829322814941406},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.6731778383255005},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6461813449859619},{"id":"https://openalex.org/keywords/quantitative-structure\u2013activity-relationship","display_name":"Quantitative structure\u2013activity relationship","score":0.6384023427963257},{"id":"https://openalex.org/keywords/probit-model","display_name":"Probit model","score":0.6000931262969971},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5835533738136292},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5754030346870422},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.5656509399414062},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5596209764480591},{"id":"https://openalex.org/keywords/probit","display_name":"Probit","score":0.5209190249443054},{"id":"https://openalex.org/keywords/partial-least-squares-regression","display_name":"Partial least squares regression","score":0.48058247566223145},{"id":"https://openalex.org/keywords/kriging","display_name":"Kriging","score":0.466656893491745},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.4489339590072632},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42465895414352417},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3460143506526947},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3370170593261719},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.13089606165885925},{"id":"https://openalex.org/keywords/computational-chemistry","display_name":"Computational chemistry","score":0.09967252612113953}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.7829322814941406},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.6731778383255005},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6461813449859619},{"id":"https://openalex.org/C164126121","wikidata":"https://www.wikidata.org/wiki/Q766383","display_name":"Quantitative structure\u2013activity relationship","level":2,"score":0.6384023427963257},{"id":"https://openalex.org/C67257552","wikidata":"https://www.wikidata.org/wiki/Q635217","display_name":"Probit model","level":2,"score":0.6000931262969971},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5835533738136292},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5754030346870422},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.5656509399414062},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5596209764480591},{"id":"https://openalex.org/C184314375","wikidata":"https://www.wikidata.org/wiki/Q3117995","display_name":"Probit","level":2,"score":0.5209190249443054},{"id":"https://openalex.org/C22354355","wikidata":"https://www.wikidata.org/wiki/Q422009","display_name":"Partial least squares regression","level":2,"score":0.48058247566223145},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.466656893491745},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.4489339590072632},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42465895414352417},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3460143506526947},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3370170593261719},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.13089606165885925},{"id":"https://openalex.org/C147597530","wikidata":"https://www.wikidata.org/wiki/Q369472","display_name":"Computational chemistry","level":1,"score":0.09967252612113953}],"mesh":[{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001812","descriptor_name":"Blood-Brain Barrier","qualifier_ui":"Q000378","qualifier_name":"metabolism","is_major_topic":false},{"descriptor_ui":"D002965","descriptor_name":"Classification","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D003663","descriptor_name":"Decision Trees","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":"D051638","descriptor_name":"Ether-A-Go-Go Potassium Channels","qualifier_ui":"Q000037","qualifier_name":"antagonists & inhibitors","is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006863","descriptor_name":"Hydrogen-Ion Concentration","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007408","descriptor_name":"Intestinal Absorption","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016018","descriptor_name":"Least-Squares Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008954","descriptor_name":"Models, Biological","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016011","descriptor_name":"Normal Distribution","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004364","descriptor_name":"Pharmaceutical Preparations","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":false},{"descriptor_ui":"D004364","descriptor_name":"Pharmaceutical Preparations","qualifier_ui":"Q000378","qualifier_name":"metabolism","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":"D012995","descriptor_name":"Solubility","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014867","descriptor_name":"Water","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":false},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001812","descriptor_name":"Blood-Brain Barrier","qualifier_ui":"Q000378","qualifier_name":"metabolism","is_major_topic":false},{"descriptor_ui":"D002965","descriptor_name":"Classification","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D003663","descriptor_name":"Decision Trees","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":"D051638","descriptor_name":"Ether-A-Go-Go Potassium Channels","qualifier_ui":"Q000037","qualifier_name":"antagonists & inhibitors","is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006863","descriptor_name":"Hydrogen-Ion Concentration","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007408","descriptor_name":"Intestinal Absorption","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016018","descriptor_name":"Least-Squares Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008954","descriptor_name":"Models, Biological","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016011","descriptor_name":"Normal Distribution","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004364","descriptor_name":"Pharmaceutical Preparations","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":false},{"descriptor_ui":"D004364","descriptor_name":"Pharmaceutical Preparations","qualifier_ui":"Q000378","qualifier_name":"metabolism","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":"D012995","descriptor_name":"Solubility","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014867","descriptor_name":"Water","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":false},{"descriptor_ui":"D001185","descriptor_name":"Artificial Intelligence","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001812","descriptor_name":"Blood-Brain Barrier","qualifier_ui":"Q000378","qualifier_name":"metabolism","is_major_topic":false},{"descriptor_ui":"D002965","descriptor_name":"Classification","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D003663","descriptor_name":"Decision Trees","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":"D051638","descriptor_name":"Ether-A-Go-Go Potassium Channels","qualifier_ui":"Q000037","qualifier_name":"antagonists & inhibitors","is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006863","descriptor_name":"Hydrogen-Ion Concentration","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007408","descriptor_name":"Intestinal Absorption","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016018","descriptor_name":"Least-Squares Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008954","descriptor_name":"Models, Biological","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016011","descriptor_name":"Normal Distribution","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004364","descriptor_name":"Pharmaceutical Preparations","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":false},{"descriptor_ui":"D004364","descriptor_name":"Pharmaceutical Preparations","qualifier_ui":"Q000378","qualifier_name":"metabolism","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":"D012995","descriptor_name":"Solubility","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D014867","descriptor_name":"Water","qualifier_ui":"Q000737","qualifier_name":"chemistry","is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1021/ci900406x","is_oa":false,"landing_page_url":"https://doi.org/10.1021/ci900406x","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:20433177","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/20433177","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}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life in Land","score":0.7699999809265137,"id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1522205938","https://openalex.org/W1563088657","https://openalex.org/W1967042264","https://openalex.org/W1984994707","https://openalex.org/W1993966269","https://openalex.org/W2000208781","https://openalex.org/W2019334008","https://openalex.org/W2025538419","https://openalex.org/W2026544535","https://openalex.org/W2049334526","https://openalex.org/W2087908817","https://openalex.org/W2107152312","https://openalex.org/W2118689184","https://openalex.org/W2125055259","https://openalex.org/W2129893339","https://openalex.org/W2133990480","https://openalex.org/W2138095345","https://openalex.org/W2157970175","https://openalex.org/W2171639300","https://openalex.org/W2911964244","https://openalex.org/W4211049957"],"related_works":["https://openalex.org/W1978803721","https://openalex.org/W1601181570","https://openalex.org/W2323673971","https://openalex.org/W2074923463","https://openalex.org/W2985122456","https://openalex.org/W3149080514","https://openalex.org/W4297683888","https://openalex.org/W2209414691","https://openalex.org/W2071057946","https://openalex.org/W3122701957"],"abstract_inverted_index":{"In":[0],"this":[1],"article,":[2],"we":[3,40],"extend":[4],"the":[5,8,34,42,46,69,103,106,118],"application":[6],"of":[7,33,45,56,71,117],"Gaussian":[9,25,35,72,107],"processes":[10,26,36,73,108],"technique":[11,28],"to":[12,52,76],"classification":[13,27,75],"quantitative":[14],"structure-activity":[15],"relationship":[16],"modeling":[17],"problems.":[18],"We":[19,66],"explore":[20],"two":[21],"approaches,":[22],"an":[23],"intrinsic":[24],"and":[29,48,62,89,125],"a":[30],"probit":[31,90],"treatment":[32],"regression":[37],"method.":[38],"Here,":[39],"describe":[41],"basic":[43],"concepts":[44],"methods":[47],"apply":[49],"these":[50],"techniques":[51],"building":[53],"category":[54],"models":[55,114],"absorption,":[57],"distribution,":[58],"metabolism,":[59],"excretion,":[60],"toxicity":[61],"target":[63],"activity":[64],"data.":[65],"also":[67],"compare":[68],"performance":[70],"for":[74],"other":[77],"known":[78],"computational":[79],"methods,":[80],"namely":[81],"decision":[82],"trees,":[83],"random":[84,119],"forest,":[85],"support":[86,122],"vector":[87,123],"machines,":[88],"partial":[91],"least":[92],"squares.":[93],"The":[94],"results":[95],"indicate":[96],"that,":[97],"while":[98],"no":[99],"method":[100],"consistently":[101],"generates":[102],"best":[104],"model,":[105],"classifier":[109],"often":[110],"produces":[111],"more":[112],"predictive":[113],"than":[115],"those":[116],"forest":[120],"or":[121],"machines":[124],"was":[126],"rarely":[127],"significantly":[128],"outperformed.":[129]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":5},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":8}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}