{"id":"https://openalex.org/W2147781375","doi":"https://doi.org/10.1186/1758-2946-5-27","title":"Defining a novel k-nearest neighbours approach to assess the applicability domain of a QSAR model for reliable predictions","display_name":"Defining a novel k-nearest neighbours approach to assess the applicability domain of a QSAR model for reliable predictions","publication_year":2013,"publication_date":"2013-05-30","ids":{"openalex":"https://openalex.org/W2147781375","doi":"https://doi.org/10.1186/1758-2946-5-27","mag":"2147781375","pmid":"https://pubmed.ncbi.nlm.nih.gov/23721648"},"language":"en","primary_location":{"id":"doi:10.1186/1758-2946-5-27","is_oa":true,"landing_page_url":"https://doi.org/10.1186/1758-2946-5-27","pdf_url":"https://jcheminf.biomedcentral.com/counter/pdf/10.1186/1758-2946-5-27","source":{"id":"https://openalex.org/S180838163","display_name":"Journal of Cheminformatics","issn_l":"1758-2946","issn":["1758-2946"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Cheminformatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://jcheminf.biomedcentral.com/counter/pdf/10.1186/1758-2946-5-27","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5005183732","display_name":"Faizan Sahigara","orcid":null},"institutions":[{"id":"https://openalex.org/I66752286","display_name":"University of Milano-Bicocca","ror":"https://ror.org/01ynf4891","country_code":"IT","type":"education","lineage":["https://openalex.org/I66752286"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Faizan Sahigara","raw_affiliation_strings":["Milano Chemometrics and QSAR Research Group, Department of Earth and Environmental Sciences, University of Milano-Bicocca, P,za della Scienza 1, Milano 20126, Italy. viviana.consonni@unimib.it","Milano Chemometrics and QSAR Research Group, Department of Earth and Environmental Sciences, University of Milano-Bicocca, P.za della Scienza 1, Milano, 20126, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Milano Chemometrics and QSAR Research Group, Department of Earth and Environmental Sciences, University of Milano-Bicocca, P,za della Scienza 1, Milano 20126, Italy. viviana.consonni@unimib.it","institution_ids":[]},{"raw_affiliation_string":"Milano Chemometrics and QSAR Research Group, Department of Earth and Environmental Sciences, University of Milano-Bicocca, P.za della Scienza 1, Milano, 20126, Italy","institution_ids":["https://openalex.org/I66752286"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080605090","display_name":"Davide Ballabio","orcid":"https://orcid.org/0000-0002-5748-147X"},"institutions":[{"id":"https://openalex.org/I66752286","display_name":"University of Milano-Bicocca","ror":"https://ror.org/01ynf4891","country_code":"IT","type":"education","lineage":["https://openalex.org/I66752286"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Davide Ballabio","raw_affiliation_strings":["Milano Chemometrics and QSAR Research Group, Department of Earth and Environmental Sciences, University of Milano-Bicocca, P.za della Scienza 1, Milano, 20126, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Milano Chemometrics and QSAR Research Group, Department of Earth and Environmental Sciences, University of Milano-Bicocca, P.za della Scienza 1, Milano, 20126, Italy","institution_ids":["https://openalex.org/I66752286"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032671962","display_name":"Roberto Todeschini","orcid":"https://orcid.org/0000-0002-6454-4192"},"institutions":[{"id":"https://openalex.org/I66752286","display_name":"University of Milano-Bicocca","ror":"https://ror.org/01ynf4891","country_code":"IT","type":"education","lineage":["https://openalex.org/I66752286"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Roberto Todeschini","raw_affiliation_strings":["Milano Chemometrics and QSAR Research Group, Department of Earth and Environmental Sciences, University of Milano-Bicocca, P.za della Scienza 1, Milano, 20126, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Milano Chemometrics and QSAR Research Group, Department of Earth and Environmental Sciences, University of Milano-Bicocca, P.za della Scienza 1, Milano, 20126, Italy","institution_ids":["https://openalex.org/I66752286"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043814662","display_name":"Viviana Consonni","orcid":"https://orcid.org/0000-0001-6252-9805"},"institutions":[{"id":"https://openalex.org/I66752286","display_name":"University of Milano-Bicocca","ror":"https://ror.org/01ynf4891","country_code":"IT","type":"education","lineage":["https://openalex.org/I66752286"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Viviana Consonni","raw_affiliation_strings":["Milano Chemometrics and QSAR Research Group, Department of Earth and Environmental Sciences, University of Milano-Bicocca, P.za della Scienza 1, Milano, 20126, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Milano Chemometrics and QSAR Research Group, Department of Earth and Environmental Sciences, University of Milano-Bicocca, P.za della Scienza 1, Milano, 20126, Italy","institution_ids":["https://openalex.org/I66752286"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5005183732"],"corresponding_institution_ids":["https://openalex.org/I66752286"],"apc_list":{"value":1290,"currency":"GBP","value_usd":1582},"apc_paid":{"value":1290,"currency":"GBP","value_usd":1582},"fwci":8.192,"has_fulltext":true,"cited_by_count":107,"citation_normalized_percentile":{"value":0.98035861,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"5","issue":"1","first_page":"27","last_page":"27"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.10300000011920929,"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":0.10300000011920929,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.06729999929666519,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T13309","display_name":"Reliability and Agreement in Measurement","score":0.04830000177025795,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6872055530548096},{"id":"https://openalex.org/keywords/applicability-domain","display_name":"Applicability domain","score":0.6631889343261719},{"id":"https://openalex.org/keywords/quantitative-structure\u2013activity-relationship","display_name":"Quantitative structure\u2013activity relationship","score":0.5837559103965759},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.5777124166488647},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5220367908477783},{"id":"https://openalex.org/keywords/kernel-density-estimation","display_name":"Kernel density estimation","score":0.4943370819091797},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4655535817146301},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4616132974624634},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.4287962317466736},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.42716100811958313},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.42061352729797363},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22504284977912903},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.17307642102241516}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6872055530548096},{"id":"https://openalex.org/C107908354","wikidata":"https://www.wikidata.org/wiki/Q4781456","display_name":"Applicability domain","level":3,"score":0.6631889343261719},{"id":"https://openalex.org/C164126121","wikidata":"https://www.wikidata.org/wiki/Q766383","display_name":"Quantitative structure\u2013activity relationship","level":2,"score":0.5837559103965759},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.5777124166488647},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5220367908477783},{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.4943370819091797},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4655535817146301},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4616132974624634},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.4287962317466736},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.42716100811958313},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.42061352729797363},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22504284977912903},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.17307642102241516},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1186/1758-2946-5-27","is_oa":true,"landing_page_url":"https://doi.org/10.1186/1758-2946-5-27","pdf_url":"https://jcheminf.biomedcentral.com/counter/pdf/10.1186/1758-2946-5-27","source":{"id":"https://openalex.org/S180838163","display_name":"Journal of Cheminformatics","issn_l":"1758-2946","issn":["1758-2946"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Cheminformatics","raw_type":"journal-article"},{"id":"pmid:23721648","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/23721648","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 cheminformatics","raw_type":null},{"id":"pmh:oai:boa.unimib.it:10281/44582","is_oa":true,"landing_page_url":"http://hdl.handle.net/10281/44582","pdf_url":"http://hdl.handle.net/10281/44582","source":{"id":"https://openalex.org/S4306401259","display_name":"BOA (University of Milano-Bicocca)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I66752286","host_organization_name":"University of Milano-Bicocca","host_organization_lineage":["https://openalex.org/I66752286"],"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":null,"raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:europepmc.org:2685149","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/3679843","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1186/1758-2946-5-27","is_oa":true,"landing_page_url":"https://doi.org/10.1186/1758-2946-5-27","pdf_url":"https://jcheminf.biomedcentral.com/counter/pdf/10.1186/1758-2946-5-27","source":{"id":"https://openalex.org/S180838163","display_name":"Journal of Cheminformatics","issn_l":"1758-2946","issn":["1758-2946"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Cheminformatics","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.7099999785423279}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2147781375.pdf","grobid_xml":"https://content.openalex.org/works/W2147781375.grobid-xml"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W17944005","https://openalex.org/W919565225","https://openalex.org/W1540105270","https://openalex.org/W1551711366","https://openalex.org/W1570912112","https://openalex.org/W1571439140","https://openalex.org/W1984471054","https://openalex.org/W1989936786","https://openalex.org/W2008572210","https://openalex.org/W2012431882","https://openalex.org/W2025320861","https://openalex.org/W2070442000","https://openalex.org/W2073511756","https://openalex.org/W2080922998","https://openalex.org/W2085890279","https://openalex.org/W2089578131","https://openalex.org/W2099071242","https://openalex.org/W2125411686","https://openalex.org/W2128245586","https://openalex.org/W2129905273","https://openalex.org/W2140530403","https://openalex.org/W2176009755","https://openalex.org/W2414870557","https://openalex.org/W2801830100","https://openalex.org/W4233014035"],"related_works":["https://openalex.org/W2746158299","https://openalex.org/W2076018148","https://openalex.org/W227407425","https://openalex.org/W1969085205","https://openalex.org/W3011161038","https://openalex.org/W3117501106","https://openalex.org/W1488718676","https://openalex.org/W4382502193","https://openalex.org/W2085145070","https://openalex.org/W4376131490"],"abstract_inverted_index":{"BACKGROUND:":[0],"With":[1],"the":[2,30,56,75,105,112,121,125,134,146,160,165,169,172,178,201,206,215,229,258,283,288],"growing":[3],"popularity":[4],"of":[5,25,107,124,130,168,208,225,238,281],"using":[6],"QSAR":[7,108,209],"predictions":[8],"towards":[9],"regulatory":[10],"purposes,":[11],"such":[12],"predictive":[13],"models":[14],"are":[15,141],"now":[16],"required":[17],"to":[18,28,47,54,84,97,133,144,204,222,257,265],"be":[19,157],"strictly":[20],"validated,":[21],"an":[22],"essential":[23],"feature":[24],"which":[26,72],"is":[27,93,162,233],"have":[29,44],"model's":[31,57,289],"Applicability":[32],"Domain":[33],"(AD)":[34],"defined":[35,163],"clearly.":[36],"Although":[37],"in":[38,103,164,180,251],"recent":[39],"years":[40],"several":[41,99,244],"different":[42],"approaches":[43],"been":[45,61],"proposed":[46,91,193,216],"address":[48,98],"this":[49],"goal,":[50],"no":[51],"optimal":[52],"approach":[53,126,194,218,284],"define":[55,205],"AD":[58,70,161,207,217,290],"has":[59],"yet":[60],"recognized.":[62],"RESULTS:":[63],"This":[64],"study":[65,276],"proposes":[66],"a":[67,86,94,128,152,196,274,278],"novel":[68,197],"descriptor-based":[69],"method":[71,92,115],"accounts":[73],"for":[74,116,291],"data":[76,240],"distribution":[77,232],"and":[78,138,186,262,286],"exploits":[79],"k-Nearest":[80],"Neighbours":[81],"(kNN)":[82],"principle":[83,203],"derive":[85,145],"heuristic":[87],"decision":[88,147],"rule.":[89,148],"The":[90,192,270],"three-stage":[95],"procedure":[96],"key":[100],"aspects":[101],"relevant":[102],"judging":[104],"reliability":[106,179],"predictions.":[109,293],"Inspired":[110],"from":[111],"adaptive":[113],"kernel":[114,245],"probability":[117],"density":[118,224,246],"function":[119],"estimation,":[120],"first":[122],"stage":[123,167,174],"defines":[127,287],"pattern":[129],"thresholds":[131,140],"corresponding":[132],"various":[135,267],"training":[136],"samples":[137],"these":[139],"later":[142],"used":[143],"Criterion":[149],"deciding":[150],"if":[151],"given":[153],"test":[154],"sample":[155],"will":[156],"retained":[158],"within":[159],"second":[166],"approach.":[170],"Finally,":[171],"last":[173],"tries":[175],"reflecting":[176],"upon":[177],"derived":[181,272],"results":[182,271],"taking":[183],"model":[184],"statistics":[185],"prediction":[187],"error":[188],"into":[189],"account.":[190],"CONCLUSIONS:":[191],"addressed":[195],"strategy":[198],"that":[199,213],"integrated":[200],"kNN":[202],"models.":[210],"Relevant":[211],"features":[212],"characterize":[214],"include:":[219],"a)":[220],"adaptability":[221],"local":[223],"samples,":[226],"useful":[227],"when":[228],"underlying":[230],"multivariate":[231],"asymmetric,":[234],"with":[235],"wide":[236],"regions":[237],"low":[239,255],"density;":[241],"b)":[242],"unlike":[243],"estimators":[247],"(KDE),":[248],"effectiveness":[249],"also":[250],"high-dimensional":[252],"spaces;":[253],"c)":[254],"sensitivity":[256],"smoothing":[259],"parameter":[260],"k;":[261],"d)":[263],"versatility":[264],"implement":[266],"distances":[268],"measures.":[269],"on":[273],"case":[275],"provided":[277],"clear":[279],"understanding":[280],"how":[282],"works":[285],"reliable":[292]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":8},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":11},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":7}],"updated_date":"2026-04-29T09:16:38.111599","created_date":"2025-10-10T00:00:00"}
