{"id":"https://openalex.org/W2128167103","doi":"https://doi.org/10.1186/1758-2946-5-s1-o14","title":"Dataset overlap density analysis","display_name":"Dataset overlap density analysis","publication_year":2013,"publication_date":"2013-03-01","ids":{"openalex":"https://openalex.org/W2128167103","doi":"https://doi.org/10.1186/1758-2946-5-s1-o14","mag":"2128167103"},"language":"en","primary_location":{"id":"doi:10.1186/1758-2946-5-s1-o14","is_oa":true,"landing_page_url":"https://doi.org/10.1186/1758-2946-5-s1-o14","pdf_url":"https://jcheminf.biomedcentral.com/track/pdf/10.1186/1758-2946-5-S1-O14","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"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://jcheminf.biomedcentral.com/track/pdf/10.1186/1758-2946-5-S1-O14","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5067864075","display_name":"Andreas H. G\u00f6ller","orcid":"https://orcid.org/0000-0003-4343-4063"},"institutions":[{"id":"https://openalex.org/I67348948","display_name":"Bayer (Germany)","ror":"https://ror.org/04hmn8g73","country_code":"DE","type":"company","lineage":["https://openalex.org/I67348948"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Andreas H G\u00f6ller","raw_affiliation_strings":["Bayer Schering Pharma AG, Computational Chemistry, Wuppertal, Germany"],"affiliations":[{"raw_affiliation_string":"Bayer Schering Pharma AG, Computational Chemistry, Wuppertal, Germany","institution_ids":["https://openalex.org/I67348948"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5067864075"],"corresponding_institution_ids":["https://openalex.org/I67348948"],"apc_list":{"value":1290,"currency":"GBP","value_usd":1582},"apc_paid":{"value":1290,"currency":"GBP","value_usd":1582},"fwci":2.2415,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.88538381,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"5","issue":"S1","first_page":null,"last_page":null},"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/T10908","display_name":"Analytical Chemistry and Chromatography","score":0.9879000186920166,"subfield":{"id":"https://openalex.org/subfields/1607","display_name":"Spectroscopy"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10836","display_name":"Metabolomics and Mass Spectrometry Studies","score":0.9199000000953674,"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/chembl","display_name":"chEMBL","score":0.8060516119003296},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6901925206184387},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6656965017318726},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.6061767935752869},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.5709031224250793},{"id":"https://openalex.org/keywords/pubchem","display_name":"PubChem","score":0.558972179889679},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5393990874290466},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.5079894661903381},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.46917229890823364},{"id":"https://openalex.org/keywords/cheminformatics","display_name":"Cheminformatics","score":0.4533878266811371},{"id":"https://openalex.org/keywords/property","display_name":"Property (philosophy)","score":0.4160744845867157},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40065181255340576},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3260318636894226},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.22342965006828308},{"id":"https://openalex.org/keywords/drug-discovery","display_name":"Drug discovery","score":0.18386951088905334},{"id":"https://openalex.org/keywords/bioinformatics","display_name":"Bioinformatics","score":0.10495439171791077}],"concepts":[{"id":"https://openalex.org/C63222358","wikidata":"https://www.wikidata.org/wiki/Q6120337","display_name":"chEMBL","level":3,"score":0.8060516119003296},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6901925206184387},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6656965017318726},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.6061767935752869},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.5709031224250793},{"id":"https://openalex.org/C158180186","wikidata":"https://www.wikidata.org/wiki/Q278487","display_name":"PubChem","level":2,"score":0.558972179889679},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5393990874290466},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.5079894661903381},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.46917229890823364},{"id":"https://openalex.org/C68762167","wikidata":"https://www.wikidata.org/wiki/Q910164","display_name":"Cheminformatics","level":2,"score":0.4533878266811371},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.4160744845867157},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40065181255340576},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3260318636894226},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.22342965006828308},{"id":"https://openalex.org/C74187038","wikidata":"https://www.wikidata.org/wiki/Q1418791","display_name":"Drug discovery","level":2,"score":0.18386951088905334},{"id":"https://openalex.org/C60644358","wikidata":"https://www.wikidata.org/wiki/Q128570","display_name":"Bioinformatics","level":1,"score":0.10495439171791077},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1186/1758-2946-5-s1-o14","is_oa":true,"landing_page_url":"https://doi.org/10.1186/1758-2946-5-s1-o14","pdf_url":"https://jcheminf.biomedcentral.com/track/pdf/10.1186/1758-2946-5-S1-O14","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":"pmh:oai:europepmc.org:2605479","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/3606206","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-s1-o14","is_oa":true,"landing_page_url":"https://doi.org/10.1186/1758-2946-5-s1-o14","pdf_url":"https://jcheminf.biomedcentral.com/track/pdf/10.1186/1758-2946-5-S1-O14","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":[{"score":0.4399999976158142,"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2128167103.pdf","grobid_xml":"https://content.openalex.org/works/W2128167103.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4249248884","https://openalex.org/W2920928233","https://openalex.org/W4240782442","https://openalex.org/W3201640553","https://openalex.org/W4386453949","https://openalex.org/W4386823632","https://openalex.org/W1968888975","https://openalex.org/W2770765812","https://openalex.org/W2460225311","https://openalex.org/W2079781933"],"abstract_inverted_index":{"The":[0,47,69,200,296],"need":[1],"to":[2,32,79,101,111,220,272,279,315],"compare":[3],"compound":[4],"datasets":[5,117,322],"arises":[6],"from":[7,146,159,174],"various":[8,48],"scenarios,":[9],"like":[10],"mergers,":[11],"library":[12,18],"extension":[13],"programs,":[14],"gap":[15],"analysis,":[16],"combinatorial":[17],"design,":[19],"or":[20,61,141,319],"estimation":[21],"of":[22,41,63,83,115,180,205,208,216,225,229,264,292],"QSAR":[23],"model":[24],"applicability":[25],"domains.":[26],"Whereas":[27],"it":[28,106],"is":[29,44,105,172,211,241,270],"relatively":[30],"easy":[31],"find":[33],"identical":[34],"compounds":[35],"in":[36,98,118,238,261],"two":[37,116,209],"datasets,":[38,188],"the":[39,42,81,113,126,147,164,175,178,206,214,226,230,265,293,328,337],"quantification":[40],"overlap":[43,114,168,207],"not":[45,242],"straightforward.":[46],"approaches":[49],"described":[50],"include":[51],"pairwise":[52],"nearest":[53],"neighbor":[54],"comparisons,":[55],"clustering":[56],"and":[57,77,95,108,154,234,255,258],"mixed":[58,84],"cluster":[59],"statistics,":[60],"binning":[62],"e.g.":[64],"rule-of-five":[65],"property":[66,99],"space":[67,76,100,133],"distributions.":[68],"BCUT":[70],"methodology":[71],"creates":[72,87],"a":[73,88,119,155,203,236,280,307],"binned":[74],"N-dimensional":[75,182,245,267],"allows":[78,314],"assess":[80],"amount":[82],"cells.":[85],"ChemGPS":[86],"PCA":[89],"reference":[90,132],"projection":[91,123,237],"based":[92,136,283,310],"on":[93,137,284,311],"drug-like":[94,131],"satellite":[96],"molecules":[97],"classify":[102],"new":[103],"compounds.\r\n\r\nBut":[104],"possible":[107],"also":[109],"plausible":[110],"quantify":[112,316],"single":[120],"interpretable":[121],"number?\r\n\r\nPCA":[122],"models":[124],"with":[125],"World":[127],"Drug":[128],"Index":[129],"as":[130,304],"were":[134,161],"created":[135],"MACCS,":[138],"ECFP4,":[139],"estate":[140],"Lipinsky-like":[142],"physchem":[143],"descriptors.":[144],"Compounds":[145],"commercial":[148],"vendor":[149],"i-research":[150],"library,":[151],"ZINC,":[152],"ChEMBL":[153],"current":[156],"screening":[157],"subset":[158],"PubChem":[160],"projected":[162],"onto":[163],"WDI":[165,254],"maps.\r\n\r\nThe":[166],"dataset":[167],"density":[169],"index":[170,201],"DOD":[171,281],"calculated":[173],"summations":[176],"over":[177],"occupancies":[179],"each":[181,288],"volume":[183],"element":[184,298],"occupied":[185],"by":[186,190,195,327],"both":[187],"divided":[189],"all":[191],"such":[192],"elements":[193,252],"populated":[194],"at":[196,222],"least":[197,223],"one":[198],"dataset.":[199],"provides":[202],"measure":[204],"sets.\r\n\r\nIt":[210],"shown":[212],"that":[213,235],"number":[215],"principal":[217,331],"components":[218],"needed":[219,305],"describe":[221],"75%":[224],"information":[227],"content":[228],"descriptor":[231,286],"greatly":[232],"varies":[233],"2":[239],"dimensions":[240],"adequate.":[243],"Such":[244],"projections":[246],"are":[247],"extremely":[248],"sparse":[249],"(about":[250],"1043":[251],"for":[253,306],"MACCS":[256],"descriptor)":[257],"crowded":[259],"only":[260],"small":[262],"regions":[263],"spanned":[266],"space.\r\n\r\nThe":[268],"approach":[269],"universal":[271],"any":[273],"descriptor.":[274],"It":[275,313],"can":[276,300,323],"be":[277,301,324],"extended":[278],"vector":[282],"different":[285,290],"types":[287],"describes":[289],"characteristics":[291],"encoded":[294],"molecules.":[295],"box":[297],"graining":[299],"easily":[302],"adjusted":[303],"particular":[308],"application.":[309],"needs.":[312],"local":[317],"gaps":[318],"overlaps.":[320],"Proprietary":[321],"compared":[325],"just":[326],"first":[329],"N":[330],"component":[332],"values":[333],"without":[334],"even":[335],"seeing":[336],"descriptors":[338],"behind.":[339]},"counts_by_year":[{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
