{"id":"https://openalex.org/W1966854728","doi":"https://doi.org/10.1145/1141277.1141311","title":"Two-phase clustering strategy for gene expression data sets","display_name":"Two-phase clustering strategy for gene expression data sets","publication_year":2006,"publication_date":"2006-04-23","ids":{"openalex":"https://openalex.org/W1966854728","doi":"https://doi.org/10.1145/1141277.1141311","mag":"1966854728"},"language":"en","primary_location":{"id":"doi:10.1145/1141277.1141311","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1141277.1141311","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2006 ACM symposium on Applied computing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"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/A5057703543","display_name":"Dirk Habich","orcid":"https://orcid.org/0000-0002-8671-5466"},"institutions":[{"id":"https://openalex.org/I78650965","display_name":"TU Dresden","ror":"https://ror.org/042aqky30","country_code":"DE","type":"education","lineage":["https://openalex.org/I78650965"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Dirk Habich","raw_affiliation_strings":["Dresden University of Technology, Germany","Dresden University of Technology, Germany,"],"affiliations":[{"raw_affiliation_string":"Dresden University of Technology, Germany","institution_ids":["https://openalex.org/I78650965"]},{"raw_affiliation_string":"Dresden University of Technology, Germany,","institution_ids":["https://openalex.org/I78650965"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083599531","display_name":"Thomas W\u00e4chter","orcid":null},"institutions":[{"id":"https://openalex.org/I78650965","display_name":"TU Dresden","ror":"https://ror.org/042aqky30","country_code":"DE","type":"education","lineage":["https://openalex.org/I78650965"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Thomas W\u00e4chter","raw_affiliation_strings":["Dresden University of Technology, Germany","Dresden University of Technology, Germany,"],"affiliations":[{"raw_affiliation_string":"Dresden University of Technology, Germany","institution_ids":["https://openalex.org/I78650965"]},{"raw_affiliation_string":"Dresden University of Technology, Germany,","institution_ids":["https://openalex.org/I78650965"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063512642","display_name":"Wolfgang Lehner","orcid":"https://orcid.org/0000-0001-8107-2775"},"institutions":[{"id":"https://openalex.org/I78650965","display_name":"TU Dresden","ror":"https://ror.org/042aqky30","country_code":"DE","type":"education","lineage":["https://openalex.org/I78650965"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Wolfgang Lehner","raw_affiliation_strings":["Dresden University of Technology, Germany","Dresden University of Technology, Germany,"],"affiliations":[{"raw_affiliation_string":"Dresden University of Technology, Germany","institution_ids":["https://openalex.org/I78650965"]},{"raw_affiliation_string":"Dresden University of Technology, Germany,","institution_ids":["https://openalex.org/I78650965"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014489598","display_name":"Christian Pilarsky","orcid":"https://orcid.org/0000-0002-7968-3283"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Christian Pilarsky","raw_affiliation_strings":["Dresden University of Technology"],"affiliations":[{"raw_affiliation_string":"Dresden University of Technology","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5057703543"],"corresponding_institution_ids":["https://openalex.org/I78650965"],"apc_list":null,"apc_paid":null,"fwci":1.0864,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.73585838,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"145","last_page":"150"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.9990000128746033,"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"}},"topics":[{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.9990000128746033,"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/T10057","display_name":"Face and Expression Recognition","score":0.9689000248908997,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11269","display_name":"Algorithms and Data Compression","score":0.9672999978065491,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.8533474802970886},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6683010458946228},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6087918877601624},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.6025316715240479},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.600621223449707},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5218376517295837},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.47171562910079956},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2578392028808594},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.12805309891700745}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8533474802970886},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6683010458946228},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6087918877601624},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.6025316715240479},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.600621223449707},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5218376517295837},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.47171562910079956},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2578392028808594},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.12805309891700745},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"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/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1141277.1141311","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1141277.1141311","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2006 ACM symposium on Applied computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W204885769","https://openalex.org/W1492289968","https://openalex.org/W1493217831","https://openalex.org/W1493454437","https://openalex.org/W1521624597","https://openalex.org/W1556860917","https://openalex.org/W1560979799","https://openalex.org/W1673310716","https://openalex.org/W1945743004","https://openalex.org/W1981038597","https://openalex.org/W2001731844","https://openalex.org/W2087213683","https://openalex.org/W2095897464","https://openalex.org/W2129905273","https://openalex.org/W2133249310","https://openalex.org/W2152393478","https://openalex.org/W2506348433","https://openalex.org/W2999729612","https://openalex.org/W4233014035","https://openalex.org/W6629329278"],"related_works":["https://openalex.org/W2180954594","https://openalex.org/W2052835778","https://openalex.org/W2027108423","https://openalex.org/W1855666948","https://openalex.org/W2758561209","https://openalex.org/W1548095260","https://openalex.org/W2594414941","https://openalex.org/W2781711915","https://openalex.org/W2112817590","https://openalex.org/W1555291398"],"abstract_inverted_index":{"In":[0,63],"the":[1,6,25,57,77,119,143,148,153,157,160,165],"context":[2],"of":[3,8,32,43,60,79,90,108,156],"genome":[4],"research,":[5],"method":[7],"gene":[9],"expression":[10],"analysis":[11],"has":[12],"been":[13],"used":[14,116],"for":[15,141],"several":[16],"years.":[17],"Related":[18],"microarray":[19,33,97],"experiments":[20],"are":[21,36],"conducted":[22],"all":[23],"over":[24],"world,":[26],"and":[27,103],"consequently,":[28],"a":[29,68,85,92],"vast":[30],"amount":[31],"data":[34,51,98],"sets":[35],"produced.":[37],"Having":[38],"access":[39],"to":[40,48,55,83,117,137],"this":[41,50,64],"variety":[42],"repositories,":[44],"researchers":[45],"would":[46],"like":[47],"incorporate":[49],"in":[52],"their":[53,61,162],"analyses":[54],"increase":[56],"statistical":[58],"significance":[59],"results.":[62],"paper,":[65],"we":[66,124],"present":[67,125],"new":[69],"two-phase":[70],"clustering":[71,81,112,121],"strategy":[72],"which":[73],"is":[74,94,114],"based":[75,128],"on":[76,129,164],"combination":[78],"local":[80,111,144,158],"results":[82,113,145],"obtain":[84],"global":[86,120,149,166],"clustering.":[87],"The":[88,106,151],"advantage":[89],"such":[91],"technique":[93],"that":[95],"each":[96],"set":[99,107],"can":[100],"be":[101],"normalized":[102],"clustered":[104],"separately.":[105],"different":[109],"relevant":[110],"then":[115],"calculate":[118],"result.":[122,150,167],"Furthermore,":[123],"an":[126],"approach":[127],"technical":[130],"as":[131,133],"well":[132],"biological":[134],"quality":[135,155],"measures":[136],"determine":[138],"weighting":[139],"factors":[140],"quantifying":[142],"proportion":[146],"within":[147],"better":[152],"attested":[154],"results,":[159],"stronger":[161],"impact":[163]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
