{"id":"https://openalex.org/W2071874129","doi":"https://doi.org/10.1109/icde.2008.4497515","title":"Scalable Rule-Based Gene Expression Data Classification","display_name":"Scalable Rule-Based Gene Expression Data Classification","publication_year":2008,"publication_date":"2008-04-01","ids":{"openalex":"https://openalex.org/W2071874129","doi":"https://doi.org/10.1109/icde.2008.4497515","mag":"2071874129"},"language":"en","primary_location":{"id":"doi:10.1109/icde.2008.4497515","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icde.2008.4497515","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE 24th International Conference on Data Engineering","raw_type":"proceedings-article"},"type":"conference-paper","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/A5004103671","display_name":"Mark Iwen","orcid":"https://orcid.org/0000-0002-8854-3186"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mark A. Iwen","raw_affiliation_strings":["Department of Mathematics, University of Michigan, USA","Dept. of Math., Univ. of Michigan, Ann Arbor, MI"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, University of Michigan, USA","institution_ids":["https://openalex.org/I27837315"]},{"raw_affiliation_string":"Dept. of Math., Univ. of Michigan, Ann Arbor, MI","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038895307","display_name":"Willis Lang","orcid":"https://orcid.org/0009-0005-0365-9892"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Willis Lang","raw_affiliation_strings":["EECS Department, University of Michigan, USA","EECS Department, University of Michigan, USA. wlang@eecs.umich.edu"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"EECS Department, University of Michigan, USA","institution_ids":["https://openalex.org/I27837315"]},{"raw_affiliation_string":"EECS Department, University of Michigan, USA. wlang@eecs.umich.edu","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069237428","display_name":"Jignesh M. Patel","orcid":"https://orcid.org/0000-0003-3653-2538"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jignesh M. Patel","raw_affiliation_strings":["EECS Department, University of Michigan, USA","EECS Department, University of Michigan, USA. jignesh@eecs.umich.edu#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"EECS Department, University of Michigan, USA","institution_ids":["https://openalex.org/I27837315"]},{"raw_affiliation_string":"EECS Department, University of Michigan, USA. jignesh@eecs.umich.edu#TAB#","institution_ids":["https://openalex.org/I27837315"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I27837315"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1062","last_page":"1071"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10885","display_name":"Gene expression and cancer classification","score":0.9937999844551086,"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/T11269","display_name":"Algorithms and Data Compression","score":0.9873999953269958,"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/association-rule-learning","display_name":"Association rule learning","score":0.7761787176132202},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7304570078849792},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6587672233581543},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6391212940216064},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5756539106369019},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.5476526021957397},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4575793147087097},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44285884499549866},{"id":"https://openalex.org/keywords/rule-induction","display_name":"Rule induction","score":0.43593764305114746},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3347013592720032}],"concepts":[{"id":"https://openalex.org/C193524817","wikidata":"https://www.wikidata.org/wiki/Q386780","display_name":"Association rule learning","level":2,"score":0.7761787176132202},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7304570078849792},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6587672233581543},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6391212940216064},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5756539106369019},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.5476526021957397},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4575793147087097},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44285884499549866},{"id":"https://openalex.org/C2776780472","wikidata":"https://www.wikidata.org/wiki/Q7378945","display_name":"Rule induction","level":2,"score":0.43593764305114746},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3347013592720032},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icde.2008.4497515","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icde.2008.4497515","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE 24th International Conference on Data Engineering","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.130.582","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.130.582","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.eecs.umich.edu/~jignesh/publ/bst.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals","score":0.4000000059604645}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1484413656","https://openalex.org/W1520460729","https://openalex.org/W1966280301","https://openalex.org/W2038812321","https://openalex.org/W2045735774","https://openalex.org/W2078698965","https://openalex.org/W2105260718","https://openalex.org/W2111254498","https://openalex.org/W2119821739","https://openalex.org/W2125208521","https://openalex.org/W2143692243","https://openalex.org/W2147864684","https://openalex.org/W2153635508","https://openalex.org/W2154642793","https://openalex.org/W2160605849","https://openalex.org/W2162034534","https://openalex.org/W2166559705","https://openalex.org/W2167681385","https://openalex.org/W2171612826","https://openalex.org/W2295428206","https://openalex.org/W2296330440","https://openalex.org/W2911964244","https://openalex.org/W3120421331","https://openalex.org/W4231916799","https://openalex.org/W4239510810","https://openalex.org/W4285719527","https://openalex.org/W6628750762","https://openalex.org/W6683599321","https://openalex.org/W6684495928"],"related_works":["https://openalex.org/W2751920613","https://openalex.org/W2415164632","https://openalex.org/W2238349241","https://openalex.org/W2355668701","https://openalex.org/W2370453500","https://openalex.org/W3012205960","https://openalex.org/W2079402849","https://openalex.org/W4312723892","https://openalex.org/W2783065147","https://openalex.org/W4254396342"],"abstract_inverted_index":{"Current":[0],"state-of-the-art":[1],"association":[2,63,100,129,164,177,217],"rule-based":[3,64,84,101,130,165,178],"classifiers":[4],"for":[5,161],"gene":[6,72,85,117],"expression":[7,73,86,118],"data":[8,19,26,48,87,225],"operate":[9],"in":[10,204],"two":[11,59,173],"phases:":[12],"(i)":[13,180],"Association":[14],"rule":[15],"mining":[16,226],"from":[17],"training":[18,47],"followed":[20],"by":[21],"(ii)":[22,191],"Classification":[23,93],"of":[24,45,57,81,127,135,200,207,215],"query":[25],"using":[27],"the":[28,32,42,46,79,124,139,205],"mined":[29],"rules.":[30],"In":[31],"worst":[33],"case,":[34],"these":[35,58],"methods":[36,131,166],"require":[37],"an":[38],"exponential":[39],"search":[40],"over":[41,176],"subset":[43],"space":[44],"set's":[49],"samples":[50],"and/or":[51],"genes":[52],"during":[53],"at":[54],"least":[55],"one":[56],"phases.":[60],"Hence,":[61],"existing":[62],"techniques":[65],"are":[66],"prohibitively":[67],"computationally":[68,168],"expensive":[69],"on":[70,114,143,158],"large":[71,144,159],"datasets.":[74,145],"Our":[75],"main":[76],"result":[77],"is":[78,96,104,150,182],"development":[80],"a":[82,147,212],"heuristic":[83],"classifier":[88,141],"called":[89],"Boolean":[90,216],"Structure":[91],"Table":[92],"(BSTC).":[94],"BSTC":[95,122,149,170,181,192,209],"explicitly":[97],"related":[98],"to":[99,106,152,184,223],"methods,":[102],"but":[103],"guaranteed":[105],"be":[107],"polynomial":[108],"space/time.":[109],"Extensive":[110],"cross":[111],"validation":[112],"studies":[113],"several":[115],"real":[116],"datasets":[119,160,196],"demonstrate":[120],"that":[121],"retains":[123],"classification":[125,157],"accuracy":[126],"current":[128,163],"while":[132],"being":[133],"orders":[134],"magnitude":[136],"faster":[137],"than":[138],"leading":[140],"RCBT":[142],"As":[146],"result,":[148],"able":[151],"finish":[153],"table":[154],"generation":[155],"and":[156,190],"which":[162,219],"become":[167],"infeasible.":[169],"also":[171],"enjoys":[172],"other":[174,224],"advantages":[175],"classifiers:":[179],"easy":[183],"use":[185],"(requires":[186],"no":[187],"parameter":[188],"tuning),":[189],"can":[193],"easily":[194],"handle":[195],"with":[197],"any":[198],"number":[199],"class":[201,214],"types.":[202],"Furthermore,":[203],"process":[206],"developing":[208],"we":[210],"introduce":[211],"novel":[213],"rules":[218],"have":[220],"potential":[221],"applications":[222],"problems.":[227]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}