{"id":"https://openalex.org/W1900839977","doi":"https://doi.org/10.5220/0004926002110220","title":"A Framework for High-throughput Gene Signatures with Microarray-based Brain Cancer Gene Expression Profiling Data","display_name":"A Framework for High-throughput Gene Signatures with Microarray-based Brain Cancer Gene Expression Profiling Data","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W1900839977","doi":"https://doi.org/10.5220/0004926002110220","mag":"1900839977"},"language":"en","primary_location":{"id":"doi:10.5220/0004926002110220","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0004926002110220","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th International Conference on Agents and Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.5220/0004926002110220","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088479280","display_name":"Hung-Ming Lai","orcid":null},"institutions":[{"id":"https://openalex.org/I183935753","display_name":"King's College London","ror":"https://ror.org/0220mzb33","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I183935753"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Hung-Ming Lai","raw_affiliation_strings":["King\u017as College London#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"King\u017as College London#TAB#","institution_ids":["https://openalex.org/I183935753"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029149047","display_name":"Andreas Albrecht","orcid":"https://orcid.org/0000-0002-9813-4319"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Andreas Albrecht","raw_affiliation_strings":[", Middlesex University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":", Middlesex University","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042428919","display_name":"Kathleen Steinh\u00f6fel","orcid":"https://orcid.org/0000-0002-9533-4649"},"institutions":[{"id":"https://openalex.org/I183935753","display_name":"King's College London","ror":"https://ror.org/0220mzb33","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I183935753"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Kathleen Steinh\u00f6fel","raw_affiliation_strings":["King\u017as College London#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"King\u017as College London#TAB#","institution_ids":["https://openalex.org/I183935753"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05096925,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"211","last_page":"220"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.9968000054359436,"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":0.9968000054359436,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9929999709129333,"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/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9886000156402588,"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/feature-selection","display_name":"Feature selection","score":0.5778029561042786},{"id":"https://openalex.org/keywords/computational-biology","display_name":"Computational biology","score":0.5514869093894958},{"id":"https://openalex.org/keywords/gene-expression-profiling","display_name":"Gene expression profiling","score":0.5482417345046997},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5444605946540833},{"id":"https://openalex.org/keywords/gene-signature","display_name":"Gene signature","score":0.5260041952133179},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5078297257423401},{"id":"https://openalex.org/keywords/gene","display_name":"Gene","score":0.4794653654098511},{"id":"https://openalex.org/keywords/throughput","display_name":"Throughput","score":0.4682377874851227},{"id":"https://openalex.org/keywords/microarray-analysis-techniques","display_name":"Microarray analysis techniques","score":0.44823214411735535},{"id":"https://openalex.org/keywords/dna-microarray","display_name":"DNA microarray","score":0.41535940766334534},{"id":"https://openalex.org/keywords/gene-expression","display_name":"Gene expression","score":0.34604668617248535},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.31601110100746155},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.26219967007637024},{"id":"https://openalex.org/keywords/genetics","display_name":"Genetics","score":0.23312053084373474}],"concepts":[{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5778029561042786},{"id":"https://openalex.org/C70721500","wikidata":"https://www.wikidata.org/wiki/Q177005","display_name":"Computational biology","level":1,"score":0.5514869093894958},{"id":"https://openalex.org/C18431079","wikidata":"https://www.wikidata.org/wiki/Q1502169","display_name":"Gene expression profiling","level":4,"score":0.5482417345046997},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5444605946540833},{"id":"https://openalex.org/C2779733811","wikidata":"https://www.wikidata.org/wiki/Q5531562","display_name":"Gene signature","level":4,"score":0.5260041952133179},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5078297257423401},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.4794653654098511},{"id":"https://openalex.org/C157764524","wikidata":"https://www.wikidata.org/wiki/Q1383412","display_name":"Throughput","level":3,"score":0.4682377874851227},{"id":"https://openalex.org/C8415881","wikidata":"https://www.wikidata.org/wiki/Q6839217","display_name":"Microarray analysis techniques","level":4,"score":0.44823214411735535},{"id":"https://openalex.org/C95371953","wikidata":"https://www.wikidata.org/wiki/Q591745","display_name":"DNA microarray","level":4,"score":0.41535940766334534},{"id":"https://openalex.org/C150194340","wikidata":"https://www.wikidata.org/wiki/Q26972","display_name":"Gene expression","level":3,"score":0.34604668617248535},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.31601110100746155},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26219967007637024},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.23312053084373474},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.5220/0004926002110220","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0004926002110220","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th International Conference on Agents and Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.5220/0004926002110220","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0004926002110220","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th International Conference on Agents and Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17","score":0.4099999964237213}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2069695727","https://openalex.org/W1996185163","https://openalex.org/W2084813257","https://openalex.org/W2043690326","https://openalex.org/W2045929470","https://openalex.org/W4233500668","https://openalex.org/W2081127504","https://openalex.org/W1974145978","https://openalex.org/W1977867163","https://openalex.org/W3984577"],"abstract_inverted_index":{"Cancer":[0],"classification":[1,139],"through":[2],"high-throughput":[3,78,194],"gene":[4,24,69,90,175,185,195,198],"expression":[5,91],"profiles":[6,92],"has":[7,82,152],"been":[8,84,153,165],"widely":[9],"used":[10,124],"in":[11,110,136,155,183],"biomedical":[12],"research.":[13],"Most":[14],"recently,":[15],"we":[16,56],"portrayed":[17],"a":[18,31,42,63,68,72,87],"multivariate":[19],"method":[20,60],"for":[21,71,125,193],"large":[22],"scale":[23],"selection":[25,196],"based":[26,121],"on":[27],"information":[28,119],"theorem":[29,120],"with":[30,141],"central":[32],"issue":[33],"of":[34,138,160],"feature":[35,150],"interdependence":[36,151],"and":[37,61,177],"validated":[38],"its":[39],"effectiveness":[40],"using":[41],"colon":[43,114],"cancer":[44,89,115],"benchmark.":[45],"The":[46,80,167],"completed":[47],"research":[48],"work":[49],"now":[50],"contributes":[51],"to":[52,66,86,146],"this":[53,188],"article.":[54],"Firstly,":[55],"have":[57,163],"refined":[58],"the":[59,101,111,132,156],"proposed":[62],"complete":[64],"framework":[65,81,133,189],"select":[67],"signature":[70],"certain":[73],"disease":[74],"phenotype":[75],"prediction":[76],"under":[77],"technologies.":[79],"then":[83],"applied":[85],"brain":[88],"derived":[93],"from":[94],"Affymetrix":[95],"Human":[96],"Genome":[97],"U95Av2":[98],"Array,":[99],"where":[100],"interrogated":[102],"genes":[103],"are":[104],"six":[105],"times":[106],"more":[107,172],"than":[108],"that":[109,131,171],"previous":[112],"studied":[113],"data":[116],"set.":[117],"Three":[118],"filters":[122],"were":[123],"comparison.":[126],"Our":[127],"experimental":[128],"result":[129],"shows":[130],"outperformed":[134],"them":[135],"terms":[137],"performance":[140,143],"three":[142],"measures.":[144],"Additionally,":[145],"demonstrate":[147],"how":[148],"effectively":[149],"tackled":[154],"framework,":[157],"two":[158],"sets":[159,176],"enrichment":[161],"analysis":[162],"also":[164,169],"performed.":[166],"results":[168],"show":[170],"statistically":[173],"significant":[174],"regulatory":[178],"interactions":[179],"could":[180,190],"be":[181,191],"found":[182],"our":[184],"signature.":[186],"Therefore,":[187],"promising":[192],"around":[197],"synergy.":[199]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2016-06-24T00:00:00"}
