{"id":"https://openalex.org/W2107634512","doi":"https://doi.org/10.1109/iri.2008.4583008","title":"An unsupervised protein sequences clustering algorithm using functional domain information","display_name":"An unsupervised protein sequences clustering algorithm using functional domain information","publication_year":2008,"publication_date":"2008-01-01","ids":{"openalex":"https://openalex.org/W2107634512","doi":"https://doi.org/10.1109/iri.2008.4583008","mag":"2107634512"},"language":"en","primary_location":{"id":"doi:10.1109/iri.2008.4583008","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iri.2008.4583008","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Conference on Information Reuse and Integration","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/A5072192748","display_name":"Wei-Bang Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I32389192","display_name":"University of Alabama at Birmingham","ror":"https://ror.org/008s83205","country_code":"US","type":"education","lineage":["https://openalex.org/I32389192"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wei-Bang Chen","raw_affiliation_strings":["Department of Computer and Information Sciences, University of Alabama, Birmingham, Birmingham, AL, USA","Department of Computer and Information Sciences, University of Alabama at Birmingham, 35294, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer and Information Sciences, University of Alabama, Birmingham, Birmingham, AL, USA","institution_ids":["https://openalex.org/I32389192"]},{"raw_affiliation_string":"Department of Computer and Information Sciences, University of Alabama at Birmingham, 35294, USA","institution_ids":["https://openalex.org/I32389192"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061568662","display_name":"Chengcui Zhang","orcid":"https://orcid.org/0000-0002-5868-6450"},"institutions":[{"id":"https://openalex.org/I32389192","display_name":"University of Alabama at Birmingham","ror":"https://ror.org/008s83205","country_code":"US","type":"education","lineage":["https://openalex.org/I32389192"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chengcui Zhang","raw_affiliation_strings":["Department of Computer and Information Sciences, University of Alabama, Birmingham, Birmingham, AL, USA","Department of Computer and Information Sciences, University of Alabama at Birmingham, 35294, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer and Information Sciences, University of Alabama, Birmingham, Birmingham, AL, USA","institution_ids":["https://openalex.org/I32389192"]},{"raw_affiliation_string":"Department of Computer and Information Sciences, University of Alabama at Birmingham, 35294, USA","institution_ids":["https://openalex.org/I32389192"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038920560","display_name":"Hua Zhong","orcid":"https://orcid.org/0000-0002-8535-8225"},"institutions":[{"id":"https://openalex.org/I32389192","display_name":"University of Alabama at Birmingham","ror":"https://ror.org/008s83205","country_code":"US","type":"education","lineage":["https://openalex.org/I32389192"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hua Zhong","raw_affiliation_strings":["Department of Computer and Information Sciences, University of Alabama, Birmingham, Birmingham, AL, USA","Department of Computer and Information Sciences, University of Alabama at Birmingham, 35294, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer and Information Sciences, University of Alabama, Birmingham, Birmingham, AL, USA","institution_ids":["https://openalex.org/I32389192"]},{"raw_affiliation_string":"Department of Computer and Information Sciences, University of Alabama at Birmingham, 35294, USA","institution_ids":["https://openalex.org/I32389192"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I32389192"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"33","issue":null,"first_page":"76","last_page":"81"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12254","display_name":"Machine Learning in Bioinformatics","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/T12254","display_name":"Machine Learning in Bioinformatics","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/T10015","display_name":"Genomics and Phylogenetic Studies","score":0.996999979019165,"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":0.9919000267982483,"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":0.863831639289856},{"id":"https://openalex.org/keywords/single-linkage-clustering","display_name":"Single-linkage clustering","score":0.7945513725280762},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.6697332262992859},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.659172534942627},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6474035978317261},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.6296049356460571},{"id":"https://openalex.org/keywords/hierarchical-clustering","display_name":"Hierarchical clustering","score":0.6134186387062073},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5867874026298523},{"id":"https://openalex.org/keywords/canopy-clustering-algorithm","display_name":"Canopy clustering algorithm","score":0.5768246054649353},{"id":"https://openalex.org/keywords/brown-clustering","display_name":"Brown clustering","score":0.5585438013076782},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.506470799446106},{"id":"https://openalex.org/keywords/constrained-clustering","display_name":"Constrained clustering","score":0.46526363492012024},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.46191003918647766},{"id":"https://openalex.org/keywords/consensus-clustering","display_name":"Consensus clustering","score":0.4554975628852844},{"id":"https://openalex.org/keywords/clustering-high-dimensional-data","display_name":"Clustering high-dimensional data","score":0.43867552280426025},{"id":"https://openalex.org/keywords/data-stream-clustering","display_name":"Data stream clustering","score":0.42291259765625},{"id":"https://openalex.org/keywords/k-medians-clustering","display_name":"k-medians clustering","score":0.41213545203208923}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.863831639289856},{"id":"https://openalex.org/C22648726","wikidata":"https://www.wikidata.org/wiki/Q7523744","display_name":"Single-linkage clustering","level":5,"score":0.7945513725280762},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.6697332262992859},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.659172534942627},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6474035978317261},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.6296049356460571},{"id":"https://openalex.org/C92835128","wikidata":"https://www.wikidata.org/wiki/Q1277447","display_name":"Hierarchical clustering","level":3,"score":0.6134186387062073},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5867874026298523},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.5768246054649353},{"id":"https://openalex.org/C167984511","wikidata":"https://www.wikidata.org/wiki/Q17003931","display_name":"Brown clustering","level":5,"score":0.5585438013076782},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.506470799446106},{"id":"https://openalex.org/C27964816","wikidata":"https://www.wikidata.org/wiki/Q5164359","display_name":"Constrained clustering","level":5,"score":0.46526363492012024},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.46191003918647766},{"id":"https://openalex.org/C186767784","wikidata":"https://www.wikidata.org/wiki/Q5162841","display_name":"Consensus clustering","level":5,"score":0.4554975628852844},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.43867552280426025},{"id":"https://openalex.org/C193143536","wikidata":"https://www.wikidata.org/wiki/Q5227360","display_name":"Data stream clustering","level":5,"score":0.42291259765625},{"id":"https://openalex.org/C115328559","wikidata":"https://www.wikidata.org/wiki/Q4041956","display_name":"k-medians clustering","level":5,"score":0.41213545203208923}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iri.2008.4583008","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iri.2008.4583008","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Conference on Information Reuse and Integration","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320337398","display_name":"Division of Biological Infrastructure","ror":"https://ror.org/04qn9mx93"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W208128215","https://openalex.org/W2009570821","https://openalex.org/W2014719716","https://openalex.org/W2094454470","https://openalex.org/W2105324766","https://openalex.org/W2109681892","https://openalex.org/W2133828198","https://openalex.org/W2140190241","https://openalex.org/W2151831732","https://openalex.org/W2158714788","https://openalex.org/W3146331408","https://openalex.org/W3147254695","https://openalex.org/W6653923578"],"related_works":["https://openalex.org/W2087424554","https://openalex.org/W4312222690","https://openalex.org/W2130194910","https://openalex.org/W2121236959","https://openalex.org/W3159946074","https://openalex.org/W2476489150","https://openalex.org/W2188840951","https://openalex.org/W1981213098","https://openalex.org/W2551136488","https://openalex.org/W2473308841"],"abstract_inverted_index":{"In":[0,23,46,130],"this":[1],"paper,":[2],"we":[3,48,86],"present":[4],"an":[5,50],"unsupervised":[6,51],"novel":[7],"approach":[8],"for":[9,105,120],"protein":[10,69,93,148,162],"sequences":[11,94],"clustering":[12,21,52,61,74,82,91,103,138,161],"by":[13,31],"incorporating":[14],"the":[15,20,24,27,43,55,63,68,76,81,88,96,101,106,125,131,134,144],"functional":[16],"domain":[17,28],"information":[18],"into":[19],"process.":[22],"proposed":[25],"framework,":[26],"boundaries":[29],"predicated":[30],"ProDom":[32],"database":[33],"are":[34],"used":[35],"to":[36,66,79,99,123,142],"provide":[37],"a":[38,59,72,112,128],"better":[39],"measurement":[40],"in":[41,62,75,95,160],"calculating":[42],"sequence":[44],"similarity.":[45],"addition,":[47],"use":[49],"algorithm":[53],"as":[54,147],"kernel":[56],"that":[57],"includes":[58],"hierarchical":[60,90],"first":[64,97],"phase":[65,78,98],"pre-cluster":[67],"sequences,":[70],"and":[71,110,158],"partitioning":[73,108],"second":[77,132],"refine":[80,143],"results.":[83],"More":[84],"specifically,":[85],"perform":[87],"agglomerative":[89],"on":[92],"obtain":[100],"initial":[102],"results":[104,146,152],"subsequent":[107],"clustering,":[109],"then,":[111],"profile":[113],"Hidden":[114],"Markove":[115],"Model":[116],"(HMM)":[117],"is":[118,139,156],"built":[119],"each":[121],"cluster":[122,145],"represent":[124],"centroid":[126],"of":[127],"cluster.":[129],"phase,":[133],"HMMs":[135],"based":[136],"k-means":[137],"then":[140],"performed":[141],"families.":[149,163],"The":[150],"experimental":[151],"show":[153],"our":[154],"model":[155],"effective":[157],"efficient":[159]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
