{"id":"https://openalex.org/W2040167627","doi":"https://doi.org/10.1145/2147805.2147829","title":"An integrative approach to infer regulation programs in a transcription regulatory module network","display_name":"An integrative approach to infer regulation programs in a transcription regulatory module network","publication_year":2011,"publication_date":"2011-08-01","ids":{"openalex":"https://openalex.org/W2040167627","doi":"https://doi.org/10.1145/2147805.2147829","mag":"2040167627"},"language":"en","primary_location":{"id":"doi:10.1145/2147805.2147829","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2147805.2147829","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd ACM Conference on Bioinformatics, Computational Biology and Biomedicine","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/A5021106844","display_name":"Jianlong Qi","orcid":null},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Jianlong Qi","raw_affiliation_strings":["Concordia University, Montreal, Quebec, Canada"],"affiliations":[{"raw_affiliation_string":"Concordia University, Montreal, Quebec, Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061259711","display_name":"Tom Michoel","orcid":"https://orcid.org/0000-0003-4749-4725"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tom Michoel","raw_affiliation_strings":["School of Life Sciences - LifeNet, Freiburg, Germany"],"affiliations":[{"raw_affiliation_string":"School of Life Sciences - LifeNet, Freiburg, Germany","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041471776","display_name":"Gregory Butler","orcid":"https://orcid.org/0000-0002-6938-0879"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Gregory Butler","raw_affiliation_strings":["Concordia University, Montreal, Quebec, Canada"],"affiliations":[{"raw_affiliation_string":"Concordia University, Montreal, Quebec, Canada","institution_ids":["https://openalex.org/I60158472"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5021106844"],"corresponding_institution_ids":["https://openalex.org/I60158472"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08950849,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"218","last_page":"225"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.9976000189781189,"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":0.9976000189781189,"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/T10621","display_name":"Gene Regulatory Network Analysis","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/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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7204446792602539},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.5936883687973022},{"id":"https://openalex.org/keywords/gene-regulatory-network","display_name":"Gene regulatory network","score":0.5728217363357544},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5375990271568298},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.5137161016464233},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.4774214029312134},{"id":"https://openalex.org/keywords/transcription","display_name":"Transcription (linguistics)","score":0.4293181598186493},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.4143470525741577},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.41376858949661255},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37794774770736694},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.32560810446739197},{"id":"https://openalex.org/keywords/gene","display_name":"Gene","score":0.2160099446773529},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.15307071805000305},{"id":"https://openalex.org/keywords/gene-expression","display_name":"Gene expression","score":0.1409589946269989},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12693378329277039},{"id":"https://openalex.org/keywords/genetics","display_name":"Genetics","score":0.08365687727928162}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7204446792602539},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.5936883687973022},{"id":"https://openalex.org/C67339327","wikidata":"https://www.wikidata.org/wiki/Q1502576","display_name":"Gene regulatory network","level":4,"score":0.5728217363357544},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5375990271568298},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.5137161016464233},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4774214029312134},{"id":"https://openalex.org/C179926584","wikidata":"https://www.wikidata.org/wiki/Q207714","display_name":"Transcription (linguistics)","level":2,"score":0.4293181598186493},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.4143470525741577},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.41376858949661255},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37794774770736694},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.32560810446739197},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.2160099446773529},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.15307071805000305},{"id":"https://openalex.org/C150194340","wikidata":"https://www.wikidata.org/wiki/Q26972","display_name":"Gene expression","level":3,"score":0.1409589946269989},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12693378329277039},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.08365687727928162},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2147805.2147829","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2147805.2147829","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd ACM Conference on Bioinformatics, Computational Biology and Biomedicine","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W123212437","https://openalex.org/W1479933963","https://openalex.org/W1615454278","https://openalex.org/W1893022572","https://openalex.org/W1970679073","https://openalex.org/W1972764318","https://openalex.org/W2024990640","https://openalex.org/W2044525257","https://openalex.org/W2045776897","https://openalex.org/W2049633694","https://openalex.org/W2061163312","https://openalex.org/W2081098333","https://openalex.org/W2113118632","https://openalex.org/W2114268578","https://openalex.org/W2128993582","https://openalex.org/W2129265801","https://openalex.org/W2137683543","https://openalex.org/W2140665226","https://openalex.org/W2142415307","https://openalex.org/W2143076232","https://openalex.org/W2154354945","https://openalex.org/W2154664365","https://openalex.org/W2161986541","https://openalex.org/W2167190345","https://openalex.org/W2169832530","https://openalex.org/W2611370172"],"related_works":["https://openalex.org/W2348909947","https://openalex.org/W4292672442","https://openalex.org/W2362101859","https://openalex.org/W2791431590","https://openalex.org/W2941610985","https://openalex.org/W4235810826","https://openalex.org/W2350688482","https://openalex.org/W2122135111","https://openalex.org/W2053575972","https://openalex.org/W2349909726"],"abstract_inverted_index":{"The":[0,69,142,154],"module":[1,27,73,109,116],"network":[2,9,49],"method,":[3,25,199],"a":[4,26,29,106,157,202],"special":[5],"type":[6],"of":[7,31,57,71,76,92,105,136,191],"Bayesian":[8,48],"algorithms,":[10,50,178],"has":[11,201],"been":[12,98],"proposed":[13],"to":[14,46,59,65,100],"infer":[15,101],"transcription":[16,43],"regulatory":[17,127],"networks":[18,74],"from":[19,139],"gene":[20,108],"expression":[21,36],"data.":[22],"In":[23,129,193],"this":[24,51,130],"represents":[28],"set":[30],"genes,":[32],"which":[33,200],"have":[34,97],"similar":[35],"profiles":[37],"and":[38,62,84,118,150,164],"are":[39,147],"regulated":[40],"by":[41,176,214],"same":[42],"factors.":[44],"Compared":[45],"standard":[47],"design":[52],"significantly":[53],"reduces":[54],"the":[55,87,102,111,134,162,180,189,197],"number":[56],"parameters":[58],"be":[60],"learned,":[61],"consequently":[63],"leads":[64],"more":[66,170],"accurate":[67,171],"inferences.":[68],"process":[70],"learning":[72,115],"consists":[75],"two":[77],"steps:":[78],"first":[79],"clustering":[80],"genes":[81],"into":[82],"modules":[83],"then":[85],"inferring":[86],"regulation":[88,103],"program":[89,104],"(transcription":[90],"factors)":[91],"each":[93],"module.":[94],"Many":[95],"algorithms":[96,120],"designed":[99],"given":[107,175,213],"(i.e.,":[110],"second":[112],"step":[113],"in":[114,125,156,188],"networks),":[117],"these":[119],"show":[121],"very":[122],"different":[123,140],"biases":[124],"detecting":[126],"relationships.":[128],"work,":[131],"we":[132,145],"explore":[133],"possibility":[135],"integrating":[137],"results":[138,211],"algorithms.":[141],"integration":[143],"methods":[144,168],"select":[146],"union,":[148],"intersection,":[149],"weighted":[151,165],"rank":[152,166,207,215],"aggregation.":[153,216],"experiments":[155],"yeast":[158],"dataset":[159],"shows":[160],"that":[161],"union":[163,198],"aggregation":[167],"produce":[169],"predictions":[172],"than":[173,206],"those":[174],"individual":[177],"whereas":[179],"intersection":[181],"method":[182],"does":[183],"not":[184],"yield":[185],"any":[186],"improvement":[187],"accuracy":[190],"predictions.":[192],"addition,":[194],"somewhat":[195],"surprisingly,":[196],"lower":[203],"computational":[204],"cost":[205],"aggregation,":[208],"archives":[209],"comparable":[210],"as":[212]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}