{"id":"https://openalex.org/W2571752074","doi":"https://doi.org/10.1109/bibm.2016.7822497","title":"Learning regulatory motifs by direct optimization of Fisher Exact Test Score","display_name":"Learning regulatory motifs by direct optimization of Fisher Exact Test Score","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2571752074","doi":"https://doi.org/10.1109/bibm.2016.7822497","mag":"2571752074"},"language":"en","primary_location":{"id":"doi:10.1109/bibm.2016.7822497","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm.2016.7822497","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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/A5100664608","display_name":"Lin Zhu","orcid":"https://orcid.org/0000-0001-9872-459X"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lin Zhu","raw_affiliation_strings":["College of Electronics and Information Engineering, Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"College of Electronics and Information Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100368980","display_name":"Ning Li","orcid":"https://orcid.org/0000-0001-8472-3983"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ning Li","raw_affiliation_strings":["College of Electronics and Information Engineering, Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"College of Electronics and Information Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030950144","display_name":"Wenzheng Bao","orcid":"https://orcid.org/0000-0002-1471-5432"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenzheng Bao","raw_affiliation_strings":["College of Electronics and Information Engineering, Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"College of Electronics and Information Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113558338","display_name":"De-Shuang Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"De-Shuang Huang","raw_affiliation_strings":["College of Electronics and Information Engineering, Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"College of Electronics and Information Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100664608"],"corresponding_institution_ids":["https://openalex.org/I116953780"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.10818769,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"12","issue":null,"first_page":"86","last_page":"91"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10222","display_name":"Genomics and Chromatin Dynamics","score":0.9998000264167786,"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/T10222","display_name":"Genomics and Chromatin Dynamics","score":0.9998000264167786,"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/T11970","display_name":"Molecular Biology Techniques and Applications","score":0.998199999332428,"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/T10521","display_name":"RNA and protein synthesis mechanisms","score":0.9959999918937683,"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/hypergeometric-distribution","display_name":"Hypergeometric distribution","score":0.6193534731864929},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6169308423995972},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.5721786618232727},{"id":"https://openalex.org/keywords/differentiable-function","display_name":"Differentiable function","score":0.4850822985172272},{"id":"https://openalex.org/keywords/exact-test","display_name":"Exact test","score":0.420947790145874},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.41841191053390503},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33644920587539673},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3227561116218567},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3013383746147156},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11363953351974487}],"concepts":[{"id":"https://openalex.org/C176671685","wikidata":"https://www.wikidata.org/wiki/Q730600","display_name":"Hypergeometric distribution","level":2,"score":0.6193534731864929},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6169308423995972},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.5721786618232727},{"id":"https://openalex.org/C202615002","wikidata":"https://www.wikidata.org/wiki/Q783507","display_name":"Differentiable function","level":2,"score":0.4850822985172272},{"id":"https://openalex.org/C191093355","wikidata":"https://www.wikidata.org/wiki/Q9250577","display_name":"Exact test","level":2,"score":0.420947790145874},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41841191053390503},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33644920587539673},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3227561116218567},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3013383746147156},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11363953351974487},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm.2016.7822497","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm.2016.7822497","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.699999988079071}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1019830208","https://openalex.org/W1978201669","https://openalex.org/W1981093360","https://openalex.org/W1988599715","https://openalex.org/W1997930876","https://openalex.org/W1999301653","https://openalex.org/W2014677321","https://openalex.org/W2022712430","https://openalex.org/W2022736304","https://openalex.org/W2031140266","https://openalex.org/W2033855745","https://openalex.org/W2041306584","https://openalex.org/W2051680981","https://openalex.org/W2074307047","https://openalex.org/W2079035862","https://openalex.org/W2085289814","https://openalex.org/W2090123586","https://openalex.org/W2092988184","https://openalex.org/W2097175728","https://openalex.org/W2099901383","https://openalex.org/W2124823957","https://openalex.org/W2130740571","https://openalex.org/W2131263703","https://openalex.org/W2135621733","https://openalex.org/W2145955247","https://openalex.org/W2150029909","https://openalex.org/W2150248355","https://openalex.org/W2150573567","https://openalex.org/W2155925461","https://openalex.org/W2156661861","https://openalex.org/W2157758083","https://openalex.org/W2159324718","https://openalex.org/W2168341872","https://openalex.org/W2221564667","https://openalex.org/W2259938310","https://openalex.org/W2295745415"],"related_works":["https://openalex.org/W2468279273","https://openalex.org/W2354198838","https://openalex.org/W1989130879","https://openalex.org/W4285277090","https://openalex.org/W2103419012","https://openalex.org/W4327738859","https://openalex.org/W2988126442","https://openalex.org/W2152274187","https://openalex.org/W2001783515","https://openalex.org/W2049618312"],"abstract_inverted_index":{"Built":[0],"upon":[1],"the":[2,5,20,34,105,125,134,144,154,186,215,218],"hypergeometric":[3],"distribution,":[4],"Fisher":[6],"Exact":[7],"Test":[8],"score":[9],"(FETS)":[10],"and":[11,29,48,55,60,62,100,173],"its":[12,53],"variants":[13],"offer":[14],"a":[15,92,151,162,176,204],"natural":[16],"way":[17],"of":[18,22,37,52,91,107,133,157,182,193,195,217],"quantifying":[19],"level":[21],"TF":[23],"binding":[24],"site":[25],"(TFBS)":[26],"motif":[27,42,135],"enrichment,":[28],"have":[30,81],"been":[31],"chosen":[32],"as":[33,46],"objective":[35],"functions":[36],"several":[38],"widely":[39],"used":[40],"discriminant":[41],"discovery":[43],"methods,":[44],"such":[45],"HOMER":[47],"DREME.":[49],"In":[50,113],"spite":[51],"popularity":[54],"efficacy,":[56],"FETS":[57,79],"is":[58,63,120,148,161,200],"non-smooth":[59],"non-differentiable,":[61],"thus":[64],"difficult":[65],"to":[66,77,82,102,110],"optimize":[67,78],"numerically.":[68],"To":[69],"circumvent":[70],"this":[71,114],"limitation,":[72],"existing":[73],"tools":[74],"that":[75,129,142],"learn":[76],"either":[80],"rely":[83],"on":[84,210],"discrete":[85],"search":[86],"strategies":[87],"or":[88],"indirect":[89],"tuning":[90],"few":[93],"external":[94],"parameters,":[95],"which":[96,119,199],"could":[97],"hurt":[98],"accuracy":[99],"fail":[101],"fully":[103],"utilize":[104],"potential":[106],"input":[108],"sequences":[109],"generate":[111],"motifs.":[112],"paper,":[115],"we":[116],"propose":[117],"DirectFS,":[118],"(to":[121],"our":[122],"best":[123],"knowledge)":[124],"first":[126],"FETS-based":[127],"approach":[128],"allows":[130],"direct":[131],"learning":[132],"parameters":[136],"in":[137,150,179],"continuous":[138],"space.":[139],"We":[140],"show":[141],"when":[143],"resultant":[145,159],"loss":[146],"function":[147,156],"optimized":[149],"coordinate-wise":[152],"manner,":[153],"cost":[155],"each":[158,180],"sub-problem":[160],"piece-wise":[163],"constant":[164],"function,":[165],"whose":[166],"optimal":[167],"value":[168],"can":[169],"be":[170],"found":[171],"exactly":[172],"efficiently.":[174],"Further,":[175],"key":[177],"step":[178],"iteration":[181],"DirectFS":[183],"requires":[184],"finding":[185],"most":[187],"statistically":[188],"significant":[189],"one":[190],"among":[191],"tens":[192],"thousands":[194],"Fisher's":[196],"exact":[197],"tests,":[198],"solved":[201],"efficiently":[202],"using":[203],"novel":[205],"`lookahead'-style":[206],"algorithm.":[207],"Experimental":[208],"evaluations":[209],"ENCODE":[211],"ChIP-seq":[212],"data":[213],"illustrate":[214],"performance":[216],"proposed":[219],"approach.":[220]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
