{"id":"https://openalex.org/W2527751063","doi":"https://doi.org/10.1109/tsp.2016.2614798","title":"Maximum-Likelihood Adaptive Filter for Partially Observed Boolean Dynamical Systems","display_name":"Maximum-Likelihood Adaptive Filter for Partially Observed Boolean Dynamical Systems","publication_year":2016,"publication_date":"2016-10-03","ids":{"openalex":"https://openalex.org/W2527751063","doi":"https://doi.org/10.1109/tsp.2016.2614798","mag":"2527751063"},"language":"en","primary_location":{"id":"doi:10.1109/tsp.2016.2614798","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2016.2614798","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal Processing","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1702.07269","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017741575","display_name":"Mahdi Imani","orcid":"https://orcid.org/0000-0001-9570-9909"},"institutions":[{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Mahdi Imani","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA","institution_ids":["https://openalex.org/I91045830"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026990034","display_name":"Ulisses Braga-Neto","orcid":"https://orcid.org/0000-0002-1210-2173"},"institutions":[{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ulisses M. Braga-Neto","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA","institution_ids":["https://openalex.org/I91045830"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5017741575"],"corresponding_institution_ids":["https://openalex.org/I91045830"],"apc_list":null,"apc_paid":null,"fwci":10.7911,"has_fulltext":false,"cited_by_count":113,"citation_normalized_percentile":{"value":0.98728717,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"65","issue":"2","first_page":"359","last_page":"371"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10621","display_name":"Gene Regulatory Network Analysis","score":0.9993000030517578,"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/T10621","display_name":"Gene Regulatory Network Analysis","score":0.9993000030517578,"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/T10885","display_name":"Gene expression and cancer classification","score":0.9833999872207642,"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/T11236","display_name":"Control Systems and Identification","score":0.9613999724388123,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/kalman-filter","display_name":"Kalman filter","score":0.751326858997345},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.6812678575515747},{"id":"https://openalex.org/keywords/estimation-theory","display_name":"Estimation theory","score":0.5497945547103882},{"id":"https://openalex.org/keywords/boolean-network","display_name":"Boolean network","score":0.5036794543266296},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.476189523935318},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.46994784474372864},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4390884041786194},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.4285701513290405},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4190281629562378},{"id":"https://openalex.org/keywords/extended-kalman-filter","display_name":"Extended Kalman filter","score":0.41737374663352966},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.4104398488998413},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.2895500063896179},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.2876228094100952},{"id":"https://openalex.org/keywords/boolean-function","display_name":"Boolean function","score":0.2665824294090271},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.18849661946296692},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.14536434412002563}],"concepts":[{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.751326858997345},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6812678575515747},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.5497945547103882},{"id":"https://openalex.org/C134444547","wikidata":"https://www.wikidata.org/wiki/Q585230","display_name":"Boolean network","level":3,"score":0.5036794543266296},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.476189523935318},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.46994784474372864},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4390884041786194},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.4285701513290405},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4190281629562378},{"id":"https://openalex.org/C206833254","wikidata":"https://www.wikidata.org/wiki/Q5421817","display_name":"Extended Kalman filter","level":3,"score":0.41737374663352966},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.4104398488998413},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.2895500063896179},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.2876228094100952},{"id":"https://openalex.org/C187455244","wikidata":"https://www.wikidata.org/wiki/Q942353","display_name":"Boolean function","level":2,"score":0.2665824294090271},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.18849661946296692},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.14536434412002563},{"id":"https://openalex.org/C2775924081","wikidata":"https://www.wikidata.org/wiki/Q55608371","display_name":"Control (management)","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tsp.2016.2614798","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp.2016.2614798","pdf_url":null,"source":{"id":"https://openalex.org/S168680287","display_name":"IEEE Transactions on Signal Processing","issn_l":"1053-587X","issn":["1053-587X","1941-0476"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Signal Processing","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1702.07269","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1702.07269","pdf_url":"https://arxiv.org/pdf/1702.07269","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1702.07269","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1702.07269","pdf_url":"https://arxiv.org/pdf/1702.07269","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2500733730","display_name":null,"funder_award_id":"CCF-1320884","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W51833465","https://openalex.org/W1971224531","https://openalex.org/W1989367702","https://openalex.org/W2003967703","https://openalex.org/W2004419591","https://openalex.org/W2006072083","https://openalex.org/W2036252257","https://openalex.org/W2049633694","https://openalex.org/W2057802165","https://openalex.org/W2058794142","https://openalex.org/W2094815068","https://openalex.org/W2130721915","https://openalex.org/W2152239989","https://openalex.org/W2154431984","https://openalex.org/W2292227541","https://openalex.org/W2292828258","https://openalex.org/W2308181013","https://openalex.org/W2331600386","https://openalex.org/W2492996488","https://openalex.org/W2530014580","https://openalex.org/W2543669550","https://openalex.org/W2546858757","https://openalex.org/W2569862645","https://openalex.org/W2735499110","https://openalex.org/W4245662196","https://openalex.org/W6731913931"],"related_works":["https://openalex.org/W2089114113","https://openalex.org/W2389555968","https://openalex.org/W1976188970","https://openalex.org/W4252706329","https://openalex.org/W2014532259","https://openalex.org/W1964091180","https://openalex.org/W2990541822","https://openalex.org/W1588885902","https://openalex.org/W2371827284","https://openalex.org/W2124552227"],"abstract_inverted_index":{"We":[0],"present":[1],"a":[2,84],"framework":[3],"for":[4,47],"the":[5,27,31,41,48,57,67,73,101],"simultaneous":[6],"estimation":[7,23,63],"of":[8,12,30,59,72,87],"state":[9,20,45],"and":[10,21,35,51],"parameters":[11],"partially":[13],"observed":[14,91],"Boolean":[15,32,36],"dynamical":[16],"systems":[17],"(POBDS).":[18],"Simultaneous":[19],"parameter":[22,54],"is":[24,64,78],"achieved":[25],"through":[26,92],"combined":[28],"use":[29],"Kalman":[33,37],"filter":[34,77],"smoother,":[38],"which":[39],"provide":[40],"minimum":[42],"mean-square":[43],"error":[44],"estimators":[46],"POBDS":[49,85],"model,":[50],"maximum-likelihood":[52],"(ML)":[53],"estimation;":[55],"in":[56],"presence":[58],"continuous":[60],"parameters,":[61],"ML":[62,75],"performed":[65],"using":[66,100],"expectation-maximization":[68],"algorithm.":[69],"The":[70],"performance":[71],"proposed":[74],"adaptive":[76],"demonstrated":[79],"by":[80],"numerical":[81],"experiments":[82],"with":[83],"model":[86],"gene":[88,106],"regulatory":[89,107],"networks":[90],"noisy":[93],"next-generation":[94],"sequencing":[95],"(RNA-seq)":[96],"time":[97],"series":[98],"data":[99],"well-known":[102],"p53-MDM2":[103],"negative-feedback":[104],"loop":[105],"model.":[108]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":15},{"year":2019,"cited_by_count":12},{"year":2018,"cited_by_count":26},{"year":2017,"cited_by_count":22},{"year":2016,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2016-10-14T00:00:00"}