{"id":"https://openalex.org/W2418352133","doi":null,"title":"An overview of computer algorithms for deconvolution-based assessment of in vivo neuroendocrine secretory events.","display_name":"An overview of computer algorithms for deconvolution-based assessment of in vivo neuroendocrine secretory events.","publication_year":1990,"publication_date":"1990-06-01","ids":{"openalex":"https://openalex.org/W2418352133","mag":"2418352133","pmid":"https://pubmed.ncbi.nlm.nih.gov/2192741"},"language":"en","primary_location":{"id":"pmid:2192741","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/2192741","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BioTechniques","raw_type":"Journal Article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["pubmed"],"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/A5059807217","display_name":"Veldhuis Jd","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"J D Veldhuis","raw_affiliation_strings":["Department of Internal Medicine, University of Virginia Health Sciences Center, Charlottesville 22908"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Internal Medicine, University of Virginia Health Sciences Center, Charlottesville 22908","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112130961","display_name":"Johnson Ml","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"M L Johnson","raw_affiliation_strings":["UNIVERSITY OF VIRGINIA;"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"UNIVERSITY OF VIRGINIA;","institution_ids":["https://openalex.org/I51556381"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I51556381"],"apc_list":null,"apc_paid":null,"fwci":2.4273,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.86570477,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"8","issue":"6","first_page":"634","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13487","display_name":"Statistical and numerical algorithms","score":0.5727999806404114,"subfield":{"id":"https://openalex.org/subfields/2604","display_name":"Applied Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13487","display_name":"Statistical and numerical algorithms","score":0.5727999806404114,"subfield":{"id":"https://openalex.org/subfields/2604","display_name":"Applied Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11236","display_name":"Control Systems and Identification","score":0.1574999988079071,"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"}},{"id":"https://openalex.org/T11205","display_name":"Numerical methods in inverse problems","score":0.062300000339746475,"subfield":{"id":"https://openalex.org/subfields/2610","display_name":"Mathematical Physics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/deconvolution","display_name":"deconvolution","score":0.8740000128746033},{"id":"https://openalex.org/keywords/neuroendocrine-secretion","display_name":"neuroendocrine secretion","score":0.9419999718666077},{"id":"https://openalex.org/keywords/convolution-integral","display_name":"convolution integral","score":0.8209999799728394},{"id":"https://openalex.org/keywords/sparse-noisy-data","display_name":"sparse noisy data","score":0.6620000004768372},{"id":"https://openalex.org/keywords/deconvolution-algorithm","display_name":"deconvolution algorithm","score":0.7620000243186951}],"concepts":[{"id":"https://openalex.org/C174576160","wikidata":"https://www.wikidata.org/wiki/Q1183700","display_name":"Deconvolution","level":2,"score":0.9576871395111084},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6583016514778137},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6218905448913574},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6093927025794983},{"id":"https://openalex.org/C30044814","wikidata":"https://www.wikidata.org/wiki/Q11334452","display_name":"Blind deconvolution","level":3,"score":0.4530786871910095},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.20474594831466675},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000818","descriptor_name":"Animals","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008954","descriptor_name":"Models, Biological","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D009489","descriptor_name":"Neurosecretion","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D009490","descriptor_name":"Neurosecretory Systems","qualifier_ui":"Q000378","qualifier_name":"metabolism","is_major_topic":true}],"locations_count":2,"locations":[{"id":"pmid:2192741","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/2192741","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BioTechniques","raw_type":"Journal Article"},{"id":"mag:2418352133","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/2192741","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"PubMed","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G5531328711","display_name":"General Clinical Research Center","funder_award_id":"M01RR000847","funder_id":"https://openalex.org/F4320337375","funder_display_name":"National Center for Research Resources"},{"id":"https://openalex.org/G6610763224","display_name":"ACTIONS OF ESTROGEN IN MATURING GRAAFIAN FOLLICLES","funder_award_id":"K04HD000634","funder_id":"https://openalex.org/F4320337611","funder_display_name":"Eunice Kennedy Shriver National Institute of Child Health and Human Development"},{"id":"https://openalex.org/G869268388","display_name":"ANALYSIS OF MODELS OF HEMOGLOBIN ACTION","funder_award_id":"R01GM028928","funder_id":"https://openalex.org/F4320337354","funder_display_name":"National Institute of General Medical Sciences"}],"funders":[{"id":"https://openalex.org/F4320337354","display_name":"National Institute of General Medical Sciences","ror":"https://ror.org/04q48ey07"},{"id":"https://openalex.org/F4320337375","display_name":"National Center for Research Resources","ror":"https://ror.org/04pw6fb54"},{"id":"https://openalex.org/F4320337611","display_name":"Eunice Kennedy Shriver National Institute of Child Health and Human Development","ror":"https://ror.org/04byxyr05"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W1468102428","https://openalex.org/W1018488365","https://openalex.org/W1998920421","https://openalex.org/W2509305442","https://openalex.org/W2035027584","https://openalex.org/W2050314644","https://openalex.org/W2049172302","https://openalex.org/W2136251257","https://openalex.org/W2220419375","https://openalex.org/W2055479690"],"abstract_inverted_index":{"The":[0,53],"availability":[1],"of":[2,14,55,63,84,95,98,107,112,118,130,136,166,187],"increasingly":[3],"efficient":[4],"computational":[5],"systems":[6],"has":[7,70],"made":[8],"feasible":[9],"the":[10,61,125,185],"otherwise":[11],"burdensome":[12],"analysis":[13],"complex":[15,193],"neurobiological":[16],"data,":[17],"such":[18],"as":[19,39],"in":[20,85,184],"vivo":[21,86],"neuroendocrine":[22,87],"glandular":[23],"secretory":[24,134],"activity.":[25],"Neuroendocrine":[26],"data":[27,153,179],"sets":[28],"are":[29,93],"typically":[30],"sparse,":[31],"noisy":[32],"and":[33,41,49,128,140,144,154,180],"generated":[34],"by":[35],"combined":[36],"processes":[37,67],"(such":[38],"secretion":[40,108],"metabolic":[42,147],"clearance)":[43],"operating":[44],"simultaneously":[45,141],"over":[46],"both":[47],"short":[48],"long":[50],"time":[51],"spans.":[52],"concept":[54],"a":[56,104,164],"convolution":[57],"integral":[58,101],"to":[59,78,123,177],"describe":[60],"impact":[62],"two":[64],"or":[65],"more":[66],"acting":[68],"jointly":[69],"offered":[71],"an":[72],"informative":[73],"mathematical":[74],"construct":[75],"with":[76],"which":[77],"dissect":[79],"(deconvolve)":[80],"specific":[81],"quantitative":[82],"features":[83],"phenomena.":[88],"Appropriate":[89],"computer-based":[90,188],"deconvolution":[91,168,189],"algorithms":[92],"capable":[94],"solving":[96],"families":[97],"100-300":[99],"simultaneous":[100],"equations":[102],"for":[103,191],"large":[105],"number":[106],"and/or":[109],"clearance":[110,148],"parameters":[111],"interest.":[113],"For":[114],"example,":[115],"one":[116],"application":[117],"computer":[119],"technology":[120],"allows":[121],"investigators":[122],"deconvolve":[124],"number,":[126],"amplitude":[127],"duration":[129],"statistically":[131],"significant":[132],"underlying":[133],"episodes":[135],"algebraically":[137],"specifiable":[138],"waveform":[139],"estimate":[142],"subject-":[143],"condition-specific":[145],"neurohormone":[146],"rates":[149],"using":[150],"all":[151],"observed":[152],"their":[155,171,175],"experimental":[156],"variances":[157],"considered":[158],"simultaneously.":[159],"Here,":[160],"we":[161],"will":[162],"provide":[163],"definition":[165],"selected":[167],"techniques,":[169],"review":[170],"conceptual":[172],"basis,":[173],"illustrate":[174],"applicability":[176],"biological":[178,194],"discuss":[181],"new":[182],"perspectives":[183],"arena":[186],"methodologies":[190],"evaluating":[192],"events.":[195]},"counts_by_year":[],"updated_date":"2026-11-05T12:25:35.769452","created_date":"2016-06-24T00:00:00"}
