{"id":"https://openalex.org/W2488201104","doi":"https://doi.org/10.1109/acc.2016.7526087","title":"Graphoid-based methodologies in modeling, analysis, identification and control of networks of dynamic systems","display_name":"Graphoid-based methodologies in modeling, analysis, identification and control of networks of dynamic systems","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2488201104","doi":"https://doi.org/10.1109/acc.2016.7526087","mag":"2488201104"},"language":"en","primary_location":{"id":"doi:10.1109/acc.2016.7526087","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acc.2016.7526087","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 American Control Conference (ACC)","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/A5058663513","display_name":"Donatello Materassi","orcid":"https://orcid.org/0000-0002-4736-8377"},"institutions":[{"id":"https://openalex.org/I75027704","display_name":"University of Tennessee at Knoxville","ror":"https://ror.org/020f3ap87","country_code":"US","type":"education","lineage":["https://openalex.org/I75027704"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Donatello Materassi","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, University of Tennessee"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, University of Tennessee","institution_ids":["https://openalex.org/I75027704"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069864205","display_name":"Murti V. Salapaka","orcid":"https://orcid.org/0000-0002-4595-9683"},"institutions":[{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Murti V. Salapaka","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Minnesota"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Minnesota","institution_ids":["https://openalex.org/I130238516"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3482,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.68814388,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"12","issue":null,"first_page":"4661","last_page":"4675"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10621","display_name":"Gene Regulatory Network Analysis","score":0.9936000108718872,"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":0.9936000108718872,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9908999800682068,"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"}},{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9211000204086304,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/graphical-model","display_name":"Graphical model","score":0.7725008726119995},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6774725317955017},{"id":"https://openalex.org/keywords/directed-acyclic-graph","display_name":"Directed acyclic graph","score":0.6706051230430603},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.5817416906356812},{"id":"https://openalex.org/keywords/random-variable","display_name":"Random variable","score":0.5684948563575745},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5433571338653564},{"id":"https://openalex.org/keywords/joint-probability-distribution","display_name":"Joint probability distribution","score":0.4985830783843994},{"id":"https://openalex.org/keywords/directed-graph","display_name":"Directed graph","score":0.45914503931999207},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4517464339733124},{"id":"https://openalex.org/keywords/graph-theory","display_name":"Graph theory","score":0.42884552478790283},{"id":"https://openalex.org/keywords/probability-distribution","display_name":"Probability distribution","score":0.4233921468257904},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.25113996863365173},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24766674637794495},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.21372634172439575}],"concepts":[{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.7725008726119995},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6774725317955017},{"id":"https://openalex.org/C74197172","wikidata":"https://www.wikidata.org/wiki/Q1195339","display_name":"Directed acyclic graph","level":2,"score":0.6706051230430603},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5817416906356812},{"id":"https://openalex.org/C122123141","wikidata":"https://www.wikidata.org/wiki/Q176623","display_name":"Random variable","level":2,"score":0.5684948563575745},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5433571338653564},{"id":"https://openalex.org/C18653775","wikidata":"https://www.wikidata.org/wiki/Q1333358","display_name":"Joint probability distribution","level":2,"score":0.4985830783843994},{"id":"https://openalex.org/C146380142","wikidata":"https://www.wikidata.org/wiki/Q1137726","display_name":"Directed graph","level":2,"score":0.45914503931999207},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4517464339733124},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.42884552478790283},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.4233921468257904},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.25113996863365173},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24766674637794495},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21372634172439575},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/acc.2016.7526087","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acc.2016.7526087","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 American Control Conference (ACC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W178056938","https://openalex.org/W284239745","https://openalex.org/W1511986666","https://openalex.org/W1524313545","https://openalex.org/W1585303438","https://openalex.org/W1965324089","https://openalex.org/W1982344744","https://openalex.org/W2001667451","https://openalex.org/W2010307518","https://openalex.org/W2014815494","https://openalex.org/W2018045523","https://openalex.org/W2018340547","https://openalex.org/W2024650319","https://openalex.org/W2027624514","https://openalex.org/W2030205386","https://openalex.org/W2033869127","https://openalex.org/W2053351271","https://openalex.org/W2060717797","https://openalex.org/W2069443184","https://openalex.org/W2077083618","https://openalex.org/W2107396783","https://openalex.org/W2110237152","https://openalex.org/W2115360427","https://openalex.org/W2133280087","https://openalex.org/W2136913207","https://openalex.org/W2138144286","https://openalex.org/W2150546315","https://openalex.org/W2150926065","https://openalex.org/W2159080219","https://openalex.org/W2163166770","https://openalex.org/W2163988453","https://openalex.org/W2166499263","https://openalex.org/W2171853113","https://openalex.org/W2291011126","https://openalex.org/W2484772439","https://openalex.org/W2798588639","https://openalex.org/W2952114617","https://openalex.org/W3022273187","https://openalex.org/W3139799810","https://openalex.org/W3140973516","https://openalex.org/W3151620869","https://openalex.org/W4213240787","https://openalex.org/W4238823463","https://openalex.org/W4299927410","https://openalex.org/W4300167274","https://openalex.org/W4302423442","https://openalex.org/W6629574937","https://openalex.org/W6639611172","https://openalex.org/W6655147698","https://openalex.org/W6664027507","https://openalex.org/W6665573485","https://openalex.org/W6764014844"],"related_works":["https://openalex.org/W79495945","https://openalex.org/W1505105018","https://openalex.org/W2035724326","https://openalex.org/W2443765813","https://openalex.org/W4299933434","https://openalex.org/W2146569528","https://openalex.org/W17595654","https://openalex.org/W2962752536","https://openalex.org/W4302568932","https://openalex.org/W4214487273"],"abstract_inverted_index":{"There":[0],"is":[1,72,104,163,275,310],"extensive":[2],"literature":[3],"on":[4],"the":[5,21,29,46,68,94,125,145,197,205,239,246,280],"description":[6],"of":[7,26,42,56,82,96,151,156,182,186,200,214,248,250,256,288,293],"joint":[8,58],"probability":[9,59],"distributions":[10],"via":[11],"graphs,":[12],"where":[13],"each":[14,115],"node":[15],"represents":[16],"a":[17,24,53,119,131,143,165,180,297],"random":[18,83,152,215,289],"variable":[19],"and":[20,99,134,154,236,242,253,282,291,301,318],"edges":[22],"describe":[23],"form":[25],"coupling":[27],"among":[28,45],"variables.":[30,216],"The":[31],"connections":[32,127],"in":[33,93,184,245],"these":[34,62,172,218,257,305],"graphical":[35,80,149,234,286],"models":[36,81,109,150,235,287],"do":[37,128],"not":[38,164,194],"necessarily":[39],"represent":[40,52,130],"forms":[41],"input/output":[43,132],"relations":[44,133],"variables":[47,84,153,290],"involved.":[48],"Instead,":[49],"they":[50],"typically":[51,85],"convenient":[54],"factorization":[55,183],"their":[57,320],"distribution.":[60],"For":[61],"factorizations":[63],"to":[64,74,106,118,168,196,204,269,278],"be":[65,138,230,260,270],"mathematically":[66],"meaningful,":[67],"underlying":[69,148],"graph":[70,126,176],"structure":[71],"required":[73],"have":[75],"no":[76,263],"directed":[77,88,120],"cycles.":[78],"Thus,":[79],"deal":[86],"with":[87,262],"acyclic":[89],"graphs":[90],"(DAGs).":[91],"Conversely,":[92],"area":[95],"dynamic":[97,157,187,251,294],"systems,":[98,295],"especially":[100],"control":[101,243],"theory,":[102],"it":[103,162,220],"common":[105],"find":[107],"network":[108,146],"involving":[110],"stochastic":[111,208],"processes":[112,209],"that":[113,207,227],"influence":[114],"other":[116],"according":[117],"graph.":[121],"In":[122],"this":[123],"case":[124],"indeed":[129],"feedback":[135],"loops":[136],"may":[137],"present,":[139],"as":[140],"well.":[141],"As":[142],"consequence,":[144],"structures":[147],"networks":[155,185,249,292],"systems":[158,188,252],"differ":[159],"fundamentally.":[160],"Furthermore,":[161],"straightforward":[166],"task":[167],"unify":[169],"or":[170],"reconcile":[171],"two":[173,306],"semantically":[174],"different":[175,307],"descriptions.":[177],"Indeed,":[178],"introducing":[179],"notion":[181],"would":[189],"present":[190],"technical":[191],"difficulties":[192],"due":[193],"only":[195],"potential":[198],"presence":[199],"loops,":[201],"but":[202],"also":[203],"fact":[206],"involve":[210],"an":[211,276],"infinite":[212],"number":[213],"Despite":[217],"differences,":[219],"has":[221],"become":[222],"evident":[223],"during":[224],"recent":[225],"years":[226],"methodologies":[228,258],"can":[229,259],"borrowed":[231],"from":[232],"probabilistic":[233],"used":[237],"for":[238,304],"analysis,":[240],"identification":[241],"design":[244],"domain":[247],"viceversa.":[254],"Some":[255],"imported":[261],"significant":[264],"modifications,":[265],"while":[266],"others":[267],"need":[268],"substantially":[271],"revisited.":[272],"This":[273,309],"article":[274],"attempt":[277],"bridge":[279],"conceptual":[281],"methodological":[283],"gap":[284],"between":[285,315],"creating":[296],"single":[298],"unified":[299],"language":[300],"theoretical":[302],"framework":[303],"classes.":[308],"achieved":[311],"by":[312],"drawing":[313],"parallels":[314],"similar":[316],"approaches":[317],"highlighting":[319],"main":[321],"differences.":[322]},"counts_by_year":[{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}