{"id":"https://openalex.org/W3008451438","doi":"https://doi.org/10.1109/bigdata47090.2019.9006016","title":"Single-cell regulatory network inference and clustering from high-dimensional sequencing data","display_name":"Single-cell regulatory network inference and clustering from high-dimensional sequencing data","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3008451438","doi":"https://doi.org/10.1109/bigdata47090.2019.9006016","mag":"3008451438"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata47090.2019.9006016","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata47090.2019.9006016","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Big Data (Big Data)","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/A5082119404","display_name":"Aristidis G. Vrahatis","orcid":"https://orcid.org/0000-0003-1892-0000"},"institutions":[{"id":"https://openalex.org/I145722265","display_name":"University of Thessaly","ror":"https://ror.org/04v4g9h31","country_code":"GR","type":"education","lineage":["https://openalex.org/I145722265"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Aristidis G. Vrahatis","raw_affiliation_strings":["Dept. of Computer Science & Biomedical Informatics, University of Thessaly, Lamia, Greece"],"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science & Biomedical Informatics, University of Thessaly, Lamia, Greece","institution_ids":["https://openalex.org/I145722265"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077147419","display_name":"Georgios \u039d. Dimitrakopoulos","orcid":"https://orcid.org/0000-0002-7817-9552"},"institutions":[{"id":"https://openalex.org/I174878644","display_name":"University of Patras","ror":"https://ror.org/017wvtq80","country_code":"GR","type":"education","lineage":["https://openalex.org/I174878644"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Georgios N. Dimitrakopoulos","raw_affiliation_strings":["Medical School, University of Patras, Patras, Greece"],"affiliations":[{"raw_affiliation_string":"Medical School, University of Patras, Patras, Greece","institution_ids":["https://openalex.org/I174878644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039205111","display_name":"Sotiris K. Tasoulis","orcid":"https://orcid.org/0000-0001-9536-4090"},"institutions":[{"id":"https://openalex.org/I145722265","display_name":"University of Thessaly","ror":"https://ror.org/04v4g9h31","country_code":"GR","type":"education","lineage":["https://openalex.org/I145722265"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Sotiris K. Tasoulis","raw_affiliation_strings":["Dept. of Computer Science & Biomedical Informatics, University of Thessaly, Lamia, Greece"],"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science & Biomedical Informatics, University of Thessaly, Lamia, Greece","institution_ids":["https://openalex.org/I145722265"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085640042","display_name":"Spiros V. Georgakopoulos","orcid":"https://orcid.org/0000-0002-3374-0422"},"institutions":[{"id":"https://openalex.org/I145722265","display_name":"University of Thessaly","ror":"https://ror.org/04v4g9h31","country_code":"GR","type":"education","lineage":["https://openalex.org/I145722265"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Spiros V. Georgakopoulos","raw_affiliation_strings":["Dept. of Computer Science & Biomedical Informatics, University of Thessaly, Lamia, Greece"],"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science & Biomedical Informatics, University of Thessaly, Lamia, Greece","institution_ids":["https://openalex.org/I145722265"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111235416","display_name":"Vassilis P. Plagianakos","orcid":"https://orcid.org/0000-0002-4266-701X"},"institutions":[{"id":"https://openalex.org/I145722265","display_name":"University of Thessaly","ror":"https://ror.org/04v4g9h31","country_code":"GR","type":"education","lineage":["https://openalex.org/I145722265"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Vassilis P. Plagianakos","raw_affiliation_strings":["Dept. of Computer Science & Biomedical Informatics, University of Thessaly, Lamia, Greece"],"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science & Biomedical Informatics, University of Thessaly, Lamia, Greece","institution_ids":["https://openalex.org/I145722265"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5082119404"],"corresponding_institution_ids":["https://openalex.org/I145722265"],"apc_list":null,"apc_paid":null,"fwci":0.2569,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.57735792,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"2782","last_page":"2789"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11289","display_name":"Single-cell and spatial transcriptomics","score":1.0,"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/T11289","display_name":"Single-cell and spatial transcriptomics","score":1.0,"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":0.9983999729156494,"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":0.9959999918937683,"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/computer-science","display_name":"Computer science","score":0.6762345433235168},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.6584426164627075},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.611508846282959},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.6057352423667908},{"id":"https://openalex.org/keywords/gene-regulatory-network","display_name":"Gene regulatory network","score":0.5718231201171875},{"id":"https://openalex.org/keywords/workflow","display_name":"Workflow","score":0.563439667224884},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5232811570167542},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.45190659165382385},{"id":"https://openalex.org/keywords/biomedicine","display_name":"Biomedicine","score":0.4133462607860565},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32499897480010986},{"id":"https://openalex.org/keywords/bioinformatics","display_name":"Bioinformatics","score":0.1681906282901764},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.16573405265808105},{"id":"https://openalex.org/keywords/gene","display_name":"Gene","score":0.16272443532943726}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6762345433235168},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.6584426164627075},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.611508846282959},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.6057352423667908},{"id":"https://openalex.org/C67339327","wikidata":"https://www.wikidata.org/wiki/Q1502576","display_name":"Gene regulatory network","level":4,"score":0.5718231201171875},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.563439667224884},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5232811570167542},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.45190659165382385},{"id":"https://openalex.org/C66782513","wikidata":"https://www.wikidata.org/wiki/Q864601","display_name":"Biomedicine","level":2,"score":0.4133462607860565},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32499897480010986},{"id":"https://openalex.org/C60644358","wikidata":"https://www.wikidata.org/wiki/Q128570","display_name":"Bioinformatics","level":1,"score":0.1681906282901764},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.16573405265808105},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.16272443532943726},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C150194340","wikidata":"https://www.wikidata.org/wiki/Q26972","display_name":"Gene expression","level":3,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/bigdata47090.2019.9006016","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata47090.2019.9006016","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},{"id":"pmh:oai:ir.lib.uth.gr:11615/80759","is_oa":false,"landing_page_url":"http://hdl.handle.net/11615/80759","pdf_url":null,"source":{"id":"https://openalex.org/S4306400243","display_name":"University of Thessaly Institutional Repository (University of Thessaly)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I145722265","host_organization_name":"University of Thessaly","host_organization_lineage":["https://openalex.org/I145722265"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019","raw_type":"conferenceItem"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1731046649","https://openalex.org/W1977960943","https://openalex.org/W1995031758","https://openalex.org/W2008620264","https://openalex.org/W2011256013","https://openalex.org/W2012139697","https://openalex.org/W2013156169","https://openalex.org/W2037757210","https://openalex.org/W2054945727","https://openalex.org/W2061307034","https://openalex.org/W2062029454","https://openalex.org/W2062533676","https://openalex.org/W2065148309","https://openalex.org/W2076513103","https://openalex.org/W2078450879","https://openalex.org/W2094587261","https://openalex.org/W2098509290","https://openalex.org/W2105234758","https://openalex.org/W2108421561","https://openalex.org/W2162142051","https://openalex.org/W2163298355","https://openalex.org/W2260409121","https://openalex.org/W2269040222","https://openalex.org/W2345356016","https://openalex.org/W2502203653","https://openalex.org/W2536233805","https://openalex.org/W2612519453","https://openalex.org/W2616922646","https://openalex.org/W2735067671","https://openalex.org/W2753908609","https://openalex.org/W2757234574","https://openalex.org/W2762638728","https://openalex.org/W2898830231","https://openalex.org/W2903261499","https://openalex.org/W2911349457","https://openalex.org/W2952535935","https://openalex.org/W2973526013","https://openalex.org/W3101568187","https://openalex.org/W4213108508","https://openalex.org/W4240710608","https://openalex.org/W6658883175","https://openalex.org/W6756935443"],"related_works":["https://openalex.org/W2017899917","https://openalex.org/W2080571363","https://openalex.org/W2481322495","https://openalex.org/W2898682754","https://openalex.org/W2889841093","https://openalex.org/W2151082141","https://openalex.org/W2365236913","https://openalex.org/W3194374240","https://openalex.org/W2993861175","https://openalex.org/W2096756458"],"abstract_inverted_index":{"We":[0],"are":[1,130],"in":[2,203,221],"the":[3,20,26,40,56,79,89,96,116,123,127,137,144,177,188,211,263,273],"big":[4,69,172,242],"data":[5,24,74,174,179,244,274],"era":[6],"which":[7,45],"has":[8],"affected":[9,261],"several":[10,85],"domains":[11],"including":[12],"biomedicine":[13],"and":[14,33,47,158,186,248],"healthcare.":[15],"This":[16],"revolution":[17],"driven":[18],"by":[19,175,262],"explosion":[21],"of":[22,31,66,98,115,119,147,217,253],"biomedical":[23],"offers":[25],"potential":[27,97],"for":[28],"better":[29],"understanding":[30],"biology":[32],"human":[34,120],"diseases.":[35],"An":[36],"illustrative":[37],"example":[38],"is":[39,108,195,219,256,259],"emerging":[41],"single-cell":[42,70,224,243],"sequencing":[43,72],"technologies,":[44],"isolate":[46],"measure":[48],"each":[49],"cell":[50],"individually,":[51],"taking":[52],"a":[53,64,150,159,166,182,199,222,236,277],"step":[54],"beyond":[55],"traditional":[57],"techniques":[58],"where":[59],"consider":[60],"their":[61,82],"measurements":[62],"from":[63,171],"bulk":[65],"cell.":[67],"Although":[68],"RNA":[71],"(scRNA-seq)":[73],"promises":[75],"valuable":[76],"insights":[77],"into":[78,103],"cellular":[80],"level,":[81],"volume":[83],"poses":[84],"challenges":[86,124],"related":[87,125],"to":[88,93,126,181,205,210,240,276],"ultra-high":[90,128,246],"dimensionality.":[91],"Furthermore,":[92],"further":[94,196],"elucidate":[95],"these":[99],"data,":[100],"more":[101],"insight":[102],"gene":[104,167,191],"regulatory":[105,168],"networks":[106],"(GRN)":[107,170],"required.":[109],"Network-based":[110],"approaches":[111],"can":[112],"tackle":[113],"part":[114],"inherent":[117],"complexity":[118],"diseases,":[121],"however,":[122],"dimensionality":[129,146,247],"increased.":[131],"Towards":[132],"this":[133,254],"direction,":[134],"we":[135],"propose":[136],"NIRP,":[138],"an":[139],"algorithm":[140],"that":[141,257],"copes":[142],"with":[143,245],"high":[145],"scRNA-data":[148],"using":[149,198],"workflow":[151],"based":[152],"on":[153],"fast":[154],"multiple":[155],"random":[156,200],"projections":[157],"radius-based":[160],"nearest":[161],"neighbors":[162],"search.":[163],"NIRP":[164,218,235],"infers":[165],"network":[169,194],"scRNA-seq":[173],"transforming":[176],"original":[178],"space":[180,185,275],"lower":[183],"dimensions":[184],"capturing":[187],"similarities":[189],"among":[190,227],"expressions.":[192],"The":[193,215],"analyzed":[197],"walk":[201],"approach":[202],"order":[204],"achieve":[206],"dense":[207],"subgraphs,":[208],"active":[209],"case":[212],"under":[213],"study.":[214],"performance":[216],"evaluated":[220],"real":[223],"experimental":[225],"study":[226],"three":[228],"well-established":[229],"GRN":[230],"tools.":[231],"Our":[232],"results":[233],"make":[234],"reliable":[237],"tool,":[238],"able":[239],"handle":[241],"complexity.":[249],"he":[250],"main":[251],"advantage":[252],"method":[255],"it":[258,268,271],"not":[260],"volume,":[264],"as":[265,267],"much":[266],"increases,":[269],"since":[270],"transforms":[272],"specific":[278],"low":[279],"dimensional":[280],"space.":[281]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
