{"id":"https://openalex.org/W2563587942","doi":"https://doi.org/10.1093/comnet/cnv029","title":"Molecular multiplex network inference using Gaussian mixture hidden Markov models","display_name":"Molecular multiplex network inference using Gaussian mixture hidden Markov models","publication_year":2015,"publication_date":"2015-12-27","ids":{"openalex":"https://openalex.org/W2563587942","doi":"https://doi.org/10.1093/comnet/cnv029","mag":"2563587942"},"language":"en","primary_location":{"id":"doi:10.1093/comnet/cnv029","is_oa":false,"landing_page_url":"https://doi.org/10.1093/comnet/cnv029","pdf_url":null,"source":{"id":"https://openalex.org/S2531583244","display_name":"Journal of Complex Networks","issn_l":"2051-1310","issn":["2051-1310","2051-1329"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Complex Networks","raw_type":"journal-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/A5008869927","display_name":"Petar Veli\u010dkovi\u0107","orcid":"https://orcid.org/0000-0002-2820-4692"},"institutions":[{"id":"https://openalex.org/I241749","display_name":"University of Cambridge","ror":"https://ror.org/013meh722","country_code":"GB","type":"education","lineage":["https://openalex.org/I241749"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Petar Veli\u010dkovi\u0107","raw_affiliation_strings":["Computer Laboratory, University of Cambridge, Cambridge CB3 0FD, UK"],"affiliations":[{"raw_affiliation_string":"Computer Laboratory, University of Cambridge, Cambridge CB3 0FD, UK","institution_ids":["https://openalex.org/I241749"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056748708","display_name":"P\u00edetro Li\u00f3","orcid":"https://orcid.org/0000-0002-0540-5053"},"institutions":[{"id":"https://openalex.org/I241749","display_name":"University of Cambridge","ror":"https://ror.org/013meh722","country_code":"GB","type":"education","lineage":["https://openalex.org/I241749"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Pietro Li\u00f2","raw_affiliation_strings":["Computer Laboratory, University of Cambridge, Cambridge CB3 0FD, UK"],"affiliations":[{"raw_affiliation_string":"Computer Laboratory, University of Cambridge, Cambridge CB3 0FD, UK","institution_ids":["https://openalex.org/I241749"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5008869927"],"corresponding_institution_ids":["https://openalex.org/I241749"],"apc_list":{"value":4151,"currency":"USD","value_usd":4151},"apc_paid":null,"fwci":0.701,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.76245552,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"cnv029","last_page":"cnv029"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9976999759674072,"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"}},"topics":[{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9976999759674072,"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"}},{"id":"https://openalex.org/T11324","display_name":"Spectroscopy Techniques in Biomedical and Chemical Research","score":0.9886000156402588,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"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/T11948","display_name":"Machine Learning in Materials Science","score":0.9871000051498413,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.727014422416687},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6945710182189941},{"id":"https://openalex.org/keywords/multiplex","display_name":"Multiplex","score":0.6684056520462036},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.6166894435882568},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.5464935302734375},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3811030685901642},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.24331200122833252},{"id":"https://openalex.org/keywords/bioinformatics","display_name":"Bioinformatics","score":0.06814199686050415}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.727014422416687},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6945710182189941},{"id":"https://openalex.org/C2781188995","wikidata":"https://www.wikidata.org/wiki/Q6934982","display_name":"Multiplex","level":2,"score":0.6684056520462036},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.6166894435882568},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.5464935302734375},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3811030685901642},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.24331200122833252},{"id":"https://openalex.org/C60644358","wikidata":"https://www.wikidata.org/wiki/Q128570","display_name":"Bioinformatics","level":1,"score":0.06814199686050415},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1093/comnet/cnv029","is_oa":false,"landing_page_url":"https://doi.org/10.1093/comnet/cnv029","pdf_url":null,"source":{"id":"https://openalex.org/S2531583244","display_name":"Journal of Complex Networks","issn_l":"2051-1310","issn":["2051-1310","2051-1329"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Complex Networks","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1984688056","https://openalex.org/W1995876521","https://openalex.org/W2007321142","https://openalex.org/W2033192342","https://openalex.org/W2073348267","https://openalex.org/W2086699924","https://openalex.org/W2109553965","https://openalex.org/W2114930814","https://openalex.org/W2125838338","https://openalex.org/W2126105956","https://openalex.org/W3037826211"],"related_works":["https://openalex.org/W2364370872","https://openalex.org/W2053269318","https://openalex.org/W2025614924","https://openalex.org/W2294335174","https://openalex.org/W2097963413","https://openalex.org/W1591475660","https://openalex.org/W2001275470","https://openalex.org/W2073996508","https://openalex.org/W3145575561","https://openalex.org/W2164162849"],"abstract_inverted_index":{"In":[0],"this":[1,101],"paper,":[2],"we":[3],"investigate":[4],"the":[5,12,30,104,112,120],"potentials":[6],"of":[7,14,38,57,100],"utilizing":[8],"multiplex":[9,72,89,113],"networks":[10],"in":[11,29],"context":[13,20],"machine":[15,73],"learning\u2014specifically,":[16],"binary":[17,127],"classification":[18,128],"problems\u2014a":[19],"which":[21,76],"has":[22],"received":[23],"little":[24],"attention":[25],"by":[26,69],"existing":[27],"research":[28],"area.":[31],"As":[32],"there":[33],"exists":[34],"a":[35,71,87,95,126,138],"wide":[36],"variety":[37],"real-world":[39],"systems":[40],"exhibiting":[41],"\u2018natural\u2019":[42],"multiplexity,":[43],"it":[44],"is":[45,67,107],"expected":[46],"that":[47,111],"such":[48],"models":[49],"would":[50],"adapt":[51],"to":[52],"learning":[53,74],"from":[54],"multiple":[55],"types":[56],"data":[58,140],"simultaneously":[59],"better":[60],"than":[61],"their":[62],"single-layered":[63,105],"counterparts.":[64],"This":[65],"claim":[66],"verified":[68],"constructing":[70],"model,":[75],"combines":[77],"several":[78],"Gaussian":[79],"mixture":[80],"hidden":[81],"Markov":[82],"model":[83,90,102],"(GMHMM)":[84],"layers":[85],"into":[86],"single":[88],"(which":[91],"itself":[92],"behaves":[93],"like":[94],"GMHMM).":[96],"Afterwards,":[97],"comparative":[98],"evaluation":[99],"and":[103],"GMHMM":[106],"performed.":[108],"We":[109],"demonstrate":[110],"version":[114,122],"achieves":[115],"higher":[116],"performance":[117],"compared":[118],"with":[119,125],"single-layer":[121],"when":[123],"faced":[124],"problem":[129],"on":[130,137],"synthetically":[131],"generated":[132],"data,":[133],"as":[134,136],"well":[135],"biomolecular":[139],"set.":[141]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2016,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}