{"id":"https://openalex.org/W3006969484","doi":"https://doi.org/10.1109/icassp40776.2020.9052965","title":"Identification of Essential Proteins Using A Novel Multi-Objective Optimization Method","display_name":"Identification of Essential Proteins Using A Novel Multi-Objective Optimization Method","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W3006969484","doi":"https://doi.org/10.1109/icassp40776.2020.9052965","mag":"3006969484"},"language":"en","primary_location":{"id":"doi:10.1109/icassp40776.2020.9052965","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9052965","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5077932855","display_name":"Chong Wu","orcid":"https://orcid.org/0000-0003-3405-742X"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"Chong Wu","raw_affiliation_strings":["Department of Electrical Engineering, City University of Hong Kong, Kowloon, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, City University of Hong Kong, Kowloon, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020255809","display_name":"Houwang Zhang","orcid":"https://orcid.org/0000-0002-2358-0613"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Houwang Zhang","raw_affiliation_strings":["School of Automation, China University of Geosciences, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100350625","display_name":"Le Zhang","orcid":"https://orcid.org/0000-0002-3708-1727"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Le Zhang","raw_affiliation_strings":["Department of Computer Science and Technology, Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051390959","display_name":"Hanying Zheng","orcid":"https://orcid.org/0000-0002-8480-967X"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hanying Zheng","raw_affiliation_strings":["School of Automation, China University of Geosciences, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, China University of Geosciences, Wuhan, China","institution_ids":["https://openalex.org/I3124059619"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5077932855"],"corresponding_institution_ids":["https://openalex.org/I168719708"],"apc_list":null,"apc_paid":null,"fwci":0.58,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.63857367,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"2005","issue":null,"first_page":"1329","last_page":"1333"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9998000264167786,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9998000264167786,"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/T12254","display_name":"Machine Learning in Bioinformatics","score":0.996399998664856,"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/T10211","display_name":"Computational Drug Discovery Methods","score":0.9944999814033508,"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/generalization","display_name":"Generalization","score":0.7333494424819946},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6381916403770447},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.584932804107666},{"id":"https://openalex.org/keywords/pareto-principle","display_name":"Pareto principle","score":0.5754852890968323},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.49889183044433594},{"id":"https://openalex.org/keywords/voting","display_name":"Voting","score":0.4959741532802582},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4877965748310089},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.42315608263015747},{"id":"https://openalex.org/keywords/majority-rule","display_name":"Majority rule","score":0.42171114683151245},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3738238215446472},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35063090920448303},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3390944004058838},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3341110348701477},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.24105313420295715},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21941787004470825}],"concepts":[{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.7333494424819946},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6381916403770447},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.584932804107666},{"id":"https://openalex.org/C137635306","wikidata":"https://www.wikidata.org/wiki/Q182667","display_name":"Pareto principle","level":2,"score":0.5754852890968323},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.49889183044433594},{"id":"https://openalex.org/C520049643","wikidata":"https://www.wikidata.org/wiki/Q189760","display_name":"Voting","level":3,"score":0.4959741532802582},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4877965748310089},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.42315608263015747},{"id":"https://openalex.org/C153668964","wikidata":"https://www.wikidata.org/wiki/Q27636","display_name":"Majority rule","level":2,"score":0.42171114683151245},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3738238215446472},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35063090920448303},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3390944004058838},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3341110348701477},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.24105313420295715},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21941787004470825},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp40776.2020.9052965","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9052965","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1647729745","https://openalex.org/W1854214752","https://openalex.org/W1973758399","https://openalex.org/W2005740247","https://openalex.org/W2006683252","https://openalex.org/W2007245700","https://openalex.org/W2017975254","https://openalex.org/W2020541351","https://openalex.org/W2028145367","https://openalex.org/W2038920443","https://openalex.org/W2059747206","https://openalex.org/W2080124756","https://openalex.org/W2087194317","https://openalex.org/W2105089945","https://openalex.org/W2119114096","https://openalex.org/W2132582966","https://openalex.org/W2586452838","https://openalex.org/W2613994501","https://openalex.org/W2770647174","https://openalex.org/W2895946680","https://openalex.org/W4244062033","https://openalex.org/W6636975626","https://openalex.org/W6639055396","https://openalex.org/W6678074526"],"related_works":["https://openalex.org/W2768210113","https://openalex.org/W3121841074","https://openalex.org/W2901018557","https://openalex.org/W2055572829","https://openalex.org/W1894159578","https://openalex.org/W2807400035","https://openalex.org/W4297796115","https://openalex.org/W3125086856","https://openalex.org/W3124408951","https://openalex.org/W2019092055"],"abstract_inverted_index":{"Using":[0],"graph":[1],"theory":[2],"to":[3,53,96],"identify":[4],"essential":[5,39,79],"proteins":[6,40],"is":[7,27,59,70,83],"a":[8,42,48,60,71,75,93],"hot":[9],"topic":[10],"at":[11],"present.":[12],"These":[13],"methods":[14,26,132],"are":[15],"called":[16],"network-based":[17,25],"methods.":[18],"However,":[19],"the":[20,36,98,111],"generalization":[21,141],"ability":[22],"of":[23,38,62,78,100,116,135],"most":[24],"not":[28],"satisfactory.":[29],"Hence,":[30],"in":[31,67,133],"this":[32,68],"paper,":[33],"we":[34,107],"consider":[35],"identification":[37],"as":[41,85],"multi-objective":[43,50],"optimization":[44,51,57],"problem":[45],"and":[46,82,120,140],"use":[47,92],"novel":[49],"method":[52,129],"solve":[54],"it.":[55],"The":[56,123],"result":[58],"set":[61,69],"Pareto":[63],"solutions.":[64],"Every":[65],"solution":[66],"vector":[72],"which":[73],"has":[74],"certain":[76],"number":[77],"protein":[80],"candidates":[81],"considered":[84],"an":[86],"independent":[87],"predictor":[88],"or":[89],"voter.":[90],"We":[91],"voting":[94],"strategy":[95],"assemble":[97],"results":[99,125],"these":[101],"predictors.":[102],"To":[103],"validate":[104],"our":[105,128],"method,":[106],"apply":[108],"it":[109],"on":[110],"protein-protein":[112],"interactions":[113],"(PPI)":[114],"datasets":[115],"two":[117],"species":[118],"(Yeast":[119],"Escherichia":[121],"coli).":[122],"experiment":[124],"show":[126],"that":[127],"outperforms":[130],"state-of-the-art":[131],"terms":[134],"sensitive,":[136],"specificity,":[137],"F-measure,":[138],"accuracy,":[139],"ability.":[142]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}