Parallel MOEA Based on Consensus and Membrane Structure for Inferring Phylogenetic Reconstruction

In recent years, inferring phylogenies has attracted lots of attention in both academic community and various application fields. Phylogenetic inference usually consists of a couple of evolutionary relationships, which can be represented as a phylogenetic tree. The phylogenetic reconstruction proble...

Full description

Saved in:

Bibliographic Details
Published in:	IEEE access Vol. 8; pp. 6177 - 6189
Main Authors:	Zhang, Qianqian, Zhang, Jun, Zhong, Yue, Ye, Congming, Min, Xiaoping
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Biomembranes Combinatorial analysis Consensus Convergence Criteria Datasets Evolutionary algorithms Genetic algorithms Heuristic methods membrane structure Membrane structures Membranes multi-objective evolutionary algorithm Optimization parallel algorithm Parallel processing phylogenetic reconstruction Phylogenetics Phylogeny Reconstruction Topology Vegetation
ISSN:	2169-3536, 2169-3536
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Abstract	In recent years, inferring phylogenies has attracted lots of attention in both academic community and various application fields. Phylogenetic inference usually consists of a couple of evolutionary relationships, which can be represented as a phylogenetic tree. The phylogenetic reconstruction problem can be defined as an optimization problem, targeting at finding the most eligible tree among all possible topologies according to a selected criterion. Since the combinatorial number of possible topologies exceeds tolerance, various heuristic and metaheuristic methods have been proposed to find approximate solutions according to the selected criterion. However, different criterions are based on different principle and conflict with each other basically. In this line, scholars has proposed multi-objective evolutionary algorithm (MOEA) based on diverse criteria. Nevertheless, MOEA has suffered unbearable time consumption due to its inherent drawbacks of computational complexity and convergence. By studying the independence between the sub-populations in each time-consuming step of MOEA, the steps without global information can be designed to be executed in parallel, which can fundamentally address computational problems. Effective parallel algorithms designed with the characteristics of modern multicore clusters can solve such problems. In this sense, we propose a parallelized multi-objective evolutionary algorithm (MOEA-MC) by deploying on Spark, which added consensus into evolutionary algorithm to improve the quality of convergence and used membrane structure to keep equal solutions under different weights. In order to assess the performance achieved by the proposal, we have performed comparison among different methods on three real-world datasets separately. The results have certified that the solutions derived from MOEA-MC are superior to traditional methods in all studied datasets. And parallelized MOEA-MC can get dominant position and optimal Pareto-frontier simultaneously within minimal runtime.
AbstractList	In recent years, inferring phylogenies has attracted lots of attention in both academic community and various application fields. Phylogenetic inference usually consists of a couple of evolutionary relationships, which can be represented as a phylogenetic tree. The phylogenetic reconstruction problem can be defined as an optimization problem, targeting at finding the most eligible tree among all possible topologies according to a selected criterion. Since the combinatorial number of possible topologies exceeds tolerance, various heuristic and metaheuristic methods have been proposed to find approximate solutions according to the selected criterion. However, different criterions are based on different principle and conflict with each other basically. In this line, scholars has proposed multi-objective evolutionary algorithm (MOEA) based on diverse criteria. Nevertheless, MOEA has suffered unbearable time consumption due to its inherent drawbacks of computational complexity and convergence. By studying the independence between the sub-populations in each time-consuming step of MOEA, the steps without global information can be designed to be executed in parallel, which can fundamentally address computational problems. Effective parallel algorithms designed with the characteristics of modern multicore clusters can solve such problems. In this sense, we propose a parallelized multi-objective evolutionary algorithm (MOEA-MC) by deploying on Spark, which added consensus into evolutionary algorithm to improve the quality of convergence and used membrane structure to keep equal solutions under different weights. In order to assess the performance achieved by the proposal, we have performed comparison among different methods on three real-world datasets separately. The results have certified that the solutions derived from MOEA-MC are superior to traditional methods in all studied datasets. And parallelized MOEA-MC can get dominant position and optimal Pareto-frontier simultaneously within minimal runtime.
Author	Ye, Congming Min, Xiaoping Zhang, Qianqian Zhong, Yue Zhang, Jun
Author_xml	– sequence: 1 givenname: Qianqian orcidid: 0000-0003-1955-1366 surname: Zhang fullname: Zhang, Qianqian organization: Department of Computer Science, Xiamen University, Xiamen, China – sequence: 2 givenname: Jun orcidid: 0000-0003-0402-3034 surname: Zhang fullname: Zhang, Jun organization: Rehabilitation Department, Heilongjiang Province Land Reclamation Headquarters General Hospital, Harbin, China – sequence: 3 givenname: Yue orcidid: 0000-0002-8576-2439 surname: Zhong fullname: Zhong, Yue organization: Department of Computer Science, Xiamen University, Xiamen, China – sequence: 4 givenname: Congming orcidid: 0000-0002-6011-2691 surname: Ye fullname: Ye, Congming organization: Department of Computer Science, Xiamen University, Xiamen, China – sequence: 5 givenname: Xiaoping orcidid: 0000-0002-0817-0878 surname: Min fullname: Min, Xiaoping email: mxp@xmu.edu.cn organization: Department of Computer Science, Xiamen University, Xiamen, China
BookMark	eNp9kUFvEzEQhS1UJErpL-jFEucE27Pe2MewChCpVSsCZ2vinQ0bbe1i7x7673G6Lao44Iut0fvePOu9Z2chBmLsSoqllMJ-WjfNZrdbKiHtUlltVwbesHMla7sADfXZq_c7dpnzUZRjykivzhneYcJhoIHf3G7W_DNmankMvIkhU8hT5hhafkP3-4SB-G5Mkx-nRLyLiW9DRyn14cDvfj0O8UCBxt7z7-QL_aTsY_jA3nY4ZLp8vi_Yzy-bH823xfXt122zvl74SphxAaZF8MZbaaSWLdSdlgAaNVBn9lBR1dVGVrXeqxUZ8Noopf3Kg650BxLhgm1n3zbi0T2k_h7To4vYu6dBTAeHqcQbyFkQ1BrcExRjqzWa2lujyjLTCm9OXh9nr4cUf0-UR3eMUwolvlOVrmytpNBFZWeVTzHnRJ3z_YinP48J-8FJ4U4FubkgdyrIPRdUWPiHfUn8f-pqpnoi-ksYCyClgj9bUZ1i
CODEN	IAECCG
CitedBy_id	crossref_primary_10_3390_math11153327 crossref_primary_10_1016_j_biosystems_2022_104606 crossref_primary_10_1111_itor_13164 crossref_primary_10_1016_j_asoc_2023_110270
Cites_doi	10.1109/TCBB.2017.2776280 10.1109/TEVC.2007.892759 10.1186/s12918-017-0476-3 10.1016/0025-5564(90)90123-G 10.1109/TCBB.2007.070203 10.1016/j.jpdc.2019.04.007 10.1109/TCDS.2017.2785332 10.1086/509588 10.1093/bioinformatics/btz694 10.1093/oxfordjournals.molbev.a026008 10.1017/CBO9780511819049 10.1109/TPDS.2014.2325828 10.1007/s00158-009-0460-7 10.1109/TNB.2018.2873221 10.1111/2041-210X.12529 10.1023/A:1013737224969 10.1016/j.artmed.2017.02.005 10.1007/978-1-4471-5304-7_14 10.1007/978-3-642-13800-3_17 10.1007/BF02101694 10.1109/TSMCC.2005.855515 10.1109/TEVC.2017.2749619 10.1073/pnas.162224399 10.1016/j.ins.2019.08.064 10.1007/BF01731581 10.1186/s13015-017-0116-x 10.1111/j.1096-0031.2005.00054.x 10.2307/2412810 10.1007/s11063-018-9947-9 10.1109/JIOT.2018.2870288 10.1093/bioinformatics/btz418 10.1007/11415770_23 10.1145/2925985 10.1093/bioinformatics/btv177 10.1093/gigascience/giy098 10.1016/j.artmed.2017.03.001 10.1016/B978-1-4832-3211-9.50009-7 10.1038/srep33870 10.1109/TEVC.2016.2600642 10.1093/bfgp/elv024 10.1016/j.jgg.2018.07.004 10.1038/nature02053 10.1109/4235.996017 10.2307/2406441 10.1021/acs.jproteome.7b00019 10.3724/SP.J.1259.2014.00049 10.1109/TEVC.2018.2883888 10.1016/j.ins.2019.05.070 10.3390/ijms19010062 10.1109/TNB.2019.2896981 10.1080/10635150050207401 10.1109/ICCSE.2016.7581647 10.1111/j.1558-5646.1981.tb04991.x 10.1016/j.ins.2015.06.040 10.1007/BF00182187 10.1093/oxfordjournals.molbev.a025924
ContentType	Journal Article
Copyright	Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2020
Copyright_xml	– notice: Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2020
DBID	97E ESBDL RIA RIE AAYXX CITATION 7SC 7SP 7SR 8BQ 8FD JG9 JQ2 L7M L~C L~D DOA
DOI	10.1109/ACCESS.2019.2959783
DatabaseName	IEEE Xplore (IEEE) IEEE Xplore Open Access Journals IEEE All-Society Periodicals Package (ASPP) 1998–Present IEEE Electronic Library (IEL) CrossRef Computer and Information Systems Abstracts Electronics & Communications Abstracts Engineered Materials Abstracts METADEX Technology Research Database Materials Research Database ProQuest Computer Science Collection Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional DOAJ Open Access Full Text
DatabaseTitle	CrossRef Materials Research Database Engineered Materials Abstracts Technology Research Database Computer and Information Systems Abstracts – Academic Electronics & Communications Abstracts ProQuest Computer Science Collection Computer and Information Systems Abstracts Advanced Technologies Database with Aerospace METADEX Computer and Information Systems Abstracts Professional
DatabaseTitleList	Materials Research Database
Database_xml	– sequence: 1 dbid: DOA name: DOAJ Directory of Open Access Journals url: https://www.doaj.org/ sourceTypes: Open Website – sequence: 2 dbid: RIE name: IEEE Electronic Library (IEL) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher
DeliveryMethod	fulltext_linktorsrc
Discipline	Engineering
EISSN	2169-3536
EndPage	6189
ExternalDocumentID	oai_doaj_org_article_930ed8abe3b34955a86c9825a58d0c8a 10_1109_ACCESS_2019_2959783 8933112
Genre	orig-research
GrantInformation_xml	– fundername: Fundamental Research Funds for the Central Universities grantid: 63192616 funderid: 10.13039/501100012226 – fundername: Natural Science Foundation of Fujian Province grantid: 2017J01099 funderid: 10.13039/501100003392 – fundername: National Natural Science Foundation of China grantid: 61772441; 61872309; 61922020; 61425002; 61673328; 61872007 funderid: 10.13039/501100001809 – fundername: national key R&D program of China grantid: 2017YFE0130600 – fundername: Project of marine economic innovation and development in Xiamen grantid: 16PFW034SF02
GroupedDBID	0R~ 4.4 5VS 6IK 97E AAJGR ABAZT ABVLG ACGFS ADBBV AGSQL ALMA_UNASSIGNED_HOLDINGS BCNDV BEFXN BFFAM BGNUA BKEBE BPEOZ EBS EJD ESBDL GROUPED_DOAJ IPLJI JAVBF KQ8 M43 M~E O9- OCL OK1 RIA RIE RNS AAYXX CITATION 7SC 7SP 7SR 8BQ 8FD JG9 JQ2 L7M L~C L~D
ID	FETCH-LOGICAL-c408t-38da3c8c918151d36f51335a53ef8b34e4f681465b27e83c58225c7c3545f31a3
IEDL.DBID	DOA
ISICitedReferencesCount	5
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000524682100035&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	2169-3536
IngestDate	Fri Oct 03 12:52:26 EDT 2025 Sun Nov 30 05:22:22 EST 2025 Sat Nov 29 02:41:40 EST 2025 Tue Nov 18 19:52:48 EST 2025 Wed Aug 27 02:41:43 EDT 2025
IsDoiOpenAccess	true
IsOpenAccess	true
IsPeerReviewed	true
IsScholarly	true
Language	English
License	https://creativecommons.org/licenses/by/4.0/legalcode
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c408t-38da3c8c918151d36f51335a53ef8b34e4f681465b27e83c58225c7c3545f31a3
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
ORCID	0000-0002-6011-2691 0000-0003-1955-1366 0000-0002-0817-0878 0000-0003-0402-3034 0000-0002-8576-2439
OpenAccessLink	https://doaj.org/article/930ed8abe3b34955a86c9825a58d0c8a
PQID	2454962105
PQPubID	4845423
PageCount	13
ParticipantIDs	crossref_citationtrail_10_1109_ACCESS_2019_2959783 proquest_journals_2454962105 crossref_primary_10_1109_ACCESS_2019_2959783 ieee_primary_8933112 doaj_primary_oai_doaj_org_article_930ed8abe3b34955a86c9825a58d0c8a
PublicationCentury	2000
PublicationDate	20200000 2020-00-00 20200101 2020-01-01
PublicationDateYYYYMMDD	2020-01-01
PublicationDate_xml	– year: 2020 text: 20200000
PublicationDecade	2020
PublicationPlace	Piscataway
PublicationPlace_xml	– name: Piscataway
PublicationTitle	IEEE access
PublicationTitleAbbrev	Access
PublicationYear	2020
Publisher	IEEE The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher_xml	– name: IEEE – name: The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
References	ref57 ref12 ref59 ref15 ref58 ref53 hwang (ref36) 1994 ref52 ref55 ref11 ref54 ref10 ref16 ref19 tamura (ref30) 1993; 10 rokas (ref4) 2003; 425 ref51 pearl (ref17) 1984 ref50 ref46 ref45 de laet (ref18) 2005 ref48 ref42 chor (ref13) 2005 ref41 ref44 ref49 ref8 tavaré (ref29) 1986; 17 ref3 ref6 ref5 ref40 ref35 ref34 ref37 coello (ref7) 2009; 272 ref31 ref33 ref32 wu (ref47) 2019; 131 ref2 ref1 ref39 zaharia (ref56) 2010; 10 pettey (ref43) 1987 ref38 zeng (ref68) 2019 wang (ref9) 0 ref24 ref67 ref23 ref26 ref69 ref25 ref64 ref20 ref63 wang (ref14) 0 ref66 ref22 ref65 ref21 ref28 ref27 ref60 ref62 ref61
References_xml	– ident: ref64 doi: 10.1109/TCBB.2017.2776280 – ident: ref12 doi: 10.1109/TEVC.2007.892759 – ident: ref51 doi: 10.1186/s12918-017-0476-3 – ident: ref25 doi: 10.1016/0025-5564(90)90123-G – ident: ref5 doi: 10.1109/TCBB.2007.070203 – volume: 131 start-page: 189 year: 2019 ident: ref47 article-title: A risk defense method based on microscopic state prediction with partial information observations in social networks publication-title: J Parallel Distrib Comput doi: 10.1016/j.jpdc.2019.04.007 – ident: ref60 doi: 10.1109/TCDS.2017.2785332 – ident: ref33 doi: 10.1086/509588 – ident: ref66 doi: 10.1093/bioinformatics/btz694 – year: 1984 ident: ref17 publication-title: Heuristics Intelligent Search Strategies for Computer Problem Solving – ident: ref26 doi: 10.1093/oxfordjournals.molbev.a026008 – year: 1987 ident: ref43 article-title: Parallel genetic algorithm publication-title: Proc 2nd Int Conf Genet Algorithms – ident: ref10 doi: 10.1017/CBO9780511819049 – ident: ref15 doi: 10.1109/TPDS.2014.2325828 – ident: ref45 doi: 10.1007/s00158-009-0460-7 – year: 1994 ident: ref36 publication-title: Multiple Objective Decision Making Methods and Applications – ident: ref61 doi: 10.1109/TNB.2018.2873221 – ident: ref39 doi: 10.1111/2041-210X.12529 – year: 0 ident: ref9 article-title: MTES: An intelligent trust evaluation scheme in sensor-cloud enabled industrial Internet of Things publication-title: IEEE Trans Ind Informat doi: 10.1023/A:1013737224969 – ident: ref52 doi: 10.1016/j.artmed.2017.02.005 – ident: ref21 doi: 10.1007/978-1-4471-5304-7_14 – ident: ref38 doi: 10.1007/978-3-642-13800-3_17 – ident: ref28 doi: 10.1007/BF02101694 – volume: 10 start-page: 95 year: 2010 ident: ref56 article-title: Spark: Cluster computing with working sets publication-title: HotCloud – ident: ref2 doi: 10.1109/TSMCC.2005.855515 – volume: 272 year: 2009 ident: ref7 publication-title: Advances in Multi-Objective Nature Inspired Computing – ident: ref35 doi: 10.1109/TEVC.2017.2749619 – ident: ref44 doi: 10.1073/pnas.162224399 – volume: 10 start-page: 512 year: 1993 ident: ref30 article-title: Estimation of the number of nucleotide substitutions in the control region of mitochondrial DNA in humans and chimpanzees publication-title: Mol Biol Evol – volume: 17 start-page: 57 year: 1986 ident: ref29 article-title: Some probabilistic and statistical problems in the analysis of DNA sequences publication-title: Lectures Math Life Sci – ident: ref37 doi: 10.1016/j.ins.2019.08.064 – ident: ref31 doi: 10.1007/BF01731581 – ident: ref53 doi: 10.1186/s13015-017-0116-x – ident: ref34 doi: 10.1111/j.1096-0031.2005.00054.x – ident: ref16 doi: 10.2307/2412810 – ident: ref63 doi: 10.1007/s11063-018-9947-9 – ident: ref46 doi: 10.1109/JIOT.2018.2870288 – ident: ref69 doi: 10.1093/bioinformatics/btz418 – year: 2005 ident: ref13 article-title: Maximum likelihood of evolutionary trees is hard publication-title: Proc Annu Int Conf Res Comput Mol Biol doi: 10.1007/11415770_23 – ident: ref40 doi: 10.1145/2925985 – year: 2019 ident: ref68 article-title: Predicting disease-associated circular RNAs using deep forests combined with positive-unlabeled learning methods publication-title: Briefings Bioinf – ident: ref49 doi: 10.1093/bioinformatics/btv177 – ident: ref20 doi: 10.1007/11415770_23 – ident: ref54 doi: 10.1093/gigascience/giy098 – ident: ref50 doi: 10.1016/j.artmed.2017.03.001 – ident: ref22 doi: 10.1017/CBO9780511819049 – ident: ref27 doi: 10.1016/B978-1-4832-3211-9.50009-7 – ident: ref42 doi: 10.1038/srep33870 – ident: ref8 doi: 10.1109/TEVC.2016.2600642 – ident: ref65 doi: 10.1093/bfgp/elv024 – ident: ref48 doi: 10.1016/j.jgg.2018.07.004 – year: 0 ident: ref14 article-title: Energy-efficient and trustworthy data collection protocol based on mobile fog computing in Internet of Things publication-title: IEEE Trans Ind Informat doi: 10.1023/A:1013737224969 – volume: 425 start-page: 798 year: 2003 ident: ref4 article-title: Genome-scale approaches to resolving incongruence in molecular phylogenies publication-title: Nature doi: 10.1038/nature02053 – ident: ref11 doi: 10.1109/4235.996017 – ident: ref24 doi: 10.2307/2406441 – ident: ref55 doi: 10.1021/acs.jproteome.7b00019 – ident: ref1 doi: 10.3724/SP.J.1259.2014.00049 – ident: ref6 doi: 10.1109/TEVC.2018.2883888 – ident: ref67 doi: 10.1016/j.ins.2019.05.070 – ident: ref41 doi: 10.3390/ijms19010062 – ident: ref62 doi: 10.1109/TNB.2019.2896981 – ident: ref3 doi: 10.1080/10635150050207401 – ident: ref57 doi: 10.1109/ICCSE.2016.7581647 – ident: ref23 doi: 10.1111/j.1558-5646.1981.tb04991.x – start-page: 81 year: 2005 ident: ref18 article-title: Parsimony and the problem of inapplicables in sequence data publication-title: Parsimony Phylogeny and Genomics – ident: ref32 doi: 10.1016/j.ins.2015.06.040 – ident: ref19 doi: 10.1007/BF00182187 – ident: ref58 doi: 10.1093/oxfordjournals.molbev.a025924 – ident: ref59 doi: 10.1111/2041-210X.12529
SSID	ssj0000816957
Score	2.1895413
Snippet	In recent years, inferring phylogenies has attracted lots of attention in both academic community and various application fields. Phylogenetic inference...
SourceID	doaj proquest crossref ieee
SourceType	Open Website Aggregation Database Enrichment Source Index Database Publisher
StartPage	6177
SubjectTerms	Biomembranes Combinatorial analysis Consensus Convergence Criteria Datasets Evolutionary algorithms Genetic algorithms Heuristic methods membrane structure Membrane structures Membranes multi-objective evolutionary algorithm Optimization parallel algorithm Parallel processing phylogenetic reconstruction Phylogenetics Phylogeny Reconstruction Topology Vegetation
SummonAdditionalLinks	– databaseName: IEEE Electronic Library (IEL) dbid: RIE link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1Nb9QwELVKxQEOQCmoCy3ygWPTJpn467hdtQKpLSvxod4sx5kIpJKtdlt-PzNeN6WiQuIWRbZl59nxvLFnnhDvg6pa0C4WwD6mpne6aHXvii7wGZwtW50cbt9Ozfm5vbhw8w2xP8bCIGK6fIYH_JjO8rtFvGFX2SFLw1csKfzIGLOO1Rr9KSwg4ZTJiYWq0h1OZzMaA9_ecgc19cRYuLf5pBz9WVTlrz9x2l5Onv9fx16IZ9mMlNM17ltiA4eX4ukfyQW3RZiHJQulXMqzT8dTeUTbVScXg2SJTta3WMkwdPIMfxJfHlB-Tolkb5YoyYyVHzkOkNuR8-9E6WmWcbCjZLJ6l3L2lfh6cvxl9qHIggpFbEp7XYDtAkQbHW3rqupA96zuooIC7G0LDTa9ZpegamuDFqIi60FFE4HMrB6qAK_F5rAYcEfIMgL0ZC7qxoYGySaqMVqy9qjNBgDMRNS3X9rHnG2cRS8ufWIdpfNreDzD4zM8E7E_VrpaJ9v4d_EjhnAsypmy0wvCxueF5x2U2NnQItAAnVLB6uiIFgdluzLaMBHbjOfYSIZyInZvJ4TPq3rl64bYtCaSrN48XOuteFIzH08uml2xSXjgnngcf13_WC3fpQn7Gy5L5sE priority: 102 providerName: IEEE
Title	Parallel MOEA Based on Consensus and Membrane Structure for Inferring Phylogenetic Reconstruction
URI	https://ieeexplore.ieee.org/document/8933112 https://www.proquest.com/docview/2454962105 https://doaj.org/article/930ed8abe3b34955a86c9825a58d0c8a
Volume	8
WOSCitedRecordID	wos000524682100035&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVAON databaseName: DOAJ Directory of Open Access Journals customDbUrl: eissn: 2169-3536 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000816957 issn: 2169-3536 databaseCode: DOA dateStart: 20130101 isFulltext: true titleUrlDefault: https://www.doaj.org/ providerName: Directory of Open Access Journals – providerCode: PRVHPJ databaseName: ROAD: Directory of Open Access Scholarly Resources customDbUrl: eissn: 2169-3536 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000816957 issn: 2169-3536 databaseCode: M~E dateStart: 20130101 isFulltext: true titleUrlDefault: https://road.issn.org providerName: ISSN International Centre
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1LS8QwEA4iHvQgPnF9kYNHq22nSZPjuqwouLrgA28hTVMUtMquevS3O5PWdUXQi5ceSpq2M9Pk-6bJN4ztWZEUILWLgHJMWaVlVMhKR6Wlf3AqLmRIuN2c5efn6vZWD6dKfdGasEYeuDHcoYbYl8oWHgpAMC-skk4jrbFClbFTARoh6pkiU2EMVonUIm9lhpJYH3Z7PXwjWsulD1J8rlzBt6koKPa3JVZ-jMthsjleYostSuTd5umW2YyvV9jClHbgKrNDO6I6KA98cNHv8iOcjUr-VHOqwEnlK8bc1iUf-Eekw7Xnl0En9nXkOaJUfkrb_KgfPrxDxo5BRHsZOXHRL0XZNXZ93L_qnURtvYTIZbF6iUCVFpxyGmdtkZQgKyregpYCXym0ns8qSRk_UaS5V-AEggPhcgeIoipILKyz2fqp9huMxw6gQjQoM2Uzj5An9U4hmMM-MwDIOyz9NJ1xrZg41bR4MIFUxNo09jZkb9Pau8P2Jxc9N1oavzc_Ip9MmpIQdjiB4WHa8DB_hUeHrZJHJ50gPAOEmB22_elh0360Y5NmSJYlcmCx-R-33mLzKZHzkK_ZZrPoPb_D5tzby_14tBviFY-D9_5u2HX4AUMp7BE
linkProvider	Directory of Open Access Journals
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1Nb9QwEB1VBQl64KsgFgr4wLFpk4zt2MftqlUrdpeVKKg3y3EcFalkq92W38-MNw0gEBK3KLItO8-O54098wDee1XUqG3IkH1MsrU6q3Vrs8bzGZzJa50cbl-m1XxuLi7sYgv2h1iYGGO6fBYP-DGd5TfLcMuuskOWhi9YUviekrIsNtFag0eFJSSsqvrUQkVuD8eTCY2C72_Zg5L6Uhn8bftJWfp7WZU__sVpgzl5_H9dewKPekNSjDfIP4Wt2D2DnV_SC-6CX_gVS6VcidnH47E4og2rEctOsEgnK1yshe8aMYvfiDF3UXxKqWRvV1GQISvOOBKQ2xGLSyL1NM843FEwXf2ZdPY5fD45Pp-cZr2kQhZkbm4yNI3HYIKljV0VDeqW9V2UVxhbU6OMstXsFFR1WUWDQZH9oEIVkAytFguPL2C7W3bxJYg8ILZkMGppvIxkFZUxGLL3qE2JiNUIyrsv7UKfb5xlL65c4h25dRt4HMPjenhGsD9Uut6k2_h38SOGcCjKubLTC8LG9UvPWcxjY3wdkQZolfJGB0vE2CvT5MH4EewynkMjPZQj2LubEK5f12tXSuLTmmiyevX3Wu_gwen5bOqmZ_MPr-Fhyew8OWz2YJuwiW_gfvh-83W9epsm7w9T-OoI
openUrl	ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Parallel+MOEA+Based+on+Consensus+and+Membrane+Structure+for+Inferring+Phylogenetic+Reconstruction&rft.jtitle=IEEE+access&rft.au=Zhang%2C+Qianqian&rft.au=Zhang%2C+Jun&rft.au=Zhong%2C+Yue&rft.au=Ye%2C+Congming&rft.date=2020&rft.issn=2169-3536&rft.eissn=2169-3536&rft.volume=8&rft.spage=6177&rft.epage=6189&rft_id=info:doi/10.1109%2FACCESS.2019.2959783&rft.externalDBID=n%2Fa&rft.externalDocID=10_1109_ACCESS_2019_2959783
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2169-3536&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2169-3536&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2169-3536&client=summon