mycoreobjectrosdok_thesis_0000000021rosdok_thesis_0000000021rosdokthesisrosdok_derivate_00000376872023-08-08T09:26:42.536Z2017-08-25T15:27:42.815ZadministratoreditorTpublished1rosdok_derivate_0000037687truetruederivate_types:fulltextVolltextfulltextwf_edit_epub wf_register_epubstate:publishedstate:publishedveröffentlichtpublishedrosdok/id000002701032992093Oau2018-10-172023-08-05T18:55:47ZrdaConverted from PICA to MODS using Pica2Mods XSLT Transformer 2.7 [SCM: "0c0e7a3c226a4a0cbcbec39b493c3c5257339ab8" "v2.7" "2023-08-04T00:00:00+0200"] with mode 'DEFAULT'.MasterarbeitHochschulschriftTowards a biological modelling tool recommending proper subnetworksThe aim of this thesis is to develop methods that suggest the users suitable subnetworks for integration during modelling. To this end, techniques from the field of recommender systems are used, which aim to predict the users’ interest in certain objects in order to filter and recommend the most suitable ones. Especially association rule mining is of particular relevance in this thesis. Its algorithms offer the opportunity to find patterns of joint appearance in a large set of items. For this purpose, biological networks are considered, which are represented as graphs and annotated with standardised ontology terms. Association rule mining then is applied with respect to structural and also to semantic similarity. For a partly modelled biological network the elements are found that may extend it. The obtained results form a solid basis for the development of a recommender system that facilitates the efficient reuse of networks and decreases the manual effort to find and integrate relevant structures.FabienneLambusch1991 -VerfasserInaut11388889310000-0002-0303-1430KurtSandkuhl1963 -AkademischeR BetreuerIndgs1434454800000-0002-7431-8412DagmarWaltemath1981 -AkademischeR BetreuerIndgs10168557530000-0002-5886-556338329-6Universität Rostock1419 -Grad-verleihende Institutiondgg10085032-7Universität RostockFakultät für Informatik und Elektrotechnik2004 -Grad-verleihende Institutiondgghttp://purl.uni-rostock.de/rosdok/id00000270urn:nbn:de:gbv:28-thesis2017-0002-110.18453/rosdok_id00000270004 InformatikFakultät für Informatik und Elektrotechnikalle Rechte vorbehaltenNutzungsrechte erteiltLizenz Metadaten: CC0frei zugänglich (Open Access)de2016Universität RostockRostockmonographic201720162018Universitätsbibliothek RostockRostock2018Universitätsbibliothek Rostockhttp://purl.uni-rostock.de/rosdok/id00000270vorgelegt von Fabienne Lambuschdoctype:epubdoctype:epubDokumenttypDocument typedoctype:epub.masterthesisdoctype:epub.masterthesisMasterarbeitmaster thesisdiniPublType:masterThesis diniPublType2022:MasterThesis XMetaDissPlusThesisLevel:masterinfo:eu-repo/semantics/masterThesisdocumentnatureOfContent:ppn_105825778natureOfContent:ppn_105825778HochschulschriftdiniPublType2022:MasterThesisdiniPublType2022:MasterThesisAbschlussarbeit (Master)master thesisDRIVERXMetaDissPlusThesisLevel:masterXMetaDissPlusThesisLevel:masterMasterarbeitmaster thesisSDNB:004SDNB:004004 Informatik004 Data processing Computer sciencesinstitution:unirostockinstitution:unirostockUniversität RostockUniversity of RostockUniversität RostockUniversität RostockUni.Rostockhttp://d-nb.info/gnd/38329-6institution:unirostock.iefinstitution:unirostock.iefFakultät für Informatik und ElektrotechnikFaculty of Computer Science and Electrical EngineeringUniversität Rostock. Fakultät für Informatik und ElektrotechnikFakultät für Informatik<br />und ElektrotechnikUni.Rostock.Fakultaet.IEFhttp://d-nb.info/gnd/10085032-7licenseinfo:worklicenseinfo:workWerkworklicenseinfo:work.rightsreservedlicenseinfo:work.rightsreservedalle Rechte vorbehaltenall rights reserved/creativecommons/r/reserved/0.9/88x31.png[DE-28]Urheberrechtsschutz 1.0$gRights Statements$uhttp://rightsstatements.org/vocab/InC/1.0/http://rightsstatements.org/vocab/InC/1.0/http://rightsstatements.org/vocab/InC/1.0/licenseinfo:depositlicenseinfo:depositVeröffentlichungsgenehmigungpermission to storelicenseinfo:deposit.rightsgrantedlicenseinfo:deposit.rightsgrantedNutzungsrechte erteiltrights grantedlicenseinfo:metadatalicenseinfo:metadataLizenzen für Metadatenlicenseinfo:metadata.cc0licenseinfo:metadata.cc0Lizenz Metadaten: CC0license metadata: CC0/creativecommons/p/zero/1.0/88x31.pnghttps://creativecommons.org/publicdomain/zero/1.0/accesscondition:openaccessaccesscondition:openaccessfrei zugänglich (Open Access)open accesshttp://purl.org/coar/access_right/c_abf2OAfreeinfo:eu-repo/semantics/openAccess[DE-28]Open Access$gControlled Vocabulary for Access Rights$uhttp://purl.org/coar/access_right/c_abf2rfc5646:derfc5646:deDeutschGermangerdeuTowards a biological modelling tool recommending proper subnetworksTowards a biological modelling tool recommending proper subnetworksgnd:1138888931orcid:0000-0002-0303-1430gnd:143445480orcid:0000-0002-7431-8412gnd:1016855753orcid:0000-0002-5886-5563gnd:38329-6gnd:10085032-7gnd:1138888931orcid:0000-0002-0303-1430gnd:143445480orcid:0000-0002-7431-8412gnd:1016855753orcid:0000-0002-5886-5563gnd:38329-6gnd:10085032-7rosdok_thesis_0000000021-d454270e52gnd:1138888931orcid:0000-0002-0303-1430Fabienne LambuschFabienne Lambuschrosdok_thesis_0000000021-d454270e68gnd:143445480orcid:0000-0002-7431-8412Kurt SandkuhlKurt Sandkuhlrosdok_thesis_0000000021-d454270e84gnd:1016855753orcid:0000-0002-5886-5563Dagmar WaltemathDagmar Waltemathrosdok_thesis_0000000021-d454270e100gnd:38329-6Universität RostockUniversität Rostockrosdok_thesis_0000000021-d454270e112gnd:10085032-7Universität Rostock Fakultät für Informatik und ElektrotechnikUniversität Rostock Fakultät für Informatik und ElektrotechnikFabienne LambuschKurt SandkuhlDagmar WaltemathUniversität RostockUniversität Rostock Fakultät für Informatik und ElektrotechnikFabienne LambuschKurt SandkuhlDagmar WaltemathUniversität RostockUniversität Rostock Fakultät für Informatik und ElektrotechnikFabienne LambuschRostockUniversität Rostockepub.masterthesishttp://purl.uni-rostock.de/rosdok/id00000270urn:nbn:de:gbv:28-thesis2017-0002-110.18453/rosdok_id00000270The aim of this thesis is to develop methods that suggest the users suitable subnetworks for integration during modelling. To this end, techniques from the field of recommender systems are used, which aim to predict the users’ interest in certain objects in order to filter and recommend the most suitable ones. Especially association rule mining is of particular relevance in this thesis. Its algorithms offer the opportunity to find patterns of joint appearance in a large set of items. For this purpose, biological networks are considered, which are represented as graphs and annotated with standardised ontology terms. Association rule mining then is applied with respect to structural and also to semantic similarity. For a partly modelled biological network the elements are found that may extend it. The obtained results form a solid basis for the development of a recommender system that facilitates the efficient reuse of networks and decreases the manual effort to find and integrate relevant structures.20162016vorgelegt von Fabienne Lambuschepub.masterthesis1 Master_Lambusch_2017.pdf 4314311 3d7e53fd690fc1b413d8cc70e8995bca rosdok/id000002701032992093Oau2018-10-172023-08-05T18:55:47ZrdaConverted from PICA to MODS using Pica2Mods XSLT Transformer 2.7 [SCM: "0c0e7a3c226a4a0cbcbec39b493c3c5257339ab8" "v2.7" "2023-08-04T00:00:00+0200"] with mode 'DEFAULT'.MasterarbeitHochschulschriftTowards a biological modelling tool recommending proper subnetworksThe aim of this thesis is to develop methods that suggest the users suitable subnetworks for integration during modelling. To this end, techniques from the field of recommender systems are used, which aim to predict the users’ interest in certain objects in order to filter and recommend the most suitable ones. Especially association rule mining is of particular relevance in this thesis. Its algorithms offer the opportunity to find patterns of joint appearance in a large set of items. For this purpose, biological networks are considered, which are represented as graphs and annotated with standardised ontology terms. Association rule mining then is applied with respect to structural and also to semantic similarity. For a partly modelled biological network the elements are found that may extend it. The obtained results form a solid basis for the development of a recommender system that facilitates the efficient reuse of networks and decreases the manual effort to find and integrate relevant structures.FabienneLambusch1991 -VerfasserInaut11388889310000-0002-0303-1430KurtSandkuhl1963 -AkademischeR BetreuerIndgs1434454800000-0002-7431-8412DagmarWaltemath1981 -AkademischeR BetreuerIndgs10168557530000-0002-5886-556338329-6Universität Rostock1419 -Grad-verleihende Institutiondgg10085032-7Universität RostockFakultät für Informatik und Elektrotechnik2004 -Grad-verleihende Institutiondgghttp://purl.uni-rostock.de/rosdok/id00000270urn:nbn:de:gbv:28-thesis2017-0002-110.18453/rosdok_id00000270004 InformatikFakultät für Informatik und Elektrotechnikalle Rechte vorbehaltenNutzungsrechte erteiltLizenz Metadaten: CC0frei zugänglich (Open Access)de2016Universität RostockRostockmonographic201720162018Universitätsbibliothek RostockRostock2018Universitätsbibliothek Rostockhttp://purl.uni-rostock.de/rosdok/id00000270vorgelegt von Fabienne Lambusch 2017-08-25T15:27:42.815Z 2023-08-08T09:26:42.536Z 2023-08-18T09:26:42.570Z editorT {"identifier":"rosdok/id00000270","type":"local_id","additional":"","service":"MCRLocalID","created":"2018-06-30T10:28:30.003Z"} {"identifier":"http://purl.uni-rostock.de/rosdok/id00000270","type":"purl","additional":"","service":"RosDokPURL","created":"2018-06-30T10:28:30.080Z","registered":"2018-06-30T10:28:30.080Z"} {"identifier":"10.18453/rosdok_id00000270","type":"doi","additional":"","service":"RosDokDOI","created":"2018-06-30T10:28:31.427Z","registered":"2018-06-30T10:28:31.427Z"} {"identifier":"urn:nbn:de:gbv:28-thesis2017-0002-1","type":"dnbUrn","additional":"","service":"RosDokURN","created":"2018-06-30T10:28:30.009Z","registered":"2018-08-15T12:50:54.030Z"} administratorfulltextfile/rosdok_thesis_0000000021/rosdok_derivate_0000037687/Master_Lambusch_2017.pdfTowards a biological modelling tool recommending proper subnetworksTowards a biological modelling tool recommending proper subnetworksgnd:1138888931orcid:0000-0002-0303-1430gnd:143445480orcid:0000-0002-7431-8412gnd:1016855753orcid:0000-0002-5886-5563gnd:38329-6gnd:10085032-7gnd:1138888931orcid:0000-0002-0303-1430gnd:143445480orcid:0000-0002-7431-8412gnd:1016855753orcid:0000-0002-5886-5563gnd:38329-6gnd:10085032-7rosdok_thesis_0000000021-d454270e52gnd:1138888931orcid:0000-0002-0303-1430Fabienne LambuschFabienne Lambuschrosdok_thesis_0000000021-d454270e68gnd:143445480orcid:0000-0002-7431-8412Kurt SandkuhlKurt Sandkuhlrosdok_thesis_0000000021-d454270e84gnd:1016855753orcid:0000-0002-5886-5563Dagmar WaltemathDagmar Waltemathrosdok_thesis_0000000021-d454270e100gnd:38329-6Universität RostockUniversität Rostockrosdok_thesis_0000000021-d454270e112gnd:10085032-7Universität Rostock Fakultät für Informatik und ElektrotechnikUniversität Rostock Fakultät für Informatik und ElektrotechnikFabienne LambuschKurt SandkuhlDagmar WaltemathUniversität RostockUniversität Rostock Fakultät für Informatik und ElektrotechnikFabienne LambuschKurt SandkuhlDagmar WaltemathUniversität RostockUniversität Rostock Fakultät für Informatik und ElektrotechnikFabienne LambuschRostockUniversität Rostockepub.masterthesishttp://purl.uni-rostock.de/rosdok/id00000270urn:nbn:de:gbv:28-thesis2017-0002-110.18453/rosdok_id00000270The aim of this thesis is to develop methods that suggest the users suitable subnetworks for integration during modelling. To this end, techniques from the field of recommender systems are used, which aim to predict the users’ interest in certain objects in order to filter and recommend the most suitable ones. Especially association rule mining is of particular relevance in this thesis. Its algorithms offer the opportunity to find patterns of joint appearance in a large set of items. For this purpose, biological networks are considered, which are represented as graphs and annotated with standardised ontology terms. Association rule mining then is applied with respect to structural and also to semantic similarity. For a partly modelled biological network the elements are found that may extend it. The obtained results form a solid basis for the development of a recommender system that facilitates the efficient reuse of networks and decreases the manual effort to find and integrate relevant structures.20162016vorgelegt von Fabienne Lambusch[xslt]Saxonrosdok/id00000270https://purl.uni-rostock.de/rosdok/id00000270103299209310.18453/rosdok_id00000270urn:nbn:de:gbv:28-thesis2017-0002-1Fabienne LambuschLambusch FabienneTowards a biological modelling tool recommending proper subnetworksMasterarbeitmaster thesisUniversität Rostock, 2016The aim of this thesis is to develop methods that suggest the users suitable subnetworks for integration during modelling. To this end, techniques from the field of recommender systems are used, which aim to predict the users’ interest in certain objects in order to filter and recommend the most…Fabienne LambuschTowards a biological modelling tool recommending proper subnetworksUniversitätsbibliothek Rostockhttp://purl.uni-rostock.de/rosdok/id00000270FabienneLambusch1991 -VerfasserInaut11388889310000-0002-0303-1430KurtSandkuhl1963 -AkademischeR BetreuerIndgs1434454800000-0002-7431-8412DagmarWaltemath1981 -AkademischeR BetreuerIndgs10168557530000-0002-5886-556338329-6Universität Rostock1419 -Grad-verleihende Institutiondgg10085032-7Universität RostockFakultät für Informatik und Elektrotechnik2004 -Grad-verleihende Institutiondgg[purl]http://purl.uni-rostock.de/rosdok/id00000270[urn]urn:nbn:de:gbv:28-thesis2017-0002-1[doi]10.18453/rosdok_id00000270open_access20162016epoch:21th_centuryrfc5646:dedoctype:epub.masterthesisaccesscondition:openaccessSDNB:004institution:unirostock.iefstate:published