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dc.contributor.authorWu, Zujian
dc.contributor.authorPang, Wei
dc.contributor.authorCoghill, George M.
dc.date.accessioned2015-12-14T10:57:01Z
dc.date.available2015-12-14T10:57:01Z
dc.date.issued2015-12
dc.identifier.citationWu , Z , Pang , W & Coghill , G M 2015 , ' An Integrated Qualitative and Quantitative Biochemical Model Learning Framework Using Evolutionary Strategy and Simulated Annealing ' Cognitive Computation , vol. 7 , no. 6 , pp. 637-651 . https://doi.org/10.1007/s12559-015-9328-xen
dc.identifier.issn1866-9956
dc.identifier.otherPURE: 49483110
dc.identifier.otherPURE UUID: 496e15d1-34e8-4219-aea5-feffd039d309
dc.identifier.otherScopus: 84949532109
dc.identifier.otherORCID: /0000-0002-1761-6659/work/59923298
dc.identifier.urihttp://hdl.handle.net/2164/5289
dc.identifier.urihttp://link.springer.com/article/10.1007%2Fs12559-015-9328-xen
dc.descriptionThe authors would like to thank the support on this research by the CRISP Project (Combinatorial Responses In Stress Pathways) funded by the BBSRC (BB/F00513X/1) under the Systems Approaches to Biological Research (SABR) Initiative.en
dc.format.extent15en
dc.language.isoeng
dc.relation.ispartofCognitive Computationen
dc.rightsThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http:// creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.en
dc.subjectevolutionary algorithmsen
dc.subjectheuristic algorithmsen
dc.subjectqualitative model learningen
dc.subjectquantitative model learningen
dc.subjectsystems biologyen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectBiotechnology and Biological Sciences Research Council (BBSRC)en
dc.subjectBB/F00513X/1)en
dc.subject.lccQA75en
dc.titleAn Integrated Qualitative and Quantitative Biochemical Model Learning Framework Using Evolutionary Strategy and Simulated Annealingen
dc.typeJournal articleen
dc.contributor.institutionUniversity of Aberdeen, Computing Scienceen
dc.contributor.institutionUniversity of Aberdeen, Institute for Complex Systems and Mathematical Biology (ICSMB)en
dc.contributor.institutionUniversity of Aberdeen, University of Aberdeenen
dc.description.statusPeer revieweden
dc.description.versionPublisher PDFen
dc.identifier.doihttps://doi.org/10.1007/s12559-015-9328-x


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