Please use this identifier to cite or link to this item: https://doi.org/10.1093/bioinformatics/btq276
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dc.titleDA 1.0: Parameter estimation of biological pathways using data assimilation approach
dc.contributor.authorKoh, C.H.
dc.contributor.authorNagasaki, M.
dc.contributor.authorSaito, A.
dc.contributor.authorWong, L.
dc.contributor.authorMiyano, S.
dc.date.accessioned2013-07-04T07:48:54Z
dc.date.available2013-07-04T07:48:54Z
dc.date.issued2010
dc.identifier.citationKoh, C.H., Nagasaki, M., Saito, A., Wong, L., Miyano, S. (2010). DA 1.0: Parameter estimation of biological pathways using data assimilation approach. Bioinformatics 26 (14) : 1794-1796. ScholarBank@NUS Repository. https://doi.org/10.1093/bioinformatics/btq276
dc.identifier.issn13674803
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/39759
dc.description.abstractSummary: Data assimilation (DA) is a computational approach that estimates unknown parameters in a pathway model using time-course information. Particle filtering, the underlying method used, is a well-established statistical method that approximates the joint posterior distributions of parameters by using sequentially generated Monte Carlo samples. In this article, we report the release of Java-based software (DA 1.0) with an intuitive and user-friendly interface to allow users to carry out parameters estimation using DA. © The Author 2010.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1093/bioinformatics/btq276
dc.sourceScopus
dc.typeArticle
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.doi10.1093/bioinformatics/btq276
dc.description.sourcetitleBioinformatics
dc.description.volume26
dc.description.issue14
dc.description.page1794-1796
dc.description.codenBOINF
dc.identifier.isiut000279474400023
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