Digitale Bibliotheek
Sluiten Bladeren door artikelen uit een tijdschrift
   volgende >>
     Tijdschrift beschrijving
       Alle jaargangen van het bijbehorende tijdschrift
         Alle afleveringen van het bijbehorende jaargang
           Alle artikelen van de bijbehorende aflevering
                                       Details van artikel 1 van 7 gevonden artikelen
  A framework for modelling virus gene expression data
Titel: A framework for modelling virus gene expression data
Auteur: Paul Kellam
Xiaohui Liu
Nigel Martin
Christine Orengo
Stephen Swift
Allan Tucker
Verschenen in: Intelligent data analysis
Paginering: Jaargang 6 (2002) nr. 3 pagina's 267-279
Jaar: 2002-08-30
Inhoud: Short, high-dimensional, Multivariate Time Series (MTS) data are common in many fields such as medicine, finance and science, and any advance in modelling this kind of data would be beneficial. Nowhere is this truer than functional genomics where effective ways of analysing gene expression data are urgently needed. Progress in this area could help obtain a "global" view of biological processes, and ultimately lead to a great improvement in the quality of human life. We present a computational framework for modelling this type of data, and report experimental results of applying this framework to the analysis of gene expression data in the virology domain. The framework contains a three-step modelling strategy: correlation search, variable grouping, and short MTS modelling. Novel research is involved in each step which has been individually tested on different real-world datasets in engineering and medicine. This is the first attempt to integrate all these components into a coherent computational framework, and test the framework on a very challenging application area, producing promising results.
Uitgever: IOS Press
Bronbestand: Elektronische Wetenschappelijke Tijdschriften

                             Details van artikel 1 van 7 gevonden artikelen
   volgende >>
 Koninklijke Bibliotheek - Nationale Bibliotheek van Nederland