Digital Library
Close Browse articles from a journal
   next >>
     Journal description
       All volumes of the corresponding journal
         All issues of the corresponding volume
           All articles of the corresponding issues
                                       Details for article 1 of 7 found articles
  A framework for modelling virus gene expression data
Title: A framework for modelling virus gene expression data
Author: Paul Kellam
Xiaohui Liu
Nigel Martin
Christine Orengo
Stephen Swift
Allan Tucker
Appeared in: Intelligent data analysis
Paging: Volume 6 (2002) nr. 3 pages 267-279
Year: 2002-08-30
Contents: 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.
Publisher: IOS Press
Source file: Elektronische Wetenschappelijke Tijdschriften

                             Details for article 1 of 7 found articles
   next >>
 Koninklijke Bibliotheek - National Library of the Netherlands