Angelova, Maia, Myers, Chris and Faith, Joe (2008) Classification of genes based on gene expression analysis. Physics of Atomic Nuclei, 71 (5). pp. 780-787. ISSN 1063-7788
Full text not available from this repository. (Request a copy)Abstract
Systems biology and bioinformatics are now major fields for productive research. DNA microarrays and other array technologies and genome sequencing have advanced to the point that it is now possible to monitor gene expression on a genomic scale. Gene expression analysis is discussed and some important clustering techniques are considered. The patterns identified in the data suggest similarities in the gene behavior, which provides useful information for the gene functionalities. We discuss measures for investigating the homogeneity of gene expression data in order to optimize the clustering process. We contribute to the knowledge of functional roles and regulation of E. coli genes by proposing a classification of these genes based on consistently correlated genes in expression data and similarities of gene expression patterns. A new visualization tool for targeted projection pursuit and dimensionality reduction of gene expression data is demonstrated.
Item Type: | Article |
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Subjects: | C400 Genetics |
Department: | Faculties > Engineering and Environment > Computer and Information Sciences |
Depositing User: | EPrint Services |
Date Deposited: | 22 Jul 2009 12:01 |
Last Modified: | 13 Oct 2019 00:24 |
URI: | http://nrl.northumbria.ac.uk/id/eprint/3634 |
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