DocumentCode
1576595
Title
Assessing the Codetermination of Gene Transcriptional States Using Both Superscalar and Vector Multiple Processor Systems
Author
Martino, R.L. ; Russ, D.E. ; Johnson, C.A.
Author_Institution
Div. of Comput. Bioscience, Nat. Inst. of Health, Bethesda, MD
fYear
2006
Firstpage
4779
Lastpage
4782
Abstract
An important goal of functional genomics is to develop methods for determining ways in which individual actions of genes are integrated in the cell. One way of gaining insight into a gene´s role in cellular activity is to study its expression pattern in a variety of circumstances and contexts, as it responds to its environment and to the action of other genes. Microarrays provide large-scale surveys of gene expression in which transcript levels can be determined for thousands of genes simultaneously. The coefficient of determination (CoD) has been proposed for the analysis of gene interaction via multivariate expression arrays. Parallel computing is essential to the application of the CoD to a large set of genes because of the large number of expression-based functions that must be statistically designed and compared. The results of the calculation of the CoD for a large set of genes with multiple superscalar processors are presented. A proposal for calculating the CoD with multiple vector processors is described. Multiple vector processor systems offer the potential to greatly reduce the time to calculate the CoD for a large set of genes
Keywords
biology computing; cellular biophysics; computer networks; genetics; molecular biophysics; vector processor systems; cellular activity; determination coefficient; functional genomics; gene expression pattern; gene interaction; gene transcriptional states; microarrays; multiple superscalar processors; multiple vector processors; multivariate expression arrays; parallel computing; Bioinformatics; Biological information theory; DNA; Gene expression; Genomics; Humans; Information technology; Large-scale systems; Parallel processing; Vector processors; Computational biology; gene expression analysis; microarray analysis; multiple processors; parallel computing; vector processing;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the
Conference_Location
Shanghai
Print_ISBN
0-7803-8741-4
Type
conf
DOI
10.1109/IEMBS.2005.1615540
Filename
1615540
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