Finding edging genes from microarray data
Data(s) |
30/06/2008
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Resumo |
<b>Motivation</b>: A set of genes and their gene expression levels are used to classify disease and normal tissues. Due to the massive number of genes in microarray, there are a large number of edges to divide different classes of genes in microarray space. The edging genes (EGs) can be co-regulated genes, they can also be on the same pathway or deregulated by the same non-coding genes, such as siRNA or miRNA. Every gene in EGs is vital for identifying a tissue's class. The changing in one EG's gene expression may cause a tissue alteration from normal to disease and vice versa. Finding EGs is of biological importance. In this work, we propose an algorithm to effectively find these EGs.<br /><b><br />Result</b>: We tested our algorithm with five microarray datasets. The results are compared with the border-based algorithm which was used to find gene groups and subsequently divide different classes of tissues. Our algorithm finds a significantly larger amount of EGs than does the border-based algorithm. As our algorithm prunes irrelevant patterns at earlier stages, time and space complexities are much less prevalent than in the border-based algorithm.<br /> |
Identificador | |
Idioma(s) |
eng |
Publicador |
Elsevier BV |
Relação |
http://dro.deakin.edu.au/eserv/DU:30017632/an-findingedging-2008.pdf http://dx.doi.org/10.1016/j.jbiotec.2008.04.004 |
Direitos |
2008, Elsevier B.V. |
Palavras-Chave | #microarray data analysis; ; #edging genes #classifications |
Tipo |
Journal Article |