1 research outputs found
A System to Discover Correlations within a Biological Pathway between the Expression Levels of Genes
[[abstract]]"Current pathway presentation method to the
biologist is static graph. The analysis of differentially expressed
genes using microarray gene expression data can help to find
factors that affect diseases. However, the differentially expressed
genes that are identified may be too large in number and it's
difficult for biologist to pinpoint the correlations between genes
and crucial points on pathway interactively. In this study, we
propose a method that attempts to avoid this problem and allows
the discovery of greater biological meaning than the traditional
method. We select a gene pair set of interacting genes in a
biological pathway and investigate the correlation in expression
between the gene pairs under different condition (such as relapsed
and non-relapsed breast cancer) using microarray gene expression
data. We tested the approach using breast cancer relapsed and
non-relapsed datasets in order to demonstrate that our method is
both useful and reliable; very stable results were obtained when
the same microarray platform was used. We finally use an
interface to display correlations within a biological pathway.