A Statistical Method For Identifying Phenotypic Genes Using Biological Networks

In biological networks, the high connectivity genes often associated with significant disease pathways.Because between the various molecules in cells’ s interconnected functions on a single abnormal gene may lead to complex diseases. More specific abnormal genes through the network, affect the activity of other normal gene’production. Therefore, the study will be applied to biological networks identified phenotype associated genes are essential.The applications of node centrality index has been in a variety of areas, such as cardiovascular disease and cancer research.In the network, the relationship between genes and their graphics can be represented as nodes and edges. Pearson correlation coefficients between the network side is a strong predictor of biological relationships.This article presents a method that identifies the phenotype associated genes based on centers index scores and biological networks.According to comparing with the degree indicator, the central node method for detecting genes is very effective.