Modules identification in gene positive networks of hepatocellular carcinoma using pearson agglomerative method and Pearson cohesion coupling modularity

Hu, Jinyu and Gao, Zhiwei (2012) Modules identification in gene positive networks of hepatocellular carcinoma using pearson agglomerative method and Pearson cohesion coupling modularity. Journal of Applied Mathematics, 2012. ISSN 1110-757X

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Official URL: http://dx.doi.org/10.1155/2012/248658

Abstract

In this study, a gene positive network is proposed based on a weighted undirected graph, where the weight represents the positive correlation of the genes. A Pearson agglomerative clustering algorithm is employed to build a clustering tree, where dotted lines cut the tree from bottom to top leading to a number of subsets of the modules. In order to achieve better module partitions, the Pearson correlation coefficient modularity is addressed to seek optimal module decomposition by selecting an optimal threshold value. For the liver cancer gene network under study, we obtain a strong threshold value at 0.67302, and a very strong correlation threshold at 0.80086. On the basis of these threshold values, fourteen strong modules and thirteen very strong modules are obtained respectively. A certain degree of correspondence between the two types of modules is addressed as well. Finally, the biological significance of the two types of modules is analyzed and explained, which shows that these modules are closely related to the proliferation and metastasis of liver cancer. This discovery of the new modules may provide new clues and ideas for liver cancer treatment.

Item Type: Article
Additional Information: Article ID 248658, 21 pages
Subjects: H100 General Engineering
H600 Electronic and Electrical Engineering
Department: Faculties > Engineering and Environment > Mathematics and Information Sciences
Faculties > Engineering and Environment > Physics and Electrical Engineering
Related URLs:
Depositing User: Zhiwei Gao
Date Deposited: 27 Sep 2012 08:30
Last Modified: 09 May 2017 05:11
URI: http://nrl.northumbria.ac.uk/id/eprint/9211

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