Modules Identification in Gene Positive Networks of Hepatocellular Carcinoma Using Pearson Agglomerative Method and Pearson Cohesion Coupling Modularity

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...

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Bibliographic Details
Published in:Journal of Applied Mathematics 2012-01, Vol.2012 (2012), p.551-571-133
Main Authors: Hu, Jinyu, Gao, Zhiwei
Format: Article
Language:English
Subjects:
Algorithms
Biomathematics
Cancer
Cancer therapies
Development and progression
Gene therapy
Genetic aspects
Graphs
Hepatoma
Liver cancer
Mortality
Physiological aspects
Proteins
Studies
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Summary: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.
ISSN:1110-757X
1687-0042
DOI:10.1155/2012/248658