Modules Identification in Gene Positive Networks of Hepatocellular Carcinoma Using Pearson Agglomerative Method and Pearson Cohesion Coupling Modularity
Joint Authors
Source
Journal of Applied Mathematics
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-21, 21 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-09-23
Country of Publication
Egypt
No. of Pages
21
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Hu, Jinyu& 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،Vol. 2012, no. 2012, pp.1-21.
https://search.emarefa.net/detail/BIM-993072
Modern Language Association (MLA)
Hu, Jinyu& Gao, Zhiwei. Modules Identification in Gene Positive Networks of Hepatocellular Carcinoma Using Pearson Agglomerative Method and Pearson Cohesion Coupling Modularity. Journal of Applied Mathematics No. 2012 (2012), pp.1-21.
https://search.emarefa.net/detail/BIM-993072
American Medical Association (AMA)
Hu, Jinyu& Gao, Zhiwei. Modules Identification in Gene Positive Networks of Hepatocellular Carcinoma Using Pearson Agglomerative Method and Pearson Cohesion Coupling Modularity. Journal of Applied Mathematics. 2012. Vol. 2012, no. 2012, pp.1-21.
https://search.emarefa.net/detail/BIM-993072
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-993072