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Gene Coexpression Network Comparison via Persistent Homology
Joint Authors
Source
International Journal of Genomics
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-09-19
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Persistent homology, a topological data analysis (TDA) method, is applied to microarray data sets.
Although there are a few papers referring to TDA methods in microarray analysis, the usage of persistent homology in the comparison of several weighted gene coexpression networks (WGCN) was not employed before to the very best of our knowledge.
We calculate the persistent homology of weighted networks constructed from 38 Arabidopsis microarray data sets to test the relevance and the success of this approach in distinguishing the stress factors.
We quantify multiscale topological features of each network using persistent homology and apply a hierarchical clustering algorithm to the distance matrix whose entries are pairwise bottleneck distance between the networks.
The immunoresponses to different stress factors are distinguishable by our method.
The networks of similar immunoresponses are found to be close with respect to bottleneck distance indicating the similar topological features of WGCNs.
This computationally efficient technique analyzing networks provides a quick test for advanced studies.
American Psychological Association (APA)
Duman, Ali Nabi& Pirim, Harun. 2018. Gene Coexpression Network Comparison via Persistent Homology. International Journal of Genomics،Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1172834
Modern Language Association (MLA)
Duman, Ali Nabi& Pirim, Harun. Gene Coexpression Network Comparison via Persistent Homology. International Journal of Genomics No. 2018 (2018), pp.1-11.
https://search.emarefa.net/detail/BIM-1172834
American Medical Association (AMA)
Duman, Ali Nabi& Pirim, Harun. Gene Coexpression Network Comparison via Persistent Homology. International Journal of Genomics. 2018. Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1172834
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1172834