Economics at your fingertips  

A New Method to Build Gene Regulation Network Based on Fuzzy Hierarchical Clustering Methods

Masoume Maghsoodi

MPRA Paper from University Library of Munich, Germany

Abstract: The construction of genetic regulatory networks is understanding the relationship among genes or circuits which regulate the conditions of cells in response to internal or external stimuli. In fact, the objective is to understand the network of relationship among genes which determine which genes are responsible for activating other genes. The understanding of relationships may help to identify the genes which are involved in a disease and design the drugs. The most important limitations in gene regulatory network inference are low number of samples, noise penetration possibility, and large number of genes. There are different models to build gene regulatory network. This study used fuzzy hierarchical clustering method to infer gene regulatory network. Using clustering, the similar genes will be in a cluster. Many edges therefore will be removed. The final assessments showed that the genes clustering increased the efficiency of gene regulation network inference methods.

Keywords: Principal Component Analysis; Head Cluster; Clustering; Gene Regulation Network. (search for similar items in EconPapers)
JEL-codes: C0 C6 (search for similar items in EconPapers)
Date: 2016-06-01
New Economics Papers: this item is included in nep-neu and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Published in International Academic Journal of Science and Engineering 6.3(2016): pp. 169-176

Downloads: (external link) original version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().

Page updated 2023-11-11
Handle: RePEc:pra:mprapa:79743