FLBC: A Fuzzy Link based Clustering approach for gene expression data

Author

Bora, Giri Mallika ; Sarmah, Rosy

Author_Institution

Dept. of CS & Eng., Tezpur Univ., Tezpur, India

fYear

2011

fDate

11-14 Dec. 2011

Firstpage

892

Lastpage

897

Abstract

In this paper, we propose an algorithm for efficient clustering of gene expression data. The algorithm uses the concept of common neighbors and uses a fuzzy approach for detecting intersecting and overlapping clusters. We have also compared the algorithm to the existing popular approaches and found our algorithm to give good results in terms of z-score measure of cluster validity and p-value measure.

Keywords

biology computing; fuzzy set theory; genetics; pattern clustering; FLBC; cluster validity; fuzzy link based clustering approach; gene expression data; intersecting clusters; overlapping clusters; p-value measure; z-score measure; Clustering algorithms; Clustering methods; Correlation; Gene expression; Noise; Proteins; Gene expression data; Pearson correlation coefficient; common nearest neighbor; nearest neighbor;

fLanguage

English

Publisher

ieee

Conference_Titel

Information and Communication Technologies (WICT), 2011 World Congress on

Conference_Location

Mumbai

Print_ISBN

978-1-4673-0127-5

Type

conf

DOI

10.1109/WICT.2011.6141366

Filename

6141366

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3182862