An incremental clustering of gene expression data

Author

Das, Rosy ; Bhattacharyya, Dhruba K. ; Kalita, Jugal K.

Author_Institution

Dept. of Comput. Sci. & Eng., Tezpur Univ., Tezpur, India

fYear

2009

fDate

9-11 Dec. 2009

Firstpage

742

Lastpage

747

Abstract

This paper presents an incremental clustering algorithm based on DGC, a density-based algorithm we developed earlier. We experimented with real-life datasets and both methods perform satisfactorily. The methods have been compared with some well-known clustering algorithms and they perform well in terms of z-score cluster validity measure.

Keywords

biology computing; data handling; data mining; pattern clustering; density-based algorithm; gene expression data; incremental clustering algorithm; real-life datasets; z-score cluster validity measure; Clustering algorithms; Clustering methods; Computer science; Data analysis; Data engineering; Data mining; Density measurement; Gene expression; Performance evaluation; Springs; Gene expression; clustering; density based; dissimilarity measure; incremental clustering;

fLanguage

English

Publisher

ieee

Conference_Titel

Nature & Biologically Inspired Computing, 2009. NaBIC 2009. World Congress on

Conference_Location

Coimbatore

Print_ISBN

978-1-4244-5053-4

Type

conf

DOI

10.1109/NABIC.2009.5393848

Filename

5393848

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3220067