DocumentCode
2460851
Title
GERC: Tree Based Clustering for Gene Expression Data
Author
Ahmed, H.A. ; Mahanta, P. ; Bhattacharyya, D.K. ; Kalita, Jugal K.
Author_Institution
Deptt. of Comp. Sc. & Eng., Tezpur Univ., Napalm, India
fYear
2011
fDate
24-26 Oct. 2011
Firstpage
299
Lastpage
302
Abstract
Measurement of gene expression using DNA micro arrays have revolutionized biological and medical research. This paper presents a divisive clustering algorithm that produces a tree of genes called GERC tree along with the generated clusters. Unlike a dendrogram, a GERC tree is a general tree and it is an ample resource for biological information about the genes in a data set. The leaves of the tree represent the desired clusters. The clustering method was tested with several real-life data sets and the proposed method has been found satisfactory.
Keywords
DNA; bioinformatics; biological techniques; cellular biophysics; decision trees; genetics; lab-on-a-chip; DNA microarray; GERC tree; biological information; divisive clustering algorithm; gene expression data; tree based clustering; Additives; Bioinformatics; Clustering algorithms; Correlation; Gene expression; Heuristic algorithms; Gene Expression Data; Hierarchical Clustering; Mean Squared Residue; Recursive Clustering;
fLanguage
English
Publisher
ieee
Conference_Titel
Bioinformatics and Bioengineering (BIBE), 2011 IEEE 11th International Conference on
Conference_Location
Taichung
Print_ISBN
978-1-61284-975-1
Type
conf
DOI
10.1109/BIBE.2011.54
Filename
6089845
Link To Document