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
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;
Conference_Titel :
Bioinformatics and Bioengineering (BIBE), 2011 IEEE 11th International Conference on
Conference_Location :
Taichung
Print_ISBN :
978-1-61284-975-1
DOI :
10.1109/BIBE.2011.54
