|
Title:
|
MIB: USING MUTUAL INFORMATION FOR BICLUSTERING HIGH DIMENSIONAL DATA |
|
Author(s):
|
Neelima Gupta , Seema Aggarwal |
|
ISBN:
|
978-972-8924-63-8 |
|
Editors:
|
Hans Weghorn and Ajith P. Abraham |
|
Year:
|
2008 |
|
Edition:
|
Single |
|
Keywords:
|
Biclustering and Mutual Information. |
|
Type:
|
Short Paper |
|
First Page:
|
119 |
|
Last Page:
|
123 |
|
Language:
|
English |
|
Cover:
|
|
|
Full Contents:
|
click to dowload 
|
|
Paper Abstract:
|
Most of the biclustering algorithms for gene expression data are based either on the Euclidean distance or correlation
coefficient which capture only linear relationships. However, in gene expression data, non linear relationships may exist
between the genes. Mutual Information between two variables provides a more general criterion to investigate
dependencies amongst variables. In this paper, we propose an algorithm that uses mutual information for biclustering
gene expression data. We present the experimental results on synthetic data. None of the distance based biclustering
algorithms will identify the biclusters in our synthetic data which our algorithm is able to report. In future we intend to
use our algorithm on gene expression data. |
|
|
|
|
|
|
