Cross-Correlation and Evolutionary Biclustering: Extracting Gene Interaction Sub-networks

Authors:
Ranajit Das;Sushmita Mitra;Subhasis Mukhopadhyay
Affiliations:
Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India 700 108;Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India 700 108;Department of Bio-Physics, Molecular Biology and Bioinformatics, Calcutta University, Kolkata, India 700 009
Venue:
PReMI '09 Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence
Year:
2009

Citing 5
Cited 1

Biclustering of Expression Data

Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology
Clustering of gene expression data using a local shape-based similarity measure

Bioinformatics
Multi-objective evolutionary biclustering of gene expression data

Pattern Recognition
Gene interaction - An evolutionary biclustering approach

Information Fusion
Genetic Networks and Soft Computing

IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)

Aggregation of correlation measures for the reverse engineering of gene regulatory sub-networks

PerMIn'12 Proceedings of the First Indo-Japan conference on Perception and Machine Intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper we present a simple and novel time-dependent cross-correlation-based approach for the extraction of simple gene interaction sub-networks from biclusters in temporal gene expression microarray data. Preprocessing has been employed to retain those gene interaction pairs that are strongly correlated. The methodology was applied to public-domain data sets of Yeast and the experimental results were biologically validated based on standard databases and information available in the literature.