Being capable of providing scientists with global and functional profiles of gene expression of thousands of genes simultaneously, microarray has demonstrated its value in many important applications in bioscience, such as discovering novel genes, deciphering pathways involved in tumour genesis, and identifying potential diagnostic markers or therapeutic targets. However, mining microarray data, given the presence of large quantities of high dimensional data which may come in a variety of noisy forms, and the lack of a comprehensive understanding at the molecular level, presents significant challenges to data mining communities.
This special issue aims to bring together researchers from computer science, mathematics, statistics, clinical research and system biology to present cutting edge techniques and applications in the field of microarray data analysis.
Topics relevant to this special issue include, but are not limited to, the following:
- Disease classification and outcome prediction
- Gene clustering analysis
- Biomarker and target identification
- Intelligent data integration in microarray data analysis
- Advanced data mining and machine learning algorithms for knowledge discovery from data
- Dynamic analysis of protein interaction networks
- Protein structure prediction
- Gene regulatory network/pathway prediction/discovery
- Microarray data visualisation
- SNP/phenotype data analysis
Full paper submission: 15 January 2010
Response to authors: 15 March 2010
Final manuscript submission: 15 April 2010
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