A Comparative Analysis of Two Algorithms for Biclustering Gene Expression Data

Modelling and Analysis of Safety and Risk in Complex Systems: Proceedings of the Eleventh International Scientific School MASR-2011 2011
Oļegs Užga-Rebrovs, Gaļina Kuļešova

Over the past years DNA microarray technology and techniques for processing the information obtained have been developing very fast. These methods are aimed at acquiring new knowledge from the initial data. Two major approaches to processing initial data can be distinguished: classification and clustering. Clustering allows grouping genes with similar properties and similar behavior aimed to understand the essence of diverse intracellular processes. Biclustering techniques developed in the last years enable solving this kind of tasks more effectively. This paper provides a comparative analysis of two algorithms for gene expression data biclustering and outlines a possible way to increase their performance.

Atslēgas vārdi
Gene expression data, clustering, biclustering, the residue of an entry, mean residue, mean squared residue score.

Užga-Rebrovs, O., Kuļešova, G. A Comparative Analysis of Two Algorithms for Biclustering Gene Expression Data. No: Modelling and Analysis of Safety and Risk in Complex Systems: Proceedings of the Eleventh International Scientific School MASR-2011, Krievija, Saint Petersburg, 28. Jūn-2. Jūl., 2011. Saint Petersburg: SUAI, 2011, 265.-270.lpp. ISBN 978-5-8088-0627-6.

Publikācijas valoda
English (en)