Title
Improved biclustering on expression data through overlapping control
Date Issued
21 June 2010
Access level
metadata only access
Resource Type
journal article
Author(s)
Pontes B.
Divina F.
Giráldez R.
Universidad Pablo de Olavide
Abstract
Purpose: The purpose of this paper is to present a novel control mechanism for avoiding overlapping among biclusters in expression data. Design/methodology/approach: Biclustering is a technique used in analysis of microarray data. One of the most popular biclustering algorithm was introduced by Cheng and Church. Even if this heuristic is successful at finding interesting biclusters, it presents several drawbacks. The main shortcoming is that it introduces random values in the expression matrix to control the overlapping. The overlapping control method presented in this paper is based on a matrix of weights, that is used to estimate the overlapping of a bicluster with already found ones. In this way, the algorithm is always working on real data, and so the biclusters it discovers contain only original data. Findings: The paper shows that the original algorithm wrongly estimates the quality of the biclusters after some iterations, due to random values that it introduces. The empirical results show that the proposed approach is effective in order to improve the heuristic. It is also important to highlight that many interesting biclusters found by using the approach would have not been obtained using the original algorithm. Originality/value: The original algorithm proposed by Cheng and Church is one of the most successful algorithms for discovering biclusters in microarray data. However, it presents some limitations, being the most relevant substitution phase adopted in order to avoid overlapping among biclusters. The modified version of the algorithm proposed in this paper improves the original one, as proven in the experimentation. © Emerald Group Publishing Limited.
Start page
293
End page
309
Volume
3
Issue
2
Language
English
OCDE Knowledge area
Ciencias de la computación Biotecnología relacionada con la salud
Scopus EID
2-s2.0-78549247898
Source
International Journal of Intelligent Computing and Cybernetics
ISSN of the container
17563798
Sources of information: Directorio de Producción Científica Scopus