Estimating missing value in microarray data using fuzzy clustering and gene ontology

Mohammadi, A; Saraee, MH

Abstract

Microarray experiments usually generate data sets with multiple missing expression values, due to several problems. In this paper, a new and robust method based on fuzzy clustering and gene ontology is proposed to estimate missing values in microarray data. In the proposed method, missing values are imputed with values generated from cluster centers. To determine the similar genes in clustering process, we have utilized the biological knowledge obtained from gene ontology as well as gene expression values. We have applied the proposed method on yeast cell cycle data with different percentage of missing entries. We compared the estimation accuracy of our method with some other methods. The experimental results indicate that the proposed method outperforms other methods in terms of accuracy.

Citation

Mohammadi, A., & Saraee, M. (2008, November). Estimating missing value in microarray data using fuzzy clustering and gene ontology. Presented at IEEE International Conference on Bioinformatics and Biomedicine, 2008. BIBM '08., Philadelphia, PA, USA,

• Presentation Conference Type: Other
• Conference Name: IEEE International Conference on Bioinformatics and Biomedicine, 2008. BIBM '08.
• Conference Location: Philadelphia, PA, USA,
• Start Date: Nov 7, 2008
• End Date: Nov 9, 2008
• Publication Date: Nov 21, 2008
• Deposit Date: Nov 3, 2011
• Book Title: 2008 IEEE International Conference on Bioinformatics and Biomedicine
• DOI: https://doi.org/10.1109/BIBM.2008.71
• Publisher URL: http://dx.doi.org/10.1109/BIBM.2008.71
• Additional Information: Event Type : Conference