Sin, Yi Lim and Mohd Saberi, Mohamad and Lian, En Chai and Safaai, Deris and Weng, Howe Chan and Sigeru, Omatu and Muhammad Farhan, Sjaugi and Muhammad Mahfuz, Zainuddin and Gopinathaan, Rajamohan and Zuwairie, Ibrahim and Zulkifli, Md. Yusof (2016) Investigation of the Effects of Imputation Methods for Gene Regulatory Networks Modelling Using Dynamic Bayesian Networks. In: Distributed Computing and Artificial Intelligence, 13th International Conference. Springer International Publishing, pp. 413-421. ISBN 978-3-319-40161-4
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Abstract
DNA microarray technology plays an important role in advancing the analysis of gene expression and gene functions. However, gene expression data often contain missing values, which cause problems as most of the analysis methods of gene expression data require a complete matrix. Several missing value imputation methods have been developed to overcome the problems. In this paper, effects of the missing value imputation methods in modeling of gene regulatory network are investigated. Three missing value imputation methods are used, which are k-Nearest Neighbor (kNN), Iterated Local Least Squares (ILLsimpute), and Fixed Rank Approximation Algorithm (FRAA). Dataset used in this paper is E. coli. The results suggest that the performance of each missing value imputation method is influenced by the percentage and distribution of the missing values in the dataset, which subsequently affect the modeling of gene regulatory network using Dynamic Bayesian network.
| Item Type: | Book Chapter |
|---|---|
| Uncontrolled Keywords: | Bioinformatics; Artificial intelligence; Gene regulatory network; Missing values; Gene expression; Dynamic Bayesian Network; Gene expression data; Imputation methods |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering T Technology > TS Manufactures |
| Faculty/Division: | Faculty of Electrical & Electronic Engineering Faculty of Manufacturing Engineering |
| Depositing User: | Mrs. Neng Sury Sulaiman |
| Date Deposited: | 10 Aug 2016 01:41 |
| Last Modified: | 08 Feb 2018 02:54 |
| URI: | http://umpir.ump.edu.my/id/eprint/13918 |
| Download Statistic: | View Download Statistics |
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