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An Improved Fuzzy Based Missing Value Estimation in DNA Microarray Validated by Gene Ranking
Joint Authors
Saha, Sujay
Ghosh, Anupam
Seal, Dibyendu Bikash
Dey, Kashi Nath
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-19, 19 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-07-18
Country of Publication
Egypt
No. of Pages
19
Main Subjects
Abstract EN
Most of the gene expression data analysis algorithms require the entire gene expression matrix without any missing values.
Hence, it is necessary to devise methods which would impute missing data values accurately.
There exist a number of imputation algorithms to estimate those missing values.
This work starts with a microarray dataset containing multiple missing values.
We first apply the modified version of the fuzzy theory based existing method LRFDVImpute to impute multiple missing values of time series gene expression data and then validate the result of imputation by genetic algorithm (GA) based gene ranking methodology along with some regular statistical validation techniques, like RMSE method.
Gene ranking, as far as our knowledge, has not been used yet to validate the result of missing value estimation.
Firstly, the proposed method has been tested on the very popular Spellman dataset and results show that error margins have been drastically reduced compared to some previous works, which indirectly validates the statistical significance of the proposed method.
Then it has been applied on four other 2-class benchmark datasets, like Colorectal Cancer tumours dataset (GDS4382), Breast Cancer dataset (GSE349-350), Prostate Cancer dataset, and DLBCL-FL (Leukaemia) for both missing value estimation and ranking the genes, and the results show that the proposed method can reach 100% classification accuracy with very few dominant genes, which indirectly validates the biological significance of the proposed method.
American Psychological Association (APA)
Saha, Sujay& Ghosh, Anupam& Seal, Dibyendu Bikash& Dey, Kashi Nath. 2016. An Improved Fuzzy Based Missing Value Estimation in DNA Microarray Validated by Gene Ranking. Advances in Fuzzy Systems،Vol. 2016, no. 2016, pp.1-19.
https://search.emarefa.net/detail/BIM-1095050
Modern Language Association (MLA)
Saha, Sujay…[et al.]. An Improved Fuzzy Based Missing Value Estimation in DNA Microarray Validated by Gene Ranking. Advances in Fuzzy Systems No. 2016 (2016), pp.1-19.
https://search.emarefa.net/detail/BIM-1095050
American Medical Association (AMA)
Saha, Sujay& Ghosh, Anupam& Seal, Dibyendu Bikash& Dey, Kashi Nath. An Improved Fuzzy Based Missing Value Estimation in DNA Microarray Validated by Gene Ranking. Advances in Fuzzy Systems. 2016. Vol. 2016, no. 2016, pp.1-19.
https://search.emarefa.net/detail/BIM-1095050
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1095050