Missing Value Estimation for Microarray Data by Bayesian Principal Component Analysis and Iterative Local Least Squares
Joint Authors
Shi, Fuxi
Zhang, Dan
Chen, Jun
Karimi, Hamid Reza
Source
Mathematical Problems in Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-5, 5 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-03-31
Country of Publication
Egypt
No. of Pages
5
Main Subjects
Abstract EN
Missing values are prevalent in microarray data, they course negative influence on downstream microarray analyses, and thus they should be estimated from known values.
We propose a BPCA-iLLS method, which is an integration of two commonly used missing value estimation methods—Bayesian principal component analysis (BPCA) and local least squares (LLS).
The inferior row-average procedure in LLS is replaced with BPCA, and the least squares method is put into an iterative framework.
Comparative result shows that the proposed method has obtained the highest estimation accuracy across all missing rates on different types of testing datasets.
American Psychological Association (APA)
Shi, Fuxi& Zhang, Dan& Chen, Jun& Karimi, Hamid Reza. 2013. Missing Value Estimation for Microarray Data by Bayesian Principal Component Analysis and Iterative Local Least Squares. Mathematical Problems in Engineering،Vol. 2013, no. 2013, pp.1-5.
https://search.emarefa.net/detail/BIM-1008574
Modern Language Association (MLA)
Shi, Fuxi…[et al.]. Missing Value Estimation for Microarray Data by Bayesian Principal Component Analysis and Iterative Local Least Squares. Mathematical Problems in Engineering No. 2013 (2013), pp.1-5.
https://search.emarefa.net/detail/BIM-1008574
American Medical Association (AMA)
Shi, Fuxi& Zhang, Dan& Chen, Jun& Karimi, Hamid Reza. Missing Value Estimation for Microarray Data by Bayesian Principal Component Analysis and Iterative Local Least Squares. Mathematical Problems in Engineering. 2013. Vol. 2013, no. 2013, pp.1-5.
https://search.emarefa.net/detail/BIM-1008574
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1008574