![](/images/graphics-bg.png)
Bayesian Functional Data Clustering for Temporal Microarray Data
Joint Authors
Feng, Yang
Zhong, Wenxuan
Ma, Ping
Liu, Jun S.
Source
International Journal of Plant Genomics
Issue
Vol. 2008, Issue 2008 (31 Dec. 2008), pp.1-4, 4 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2008-04-17
Country of Publication
Egypt
No. of Pages
4
Main Subjects
Abstract EN
We propose a Bayesian procedure to cluster temporal gene expression microarray profiles, based on a mixed-effect smoothing-spline model, and design a Gibbs sampler to sample from the desired posterior distribution.
Our method can determine the cluster number automatically based on the Bayesian information criterion, and handle missing data easily.
When applied to a microarray dataset on the budding yeast, our clustering algorithm provides biologically meaningful gene clusters according to a functional enrichment analysis.
American Psychological Association (APA)
Ma, Ping& Zhong, Wenxuan& Feng, Yang& Liu, Jun S.. 2008. Bayesian Functional Data Clustering for Temporal Microarray Data. International Journal of Plant Genomics،Vol. 2008, no. 2008, pp.1-4.
https://search.emarefa.net/detail/BIM-455846
Modern Language Association (MLA)
Ma, Ping…[et al.]. Bayesian Functional Data Clustering for Temporal Microarray Data. International Journal of Plant Genomics No. 2008 (2008), pp.1-4.
https://search.emarefa.net/detail/BIM-455846
American Medical Association (AMA)
Ma, Ping& Zhong, Wenxuan& Feng, Yang& Liu, Jun S.. Bayesian Functional Data Clustering for Temporal Microarray Data. International Journal of Plant Genomics. 2008. Vol. 2008, no. 2008, pp.1-4.
https://search.emarefa.net/detail/BIM-455846
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-455846