Analyzing Time-Course Microarray Data Using Functional Data Analysis - A Review
Gene expression over time can be viewed as a continuous process and therefore represented as a continuous curve or function. Functional data analysis (FDA) is a statistical methodology used to analyze functional data that has become increasingly popular in the analysis of time-course gene expression data. Several FDA techniques have been applied to gene expression profiles including functional regression analysis (to describe the relationship between expression profiles and other covariate(s)), functional discriminant analysis (to discriminate and classify groups of genes) and functional principal components analysis (for dimension reduction and clustering). This paper reviews the use of FDA and its associated methods to analyze time-course microarray gene expression data.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 10 (2011)
Issue (Month): 1 (May)
|Contact details of provider:|| Web page: http://www.degruyter.com |
|Order Information:||Web: http://www.degruyter.com/view/j/sagmb|
When requesting a correction, please mention this item's handle: RePEc:bpj:sagmbi:v:10:y:2011:i:1:n:23. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Peter Golla)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.