A Review of Feature Extraction Software for Microarray Gene Expression Data
Joint Authors
Mohamad, Mohd Saberi
Tan, Ching Siang
Ting, Wai Soon
Chan, Weng Howe
Deris, Safaai
Ali Shah, Zuraini
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-08-31
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
When gene expression data are too large to be processed, they are transformed into a reduced representation set of genes.
Transforming large-scale gene expression data into a set of genes is called feature extraction.
If the genes extracted are carefully chosen, this gene set can extract the relevant information from the large-scale gene expression data, allowing further analysis by using this reduced representation instead of the full size data.
In this paper, we review numerous software applications that can be used for feature extraction.
The software reviewed is mainly for Principal Component Analysis (PCA), Independent Component Analysis (ICA), Partial Least Squares (PLS), and Local Linear Embedding (LLE).
A summary and sources of the software are provided in the last section for each feature extraction method.
American Psychological Association (APA)
Tan, Ching Siang& Ting, Wai Soon& Mohamad, Mohd Saberi& Chan, Weng Howe& Deris, Safaai& Ali Shah, Zuraini. 2014. A Review of Feature Extraction Software for Microarray Gene Expression Data. BioMed Research International،Vol. 2014, no. 2014, pp.1-15.
https://search.emarefa.net/detail/BIM-1034402
Modern Language Association (MLA)
Tan, Ching Siang…[et al.]. A Review of Feature Extraction Software for Microarray Gene Expression Data. BioMed Research International No. 2014 (2014), pp.1-15.
https://search.emarefa.net/detail/BIM-1034402
American Medical Association (AMA)
Tan, Ching Siang& Ting, Wai Soon& Mohamad, Mohd Saberi& Chan, Weng Howe& Deris, Safaai& Ali Shah, Zuraini. A Review of Feature Extraction Software for Microarray Gene Expression Data. BioMed Research International. 2014. Vol. 2014, no. 2014, pp.1-15.
https://search.emarefa.net/detail/BIM-1034402
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1034402