DocumentCode
3318716
Title
Notice of Retraction
Spermatogenesis-Related Gene Selection by Singular Value Decomposition and Correlation Analysis
Author
Tianxue Gong ; Weixiang Liu ; Lan Tao ; Liandong Liu ; Aifa Tang
Author_Institution
Coll. of Comput. & Software Eng., Shenzhen Univ., Shenzhen, China
fYear
2011
fDate
10-12 May 2011
Firstpage
1
Lastpage
4
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
The aim of this study is to select significant genes associated with spermatogenesis. We use singular value decomposition to extract the principal component of the DNA microarray dataset and the expression profile of the first eigengene shows the expression tendency of most genes´ expression. Basing on this observation, we rank genes using correlation of each gene expression and the first eigengene´s profile. Five kinds of correlation methods are considered and experimental results on a real spermatogenesis microarray dataset demonstrate that the cosine correlation method can find 75 informative genes among top 100 probes/genes. The selected significant genes, especially the top 10 probes/genes, are related to spermatogenesis through literature analysis.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
The aim of this study is to select significant genes associated with spermatogenesis. We use singular value decomposition to extract the principal component of the DNA microarray dataset and the expression profile of the first eigengene shows the expression tendency of most genes´ expression. Basing on this observation, we rank genes using correlation of each gene expression and the first eigengene´s profile. Five kinds of correlation methods are considered and experimental results on a real spermatogenesis microarray dataset demonstrate that the cosine correlation method can find 75 informative genes among top 100 probes/genes. The selected significant genes, especially the top 10 probes/genes, are related to spermatogenesis through literature analysis.
Keywords
DNA; bioinformatics; correlation methods; genetics; molecular biophysics; singular value decomposition; DNA microarray dataset; correlation analysis; cosine correlation method; eigengene expression profile; singular value decomposition; spermatogenesis-related gene selection; Arrays; Bioinformatics; Correlation; Mice; Probes; Proteins;
fLanguage
English
Publisher
ieee
Conference_Titel
Bioinformatics and Biomedical Engineering, (iCBBE) 2011 5th International Conference on
Conference_Location
Wuhan
ISSN
2151-7614
Print_ISBN
978-1-4244-5088-6
Type
conf
DOI
10.1109/icbbe.2011.5780088
Filename
5780088
Link To Document