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Title

 

 

 

 

 

Extract-SAGE: An integrated platform for cross-analysis and GA-based selection of SAGE data

 

Authors

 

Cheng-Hong Yang1, Tsung-Mu Shih1, Yu-Chen Hung2, Hsueh-Wei Chang2,3,4,*, Li-Yeh Chuang5

Affiliation

 

 

1Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, Taiwan; 2Graduate Institute of Natural Products, College of Pharmacy, Kaohsiung Medical University, Taiwan; 3Center of Excellence for Environmental Medicine, Kaohsiung Medical University, Taiwan; 4Faculty of Biomedical Science and Environmental Biology, Kaohsiung Medical University, Taiwan; 5Department of Chemical Engineering, I-Shou University, Taiwan

 

Email

 

changhw@kmu.edu.tw; * Corresponding authors

 

Article Type

 

Software

 

Date

 

received January 19, 2009; accepted February 06, 2009; published February 27, 2009

 

Abstract

Serial analysis of gene expression (SAGE) is a powerful quantification technique for gene expression data. The huge amount of tag data in SAGE libraries of samples is difficult to analyze with current SAGE analysis tools. Data is often not provided in a biologically significant way for cross-analysis and -comparison, thus limiting its application. Hence, an integrated software platform that can perform such a complex task is required. Here, we implement set theory for cross-analyzing gene expression data among different SAGE libraries of tissue sources; up- or down-regulated tissue-specific tags can be identified computationally. Extract-SAGE employs a genetic algorithm (GA) to reduce the number of genes among the SAGE libraries. Its representative tag mining will facilitate the discovery of the candidate genes with discriminating gene expression.

 

Keywords

SAGE; genetic algorithm; set theory; software

Availability

This software and user manual are freely available at ftp://sage@bio.kuas.edu.tw/Extract-SAGE.zip

 

Citation

Yang et al., Bioinformation 3(7): 291-292 (2009)

 

Edited by

P. Kangueane

 

ISSN

0973-2063

 

Publisher

Biomedical Informatics

 

License

 

 

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.