Candidate Gene Identification Approach: Progress and Challenges

<p>Although it has been widely applied in identification of genes responsible for biomedically, economically, or even evolutionarily important complex and quantitative traits, traditional candidate gene approach is largely limited by its reliance on the priori knowledge about the physiological...

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Main Author: Mengjin Zhu, Shuhong Zhao
Format: Article
Language:English
Published: Ivyspring International Publisher 2007-01-01
Series:International Journal of Biological Sciences
Online Access:http://www.biolsci.org/v03p0420.htm
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spelling doaj-7cecfc59a16141859fc0e57962aafc112020-11-25T02:31:28ZengIvyspring International PublisherInternational Journal of Biological Sciences1449-22882007-01-0137420427Candidate Gene Identification Approach: Progress and ChallengesMengjin Zhu, Shuhong Zhao<p>Although it has been widely applied in identification of genes responsible for biomedically, economically, or even evolutionarily important complex and quantitative traits, traditional candidate gene approach is largely limited by its reliance on the priori knowledge about the physiological, biochemical or functional aspects of possible candidates. Such limitation results in a fatal information bottleneck, which has apparently become an obstacle for further applications of traditional candidate gene approach on many occasions. While the identification of candidate genes involved in genetic traits of specific interest remains a challenge, significant progress in this subject has been achieved in the last few years. Several strategies have been developed, or being developed, to break the barrier of information bottleneck. Recently, being a new developing method of candidate gene approach, digital candidate gene approach (DigiCGA) has emerged and been primarily applied to identify potential candidate genes in some studies. This review summarizes the progress, application software, online tools, and challenges related to this approach.</p>http://www.biolsci.org/v03p0420.htm
collection DOAJ
language English
format Article
sources DOAJ
author Mengjin Zhu, Shuhong Zhao
spellingShingle Mengjin Zhu, Shuhong Zhao
Candidate Gene Identification Approach: Progress and Challenges
International Journal of Biological Sciences
author_facet Mengjin Zhu, Shuhong Zhao
author_sort Mengjin Zhu, Shuhong Zhao
title Candidate Gene Identification Approach: Progress and Challenges
title_short Candidate Gene Identification Approach: Progress and Challenges
title_full Candidate Gene Identification Approach: Progress and Challenges
title_fullStr Candidate Gene Identification Approach: Progress and Challenges
title_full_unstemmed Candidate Gene Identification Approach: Progress and Challenges
title_sort candidate gene identification approach: progress and challenges
publisher Ivyspring International Publisher
series International Journal of Biological Sciences
issn 1449-2288
publishDate 2007-01-01
description <p>Although it has been widely applied in identification of genes responsible for biomedically, economically, or even evolutionarily important complex and quantitative traits, traditional candidate gene approach is largely limited by its reliance on the priori knowledge about the physiological, biochemical or functional aspects of possible candidates. Such limitation results in a fatal information bottleneck, which has apparently become an obstacle for further applications of traditional candidate gene approach on many occasions. While the identification of candidate genes involved in genetic traits of specific interest remains a challenge, significant progress in this subject has been achieved in the last few years. Several strategies have been developed, or being developed, to break the barrier of information bottleneck. Recently, being a new developing method of candidate gene approach, digital candidate gene approach (DigiCGA) has emerged and been primarily applied to identify potential candidate genes in some studies. This review summarizes the progress, application software, online tools, and challenges related to this approach.</p>
url http://www.biolsci.org/v03p0420.htm
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