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Title 

Predicting tissue-specific expressions based on sequence characteristics

Authors 

Hyo Jung PaikT RyuHyoung-Sam HeoSeung Won SeoD LeeCheol-Goo Hur

Publisher 

Korean Society for Biochemistry and Molecular Biology

Issue Date 

2011

Citation 

BMB Reports, vol. 44, no. 4, pp. 250-255

Keywords 

DomainHousekeepingRandom forestTissue-specificTranscription factor binding site

Abstract 

In multicellular organisms, including humans, understanding expression specificity at the tissue level is essential for interpreting protein function, such as tissue differentiation. We developed a prediction approach via generated sequence features from overrepresented patterns in housekeeping (HK) and tissue-specific (TS) genes to classify TS expression in humans. Using TS domains and transcriptional factor binding sites (TFBSs), sequence characteristics were used as indices of expressed tissues in a Random Forest algorithm by scoring exclusive patterns considering the biological intuition; TFBSs regulate gene expression, and the domains reflect the functional specificity of a TS gene. Our proposed approach displayed better performance than previous attempts and was validated using computational and experimental methods.

ISSN 

1976-6696

Link 

http://dx.doi.org/10.5483/BMBRep.2011.44.4.250

Appears in Collections

1. Journal Articles > Journal Articles

Registered Date

2019-05-02


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