Predicting tissue-specific expressions based on sequence characteristics

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Title
Predicting tissue-specific expressions based on sequence characteristics
Author(s)
Hyo Jung Paik; T Ryu; Hyoung-Sam Heo; Seung Won Seo; D Lee; Cheol-Goo Hur
Bibliographic Citation
BMB Reports, vol. 44, no. 4, pp. 250-255
Publication Year
2011
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.
Keyword
DomainHousekeepingRandom forestTissue-specificTranscription factor binding site
ISSN
1225-8687
Publisher
South Korea
DOI
http://dx.doi.org/10.5483/BMBRep.2011.44.4.250
Type
Article
Appears in Collections:
1. Journal Articles > Journal Articles
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