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KMID : 0624620110440040250
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BMB Reports
2011 Volume.44 No. 4 p.250 ~ p.255
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Predicting tissue-specific expressions based on sequence characteristics
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Paik Hyo-Jung
Ryu Tae-Woo
Heo Hyoung-Sam
Seo Seung-Won
Lee Do-Heon
Hur Cheol-Goo
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Abstract
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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.
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KEYWORD
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Domain, Housekeeping, Random forest, Tissue-specific, Transcription factor binding site
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