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A statistical thin-tail test of predicting regulatory regions in the Drosophila genome

หน่วยงาน Nanyang Technological University, Singapore

รายละเอียด

ชื่อเรื่อง : A statistical thin-tail test of predicting regulatory regions in the Drosophila genome
นักวิจัย : Shu, Jian Jun , Li, Yajing
คำค้น : DRNTU::Science::Biological sciences.
หน่วยงาน : Nanyang Technological University, Singapore
ผู้ร่วมงาน : -
ปีพิมพ์ : 2556
อ้างอิง : Shu, J. J., & Li, Y. (2013). A statistical thin-tail test of predicting regulatory regions in the Drosophila genome. Theoretical Biology and Medical Modelling, 10(1):11. , 1742-4682 , http://hdl.handle.net/10220/10184 , http://dx.doi.org/10.1186/1742-4682-10-11 , 169161
ที่มา : -
ความเชี่ยวชาญ : -
ความสัมพันธ์ : Theoretical biology and medical modelling
ขอบเขตของเนื้อหา : -
บทคัดย่อ/คำอธิบาย :

The identification of transcription factor binding sites (TFBSs) and cis-regulatory modules (CRMs) is a crucial step in studying gene expression, but the computational method attempting to distinguish CRMs from NCNRs still remains a challenging problem due to the limited knowledge of specific interactions involved. Methods The statistical properties of cis-regulatory modules (CRMs) are explored by estimating the similar-word set distribution with overrepresentation (Z-score). It is observed that CRMs tend to have a thin-tail Z-score distribution. A new statistical thin-tail test with two thinness coefficients is proposed to distinguish CRMs from non-coding non-regulatory regions (NCNRs). Results As compared with the existing fluffy-tail test, the first thinness coefficient is designed to reduce computational time, making the novel thin-tail test very suitable for long sequences and large database analysis in the post-genome time and the second one to improve the separation accuracy between CRMs and NCNRs. These two thinness coefficients may serve as valuable filtering indexes to predict CRMs experimentally. Conclusions The novel thin-tail test provides an efficient and effective means for distinguishing CRMs from NCNRs based on the specific statistical properties of CRMs and can guide future experiments aimed at finding new CRMs in the post-genome time.

บรรณานุกรม :
Shu, Jian Jun , Li, Yajing . (2556). A statistical thin-tail test of predicting regulatory regions in the Drosophila genome.
    กรุงเทพมหานคร : Nanyang Technological University, Singapore.
Shu, Jian Jun , Li, Yajing . 2556. "A statistical thin-tail test of predicting regulatory regions in the Drosophila genome".
    กรุงเทพมหานคร : Nanyang Technological University, Singapore.
Shu, Jian Jun , Li, Yajing . "A statistical thin-tail test of predicting regulatory regions in the Drosophila genome."
    กรุงเทพมหานคร : Nanyang Technological University, Singapore, 2556. Print.
Shu, Jian Jun , Li, Yajing . A statistical thin-tail test of predicting regulatory regions in the Drosophila genome. กรุงเทพมหานคร : Nanyang Technological University, Singapore; 2556.