Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
505247 | Computers in Biology and Medicine | 2012 | 7 Pages |
Abstract
A statistical study of cis-regulatory modules (CRMs) is presented based on the estimation of similar-word set distribution. It is observed that CRMs tend to have a fat-tail distribution. A new statistical fat-tail test with two kurtosis-based fatness coefficients is proposed to distinguish CRMs from non-CRMs. As compared with the existing fluffy-tail test, the first fatness coefficient is designed to reduce computational time, making the novel fat-tail test very suitable for long sequences and large database analysis in the post-genome time and the second one to improve separation accuracy between CRMs and non-CRMs. These two fatness coefficients may serve as valuable filtering indexes to predict CRMs experimentally.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Jian-Jun Shu, Yajing Li,