The Complexity of Promoter Regions Based on a Vector Topological Entropy

Title:The Complexity of Promoter Regions Based on a Vector Topological Entropy

Volume: 12 Issue: 5

Author(s): Shuilin Jin*, Zhuo Wang, Junyu Lin, Jia Wang, Xiurui Zhang, Renjie Tan, Chuanbin Zhang, Zhe Wang, Wanqian Guo, Yang Hu, Li Xu, Lejun Zhang, Guiyou Liu and Qinghua Jiang

Affiliation:

• Department of Mathematics, Harbin Institute of Technology, Harbin, 150001 Heilongjiang,China

Keywords: DNA sequence, topological entropy, promoter sequence, coding regions, metric entropy Kolmogorov-Sinai entropy.

Abstract: Background: Entropy can be used to detect the complexity of Sequences. various concepts of entropy appeared, such as metric entropy, Kolmogorov-Sinai entropy, Renyi entropy and topological entropy. Topological entropy is a difficult definition used to decipher the structure of DNA sequences, due to finite dimensional problems.

Method: Different from the generalized topological entropy, a vector topological entropy is presented, which is based on the idea of multi-scale analysis of DNA sequences. Subsequently the complexity of promoter regions between Chromosome X and Y is detected by the use of a quantity topological entropy.

Results: It is shown that the quantity topological entropy of promoters is less than the coding regions in all the Chromosomes. The mean of topological entropy of promoters is 3 standard deviations higher than the mean of coding regions in Chromosomes. The results show that the quantity topological entropy of coding regions is significantly higher than that of promoters.

Conclusion: The topological entropy is a useful tool for detecting the structure of DNA sequences, and the result of the comparisons shows the promoter regions as being more regular, which implies that the promoters are more functionally important.

Cite this article as:

Jin Shuilin*, Wang Zhuo, Lin Junyu, Wang Jia, Zhang Xiurui, Tan Renjie, Zhang Chuanbin, Wang Zhe, Guo Wanqian, Hu Yang , Xu Li, Zhang Lejun , Liu Guiyou and Jiang Qinghua , The Complexity of Promoter Regions Based on a Vector Topological Entropy, Current Bioinformatics 2017; 12 (5) . https://dx.doi.org/10.2174/1574893611666160527101340