Please use this identifier to cite or link to this item:
|Title:||Nonrandom clusters of palindromes in herpesvirus genomes|
Poisson process approximation
|Citation:||Leung, M.-Y., Kwok, P.C., Xia, A., Chen, L.H.Y. (2005). Nonrandom clusters of palindromes in herpesvirus genomes. Journal of Computational Biology 12 (3) : 331-354. ScholarBank@NUS Repository. https://doi.org/10.1089/cmb.2005.12.331|
|Abstract:||Palindromes are symmetrical words of DNA in the sense that they read exactly the same as their reverse complementary sequences. Representing the occurrences of palindromes in a DNA molecule as points on the unit interval, the scan statistics can be used to identify regions of unusually high concentration of palindromes. These regions have been associated with the replication origins on a few herpesviruses in previous studies. However, the use of scan statistics requires the assumption that the points representing the palindromes are independently and uniformly distributed on the unit interval. In this paper, we provide a mathematical basis for this assumption by showing that in randomly generated DNA sequences, the occurrences of palindromes can be approximated by a Poisson process. An easily computable upper bound on the Wasserstein distance between the palindrome process and the Poisson process is obtained. This bound is then used as a guide to choose an optimal palindrome length in the analysis of a collection of 16 herpesvirus genomes. Regions harboring significant palindrome clusters are identified and compared to known locations of replication origins. This analysis brings out a few interesting extensions of the scan statistics that can help formulate an algorithm for more accurate prediction of replication origins. © Mary Ann Liebert, Inc.|
|Source Title:||Journal of Computational Biology|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Oct 18, 2018
WEB OF SCIENCETM
checked on Oct 2, 2018
checked on Sep 7, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.