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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

A Monte Carlo Approach to the Fluctuation Problem in Optimal Alignments of Random Strings

Author(s):
Amsalu, S. [1] ; Hauser, R. [2] ; Matzinger, H. [3]
Total Authors: 3
Affiliation:
[1] Georgia Inst Technol, Atlanta, GA 30332 - USA
[2] Univ Oxford, Math Inst, Oxford OX1 3LB - England
[3] Georgia Inst Technol, Sch Math, Atlanta, GA 30332 - USA
Total Affiliations: 3
Document type: Journal article
Source: Markov Processes and Related Fields; v. 20, n. 1, p. 107-144, 2014.
Web of Science Citations: 1
Abstract

The problem of determining the correct order of fluctuation of the optimal alignment score of two random strings of length n has been open for several decades: It is known {[}15] that the biased expected effect of a random letter-change on the optimal score implies an order of fluctuation linear in root n. However, in many situations where such a. biased effect is observed empirically, it has been impossible to prove analytically. The main result of this paper shows that when the rescaled-limit of the optimal alignment score increases in a certain direction, then the biased effect exists. On the basis of this result one can quantify a confidence level for the existence of such a biased effect and hence of an order root n fluctuation based on simulation of optimal alignments score's. This is an important, step forward, as the correct order of fluctuation was previously known only for certain special distributions {[}6,12,15,16]. To illustrate the usefulness of our new methodology, we apply it to optimal alignments of strings written in the DNA-alphabet. As scoring function, we use the BLASTZ default-substitution matrix together with a realistic gap penalty. BLASTZ is one of the most widely used sequence alignment methodologiesin bioinformatics. (In bioinformatics, the Basic Local Alignment Search Tool (BLAST), and variants there-off such as BLASTZ, are algorithms developed for detecting similarities between genetic sequences. The BLAST program was designed by Altschul, Gish, Miller, Myers, and Lipman at the NIH and was published {[}4,7] in 1990. It is based on the Karlin-Altschul statistics {[}14].) For this DNA-setting, we show that with a high level of confidence, the fluctuation of the optimal alignment score is of order Theta(root n). An important special case of optimal alignment score is the Longest Common Subsequence (LCS) of random strings. For binary sequences with equiprobably symbols the question of the fluctuation of the LCS remains open. The symmetry in that case does not allow for our method. On the other hand, in real-life DNA sequences, it is not the case that all letters occur with the same frequency. So, for many real life situations, our method allows to determine the order of the fluctuation up to a high confidence level. (AU)

FAPESP's process: 09/52379-8 - Stochastic modeling of interacting systems
Grantee:Fabio Prates Machado
Support Opportunities: Research Projects - Thematic Grants