SEGMENT: identifying compositional domains in DNA sequences

doi:10.1093/bioinformatics/15.12.974

SEGMENT: identifying compositional domains in DNA sequences

1999-12-01

0

OA

AI

DOI：10.1093/bioinformatics/15.12.974

原文链接

查看原文

摘要

En 中文

Abstract Motivation: DNA sequences are formed by patches or domains of different nucleotide composition. In a few simple sequences, domains can simply be identified by eye; however, most DNA sequences show a complex compositional heterogeneity (fractal structure), which cannot be properly detected by current methods. Recently, a computationally efficient segmentation method to analyse such nonstationary sequence structures, based on the Jensen–Shannon entropic divergence, has been described. Specific algorithms implementing this method are now needed. Results: Here we describe a heuristic segmentation algorithm for DNA sequences, which was implemented on a Windows program (SEGMENT). The program divides a DNA sequence into compositionally homogeneous domains by iterating a local optimization procedure at a given statistical significance. Once a sequence is partitioned into domains, a global measure of sequence compositional complexity (SCC), accounting for both the sizes and compositional biases of all the domains in the sequence, is derived. SEGMENT computes SCC as a function of the significance level, which provides a multiscale view of sequence complexity. Availability: SEGMENT is available on the Web at http://www.ugr.es/local/oliver/segment/ Contact: oliver@ugr.es

SEGMENT: identifying compositional domains in DNA sequences

摘要

AI总结

期刊

机构

引用论文