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Complexity: an internet resource for analysis of DNA sequence complexity.

Y L Orlov¹, V N Potapov

¹Institute of Mathematics SB RAS, prosp. Koptyuga 4, Novosibirsk, 630090 Russia. orlov@bionet.nsc.ru

Nucleic Acids Research

|June 25, 2004

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This study introduces the "Complexity" software for identifying low-complexity DNA regions in genomes. It aids in structural analysis by detecting biased composition, repeats, and palindromes.

Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

Identifying low-complexity DNA regions is crucial for understanding genome structure.
Low complexity can arise from biased nucleotide composition, repeats, or palindromic structures.

Purpose of the Study:

To present a software tool, 'Complexity', for detecting low-complexity DNA regions.
To provide a method for analyzing sequence complexity in large datasets like genomes.

Main Methods:

Implementation of various numerical measures for textual complexity, including combinatorial and linguistic approaches.
Utilizing a modified Lempel-Ziv algorithm for complexity estimation.
Development of the 'Complexity' software tool.

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Main Results:

The 'Complexity' software effectively identifies low-complexity regions in long DNA sequences.
The tool can analyze complete bacterial genomes and eukaryotic chromosomes.
It also estimates the complexity of aligned sequence groups.

Conclusions:

The 'Complexity' software is a valuable tool for genomic structural analysis.
It aids researchers in identifying and characterizing functionally significant DNA regions.
The software facilitates the study of genome evolution and organization.