LowComplexity

LowComplexity identifies and analyzes low-complexity regions in DNA and protein sequences to characterize biased nucleotide composition, tandem or dispersed repeats, and palindrome-hairpin structures for genome structural analysis.

Key Features:

• Sequence types: Analyzes DNA and protein sequences, including long sequences such as entire bacterial genomes or eukaryotic chromosomes and groups of aligned sequences.
• Numerical measures of complexity: Employs a range of numerical measures incorporating combinatorial and linguistic approaches to assess sequence complexity.
• Modified Lempel-Ziv algorithm: Implements a modified Lempel-Ziv algorithm to estimate sequence complexity and detect low-complexity regions.
• Detection of composition and repeats: Identifies regions characterized by biased nucleotide composition, tandem or dispersed repeats, and palindrome-hairpin structures.

Scientific Applications:

• Genomic structural analysis: Identifies low-complexity regions to inform studies of genome structural organization and evolutionary dynamics.
• Bias detection in nucleotide content: Detects nucleotide composition biases that may affect gene regulation and genome stability.
• Repetitive element identification: Facilitates identification of tandem and dispersed repeats and palindrome-hairpin structures relevant to genomic architecture and function.

Methodology:

Integrates multiple complexity estimation methods, including combinatorial and linguistic measures, and applies a modified Lempel-Ziv algorithm to estimate sequence complexity.