RISO

RISO identifies cis-regulatory modules within genomic sequences by detecting conserved, regularly spaced structured motifs that represent promoter models.

Key Features:

• Algorithmic Innovation: Employs a novel algorithm that uses a "box-link" data structure to efficiently store information about conserved regions.
• Efficiency: Achieves improved time and space complexity compared to existing exact algorithms, particularly for large spacings between binding sites.
• Performance: Demonstrates experimental speed improvements of more than four orders of magnitude over other methods in certain cases.

Scientific Applications:

• Consensus extraction: Extracts relevant consensi from biological datasets by identifying structured motifs.
• Regulatory mechanism analysis: Identifies cis-regulatory modules and promoter models to support investigation of gene regulatory mechanisms and other regulatory elements.

Methodology:

RISO implements a novel algorithm that leverages a "box-link" data structure to represent conserved regions and attains better time and space complexity than existing exact algorithms, especially for large inter-site spacings.