RegAnalyst

RegAnalyst analyzes regulatory elements in mycobacterial genomes to identify promoter and degenerate oligonucleotide motifs and support regulatory network analysis.

Key Features:

• MoPP (Motif Prediction Program): Performs de novo, greedy, inexact word‑based motif enumeration to discover highly degenerate oligonucleotide motifs, including completely degenerate motifs in noisy datasets.
• MyPatternFinder: Scans sequences or whole genomes for exact or approximate matches to query motifs, including motifs identified by MoPP or user-defined motifs.
• MycoRegDB (Mycobacterial Promoter and Regulatory Elements Database): Provides a repository of known mycobacterial promoter and regulatory elements for benchmarking and validation of predicted motifs.
• Integrated analysis: Combines motif discovery, genome-wide motif scanning, and a curated regulatory element database to support motif validation and comparative analysis.

Scientific Applications:

• Regulatory network analysis: Identification of degenerate motifs and promoters to elucidate gene regulatory networks in mycobacteria.
• Promoter and regulatory element discovery: Detection and analysis of promoter regions and other regulatory elements within mycobacterial genomes.
• Benchmarking and validation: Use of curated mycobacterial regulatory elements to validate motif predictions and assess motif discovery performance.
• Genomic studies: Support for basic and applied genomic investigations in mycobacterial research, including analyses that require handling of highly variable motif instances.

Methodology:

MoPP uses a de novo, greedy, inexact word‑based motif enumeration algorithm to detect degenerate oligonucleotide motifs; MyPatternFinder scans sequences or whole genomes for exact or approximate motif matches; MycoRegDB supplies known promoter and regulatory elements for benchmarking and validation, and benchmarking studies report that MoPP outperforms other motif discovery tools.