ARGO

ARGO detects region-specific degenerate oligonucleotide motifs and recognizes eukaryotic gene promoters to enable motif-based prediction of promoter activity and tissue-specific promoter analysis.


Key Features:

  • Detection of Degenerate Oligonucleotide Motifs: ARGO_Motifs identifies sets of region-specific degenerate oligonucleotide motifs within regulatory regions.
  • Improved Promoter Recognition Accuracy: ARGO_Motifs enhances promoter recognition accuracy by leveraging the collective presence of motif ensembles correlated with gene expression features.
  • Tissue-Specific Promoter Analysis: ARGO_Viewer uses motif data generated by ARGO_Motifs to analyze and predict tissue-specific promoter activity.
  • Empirical Validation: Empirical analysis using five gene samples demonstrated the quality and reliability of ARGO's promoter recognition.

Scientific Applications:

  • Gene Expression Studies: Identification of tissue-specific promoters to investigate gene expression patterns across tissues in development, disease, and differentiation.
  • Functional Genomics: Detection of regulatory motifs to explore promoter function and its impact on gene regulation within genomic architectures.
  • Comparative Genomics: Comparison of promoter regions across eukaryotic genomes to assess evolutionary conservation and divergence of regulatory mechanisms.

Methodology:

ARGO employs a motif-based approach that systematically searches regulatory regions for degenerate oligonucleotide motifs, integrates motif ensembles to predict promoter activity and specificity, and refines predictions with tissue-specific analysis via ARGO_Viewer.

Topics

Details

Tool Type:
web application
Operating Systems:
Linux, Windows, Mac
Added:
2/10/2017
Last Updated:
11/25/2024

Operations

Publications

Vishnevsky OV, Kolchanov NA. ARGO: a web system for the detection of degenerate motifs and large-scale recognition of eukaryotic promoters. Nucleic Acids Research. 2005;33(Web Server):W417-W422. doi:10.1093/nar/gki459. PMID:15980502. PMCID:PMC1160220.

Documentation