SSA

SSA identifies and characterizes sequence motifs that are positionally correlated with functional sites such as transcription or translation initiation sites, facilitating analysis of eukaryotic promoter elements and regulatory sequence architecture.

Key Features:

• Identification of non-random sequence regions: Detects sequence regions under evolutionary constraint that indicate functional importance.
• Detection of consensus sequence-based motifs: Finds motifs that are over- or under-represented at specific distances from a functional site.
• Analysis of positional distribution: Analyzes how consensus sequence-based or weight matrix-based motifs distribute around functional sites.
• Optimization of weight matrix descriptions: Refines weight matrices describing locally over-represented sequence motifs to improve motif models.

Scientific Applications:

• Eukaryotic promoter analysis: Maps and characterizes motifs and their spatial relationships to transcription and translation initiation sites in promoter regions.
• Regulatory element discovery: Detects locally over-represented motifs and conserved sequence regions to infer candidate regulatory elements.

Methodology:

SSA provides four computer programs: Program 1 identifies non-random sequence regions under evolutionary constraint; Program 2 detects consensus sequence-based motifs that are over- or under-represented relative to a functional site; Program 3 analyzes the positional distribution of consensus sequence-based or weight matrix-based motifs around functional sites; and Program 4 optimizes weight matrix descriptions for locally over-represented motifs.