Intersect: identification and visualization of overlaps in database search results.

Area of Science:

• Bioinformatics
• Computational Biology
• Evolutionary Biology

Background:

• Determining distant evolutionary relationships is a significant challenge in biology.
• Distant homologs are often missed in standard sequence similarity searches due to insignificant statistical regions.
• Identifying conserved protein families and superfamilies is crucial for understanding biological function and evolution.

Purpose of the Study:

• To introduce Intersect, a novel computer program designed to address the challenge of identifying distant evolutionary relationships.
• To enhance the utility of sequence similarity search results by enabling the identification of overlapping sequences across multiple searches.
• To assist researchers in pinpointing key sequences that connect different protein families and superfamilies.

Main Methods:

• The study describes the development and functionality of the Intersect computer program.
• Intersect identifies and visualizes overlaps between sets of sequences obtained from various database searches.
• The program facilitates the integration and interpretation of data from multiple sequence similarity analyses.

Main Results:

• Intersect effectively identifies overlapping sequence regions that may be missed by individual searches.
• The program aids in the discovery of linking sequences that bridge distinct protein families.
• Visualization of overlaps enhances the understanding of complex evolutionary relationships.

Conclusions:

• Intersect is a valuable tool for researchers studying evolutionary biology and protein family relationships.
• The program improves the identification of distant homologs and strengthens the analysis of sequence similarity data.
• By extending the usefulness of database searches, Intersect aids in the comprehensive mapping of protein sequence space.