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Post-processing of BLAST results using databases of clustered sequences

G S Miller¹, R Fuchs

¹Glaxo Wellcome Inc. Bioinformatics Group, Research Triangle Park, NC 27709, USA.

Computer Applications in the Biosciences : CABIOS

|February 1, 1997

Summary

A new program, CBLAST, sorts BLAST search results by sequence clusters. This tool helps identify relationships between new sequences and existing database entries, revealing biological insights.

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Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Identifying shared characteristics among sequences in similarity searches is crucial for biological insights.
Dependencies between database entries are often hidden, hindering the discovery of gene and protein functions.

Purpose of the Study:

To develop a computational tool for organizing and analyzing sequence similarity search results.
To facilitate the identification of relationships between novel sequences and known database entries.

Main Methods:

Developed CBLAST, a program to sort BLAST search results based on user-defined sequence clusters.
Constructed two cluster databases: one for UNIGENE nucleotide sequences and another for PROSITE protein families.

Main Results:

CBLAST efficiently sorts sequence similarity search results by cluster membership.
The constructed cluster databases enable exploration of sequence relationships.

Conclusions:

CBLAST and cluster databases offer an efficient method for discovering dependencies between sequences.
This approach aids in understanding the biological function of genes and proteins through sequence analysis.