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Post-processing of BLAST results using databases of clustered sequences
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.
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.
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