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BMCBI
2005

CLU: A new algorithm for EST clustering

13 years 4 months ago
CLU: A new algorithm for EST clustering
Background: The continuous flow of EST data remains one of the richest sources for discoveries in modern biology. The first step in EST data mining is usually associated with EST clustering, the process of grouping of original fragments according to their annotation, similarity to known genomic DNA or each other. Clustered EST data, accumulated in databases such as UniGene, STACK and TIGR Gene Indices have proven to be crucial in research areas from gene discovery to regulation of gene expression. Results: We have developed a new nucleotide sequence matching algorithm and its implementation for clustering EST sequences. The program is based on the original CLU match detection algorithm, which has improved performance over the widely used d2_cluster. The CLU algorithm automatically ignores low-complexity regions like poly-tracts and short tandem repeats. Conclusion: CLU represents a new generation of EST clustering algorithm with improved performance over current approaches. An early i...
Andrey A. Ptitsyn, Winston Hide
Added 15 Dec 2010
Updated 15 Dec 2010
Type Journal
Year 2005
Where BMCBI
Authors Andrey A. Ptitsyn, Winston Hide
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