Efficient discovery of unique signatures on whole-genome EST databases

Authors:
Hsiao Ping Lee;Tzu Fang Sheu;Yin Te Tsai
Affiliations:
National Tsing Hua University, Hsinchu, Taiwan, ROC;National Tsing Hua University, Hsinchu, Taiwan, ROC;Providence University, Shalu, Taiwan, ROC
Venue:
Proceedings of the 2005 ACM symposium on Applied computing
Year:
2005

Citing 3
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Efficient selection of unique and popular oligos for large EST databases†A preliminary version of this work was presented at the Symposium on Combinatorial Pattern Matching, Morelia, Mexico, and included in its Proceedings, pp. 273--283, LNCS 2676, Springer (2003).

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Proceedings of the 2010 ACM Symposium on Applied Computing

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Abstract

Expressed Sequence Tags (EST) are widely used for the discovery of new genes, particularly those involved in human disease processes. A subsequence in an EST dataset is unique if it appears only in one EST sequence of the dataset but does not appear in any other EST sequence. The unique subsequences can be regarded as signatures that distinguish an EST from all the others, and provide valuable information for many applications, such as PCR primer designs and microarray experiments. The discoveries of unique signatures on large-scale EST datasets are previously computational challenges. In this paper, we propose two efficient algorithms to extract the unique signatures from EST databases. The algorithms perform impressive discovery efficiencies in the experiments on real human ESTs.