Abstract
One of the fundamental components of large-scale gene discovery projects is that of clustering of Expressed Sequence Tags (ESTs) from complementary DNA (cDNA) clone libraries. Clustering is used to create non-redundant catalogs and indices of these sequences. In particular, clustering of ESTs is frequently used to estimate the number of genes derived from cDNA-based gene discovery efforts. This paper presents a novel parallel extension to an EST clustering program, UIcluster4, that incorporates alternative splicing information and a new parallelization strategy. The results are compared to other parallelized EST clustering systems in terms of overall processing time and in accuracy of the resulting clustering.
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Trivedi, N., Pedretti, K.T., Braun, T.A., Scheetz, T.E., Casavant, T.L. (2003). Alternative Parallelization Strategies in EST Clustering. In: Malyshkin, V.E. (eds) Parallel Computing Technologies. PaCT 2003. Lecture Notes in Computer Science, vol 2763. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45145-7_36
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DOI: https://doi.org/10.1007/978-3-540-45145-7_36
Publisher Name: Springer, Berlin, Heidelberg
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