Constructing large suffix trees on a computational grid
Journal of Parallel and Distributed Computing
Assembling genomes on large-scale parallel computers
Journal of Parallel and Distributed Computing
Using Bloom Filters for Large Scale Gene Sequence Analysis in Haskell
PADL '09 Proceedings of the 11th International Symposium on Practical Aspects of Declarative Languages
Software note: Construction and characterization of a rock-cluster-based EST analysis pipeline
Computational Biology and Chemistry
Evolutionary Rough Parallel Multi-Objective Optimization Algorithm
Fundamenta Informaticae
Assembling genomes on large-scale parallel computers
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
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Expressed sequence tags, abbreviated as ESTs, are DNA molecules experimentally derived from expressed portions of genes. Clustering of ESTs is essential for gene recognition and for understanding important genetic variations such as those resulting in diseases. We present the algorithmic foundations and implementation of PaCE, a parallel software system we developed for large-scale EST clustering. The novel features of our approach include 1) design of space-efficient algorithms to limit the space required to linear in the size of the input data set, 2) a combination of algorithmic techniques to reduce the total work without sacrificing the quality of EST clustering, and 3) use of parallel processing to reduce runtime and facilitate clustering of large data sets. Using a combination of these techniques, we report the clustering of 327,632 rat ESTs in 47 minutes, and 420,694 Triticum aestivum ESTs in 3 hours and 15 minutes, using a 60-processor IBM xSeries cluster. These problems are well beyond the capabilities of state-of-the-art sequential software. We also present thorough experimental evaluation of our software including quality assessment using benchmark Arabidopsis EST data.