PLoS ONE · 2014 · 44 citations · 31 references
Life SciencesBioinformaticsHigh-performance ComputingComputational BiologyParallel ComputingSequence AnalysisData ParallelismDna SequencingDynamic Programming For AlignmentMemory Hierarchy OptimizationNext-generation SequencingSequence AlignmentComputational Alignment AlgorithmsComputational Efficiency In AlignmentCpu OptimizationNext-generation Sequencing Data AnalysisParallel SequencingSequence Space Exploration
UNLABELLED: Due to the size of Next-Generation Sequencing data, the computational challenge of sequence alignment has been vast. Inexact alignments can take up to 90% of total CPU time in bioinformatics pipelines. High-performance Integrated Virtual Environment (HIVE), a cloud-based environment optimized for storage and analysis of extra-large data, presents an algorithmic solution: the HIVE-hexagon DNA sequence aligner. HIVE-hexagon implements novel approaches to exploit both characteristics of sequence space and CPU, RAM and Input/Output (I/O) architecture to quickly compute accurate alignments. Key components of HIVE-hexagon include non-redundification and sorting of sequences; floating diagonals of linearized dynamic programming matrices; and consideration of cross-similarity to minimize computations. AVAILABILITY: https://hive.biochemistry.gwu.edu/hive/
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Basic local alignment search tool
Stephen F. Altschul, Warren Gish, Webb Miller et al. · Journal of Molecular Biology · 1990 · 94.5K citations
Space/time trade-offs in hash coding with allowable errors
Burton H. Bloom · Communications of the ACM · 1970 · 7.5K citations · Full text