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MOTIVATION Rapid advances in next-generation sequencing (NGS) technology have led to exponential increase in the amount of genomic information. However, NGS reads contain far more errors than data from traditional sequencing methods, and downstream genomic analysis results can be improved by correcting the errors. Unfortunately, all the previous error(More)
With the cost reduction of the next-generation sequencing (NGS) technologies, genomics has provided us with an unprecedented opportunity to understand fundamental questions in biology and elucidate human diseases. De novo genome assembly is one of the most important steps to reconstruct the sequenced genome. However, most de novo assemblers require enormous(More)
The homozygous deletion allele of the angiotensin-converting enzyme gene (ACE/DD), homozygous threonine allele of the angiotensinogen gene (AGN/TT), and the epsilon4 allele of the apolipoprotein E gene (apoE/epsilon4) are reported to be associated with ischemic heart disease. Cerebral infarction (CI) is another atherosclerotic disease, and the effects of(More)
UNLABELLED The most important features of error correction tools for sequencing data are accuracy, memory efficiency and fast runtime. The previous version of BLESS was highly memory-efficient and accurate, but it was too slow to handle reads from large genomes. We have developed a new version of BLESS to improve runtime and accuracy while maintaining a(More)
Stem cells have infinite potential for regenerative therapy thanks to their advantageous ability which is differentiable to requisite cell types for recovery and self-renewal. The microsystem has been proved to be more helpful to stem cell studies compared to the traditional methods, relying on its advantageous feature of mimicking in vivo cellular(More)
Correcting errors in DNA sequencing data is an important process that can improve the quality of downstream analysis using the data. Even though many error-correction methods have been proposed for Illumina reads, their throughput is not high enough to process data from large genomes. The current paper describes the first FPGA-based error-correction tool,(More)
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