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Showing 1 to 4 of 4 for “"NGS Data Analysis"”.
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Computational Pipeline for Human Transcriptome Quantification Using RNA-seq Data
… Next-generation RNA sequencing (RNA-seq) data. RNA-seq experiments generate tens of millions of short reads for each DNA/RNA sample. The alignment of a large volume of short reads to a reference genome is a key step in NGS data analysis. Although storing alignment information in the …
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Development of Novel Methods to Minimize The Impact of Sequencing Errors In The Next-Generation Sequencing Data Analysis
<p>Next-generation sequencing (NGS) technology has become a prominent tool in biological and biomedical research. However, NGS data analysis, such as <em>de novo</em> assembly, mapping and variants detection is far from maturity, and the high sequencing error-rate is one of the major problems. …
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Statistical methods for variant discovery and functional genomic analysis using next-generation sequencing data
… of high-throughput next-generation sequencing (NGS) techniques produces massive amount of data, allowing the identification of biomarkers in early disease diagnosis and driving the transformation of most disciplines in biology and medicine. A greater concentration is needed in developing novel, …
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Bayesian Integration and Modeling for Next-generation Sequencing Data Analysis
… biology currently faces challenges in a big data world with thousands of data samples across multiple disease types including cancer. The challenging problem is how to extract biologically meaningful information from large-scale genomic data. Next-generation Sequencing (NGS) can now produce …