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Titlebook: Computational Advances in Bio and Medical Sciences; 10th International C Sumit Kumar Jha,Ion Măndoiu,Alex Zelikovsky Conference proceedings

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https://doi.org/10.1007/978-1-4020-8733-2software, read trimmers, and sequence masks. Many programs appear to use arbitrarily chosen features that are putatively relevant to DNA alignment quality. Machine learning gives a ready way to empirically assess a variety of features and rank them according to their importance. Sequence complexity
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1D Finite Elements for Axially Loaded Rods,to stress urinary incontinence by generating spontaneous mechanical and electrical activities. It generates spontaneous electrical events in the terms of membrane depolarization and action potentials. Therefore, a complete understanding of the urethral smooth muscle cell’s spontaneous action potenti
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https://doi.org/10.1007/978-1-4020-8733-2tional analysis of single cell RNA-Seq (scRNA-Seq) data. In this paper, we introduce SC1CC (. .ell .ycle analysis tool), a computational approach for clustering and ordering single cell transcriptional profiles according to their progression along cell cycle phases. We also introduce a new robust me
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