Search alternatives:
we decrease » _ decrease (Expand Search), nn decrease (Expand Search), mean decrease (Expand Search)
data based » data used (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
we decrease » _ decrease (Expand Search), nn decrease (Expand Search), mean decrease (Expand Search)
data based » data used (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
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Machine-Learning-Based Data Analysis Method for Cell-Based Selection of DNA-Encoded Libraries
Published 2023“…Researchers have developed several approaches to denoise DEL datasets, but it remains unclear whether they are suitable for cell-based DEL selections. Here, we report the proof-of-principle of a new machine-learning (ML)-based approach to process cell-based DEL selection datasets by using a Maximum A Posteriori (MAP) estimation loss function, a probabilistic framework that can account for and quantify uncertainties of noisy data. …”
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Machine-Learning-Based Data Analysis Method for Cell-Based Selection of DNA-Encoded Libraries
Published 2023“…Researchers have developed several approaches to denoise DEL datasets, but it remains unclear whether they are suitable for cell-based DEL selections. Here, we report the proof-of-principle of a new machine-learning (ML)-based approach to process cell-based DEL selection datasets by using a Maximum A Posteriori (MAP) estimation loss function, a probabilistic framework that can account for and quantify uncertainties of noisy data. …”
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Machine-Learning-Based Data Analysis Method for Cell-Based Selection of DNA-Encoded Libraries
Published 2023“…Researchers have developed several approaches to denoise DEL datasets, but it remains unclear whether they are suitable for cell-based DEL selections. Here, we report the proof-of-principle of a new machine-learning (ML)-based approach to process cell-based DEL selection datasets by using a Maximum A Posteriori (MAP) estimation loss function, a probabilistic framework that can account for and quantify uncertainties of noisy data. …”
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Machine-Learning-Based Data Analysis Method for Cell-Based Selection of DNA-Encoded Libraries
Published 2023“…Researchers have developed several approaches to denoise DEL datasets, but it remains unclear whether they are suitable for cell-based DEL selections. Here, we report the proof-of-principle of a new machine-learning (ML)-based approach to process cell-based DEL selection datasets by using a Maximum A Posteriori (MAP) estimation loss function, a probabilistic framework that can account for and quantify uncertainties of noisy data. …”
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Table 1_Effect of decreased suspended sediment content on chlorophyll-a in Dongting Lake, China.docx
Published 2025“…Additionally, a significant correlation between Chl-a concentration and SSC was found. …”
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Contains R code utilized in the analyses.
Published 2024“…The relative abundance of excitatory and inhibitory neurons, astrocytes, oligodendrocytes, microglia, and endothelial cells was estimated from the RNA sequencing data using a deconvolution-based analysis. Spearman correlation analysis between the individuals’ calendar ages and cell type proportions revealed a statistically significant decrease in the proportion of neurons with increasing age. …”
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The significance of variation in cortical trabecular bone stiffness between specimens.
Published 2024“…The Homogeneity of Variance based on the median was used to determine an appropriate statistical method to test for significant differences between slices within a Part; either a <sup>d</sup>Dunn’s post hoc test, <sup>e</sup>Dunnett’s T3 post hoc test or <sup>f</sup>Tukey’s post hoc test. …”
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