... in a sex-dependent behavior in cancer patients. A differential sex effect of PSG genes with respect to tumor immune landscape and cancer outcomes was investigated using statistical, bioinformatic, and machine learning analyses in The Cancer Genome Atlas (TCGA) data. The resulting findings were...

...://www.ebi.ac.uk/pride/archive/projects/PXD040947 ). (2) For the case group of differentially abundant proteins, the parameters were added with . The standard deviation (SD) of the protein intensities on the log scale, , was sampled from an inverse gamma distribution (3) All default simulation parameters...

...Cong M Pham; Timothy J Rankin; Timothy P Stinear; Calum J Walsh; Feargal J Ryan In the past, DA analysis was performed using either simple statistical tests (e.g. Wilcoxon rank sum test), or by adapting differential gene expression approaches from transcriptomics (e.g. edgeR, DESeq2 [ 9 ]) although...

...-HS and neurodegenerative disorders differentiating from antibody-positive ALE and classical inflammatory CNS diseases with regard to B and plasma cell response. Longitudinal immune cell phenotyping in ALE revealed dynamic changes over time mainly affecting the innate, B and plasma cell compartment...

... differential equations difference equations machine learning statistical modeling hybrid model Page 5 of 62 Manuscripts submitted to Journal of Sickle Cell Disease 1 2 3 4 5 1 Mathematical Modeling of Sickle Cell 6 7 82 Disease: A Literature Review 9 10 11 3 4 Quindel Jones, Ph.D1, Reginald McGee, Ph.D.2...

... in-silico mixtures: CeDAR [ 9 ] utilizes a hierarchical Bayesian model for the detection of cell-type-specific signals. Its strength lies in leveraging the cell type hierarchy to improve the detection of differential signals. By utilizing correlations among related cell types, CeDAR increases detection...

... 496 0.637 LUSC 469 0.582 BLCA 402 0.562 ESCA 164 0.610 Target-WT 131 0.588 Table 2 -index values for different methods in the contexts of federated transfer learning with differential privacy and direct learning using only the target cancer data. The average of -index values...

... in these rhythms have been linked to a wide range of diseases. Identifying molecular biomarkers showing differential circadian (DC) patterns between biological conditions or disease status is important for disease prevention, diagnosis, and treatment. However, circadian pattern is characterized by three key...

... is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model ( https://dbpia.nl.go.kr/pages/standard-publication-reuse-rights ) Abstract The stabilization of a class of stochastic differential equations by using intermittent feedback control is studied...

... attention for the quantitative analysis of bioactive compounds due to their simplicity, sensitivity, and cost-effectiveness. The electrochemical determination of MIQ primarily involves the utilization of electrochemical techniques such as cyclic voltammetry and differential pulse voltammetry. Results...

.... Res, 63, 1026–1043) can be highly efficient at approximating expectations of path functionals associated with stochastic differential equations. However, algorithms for calculating the optimal distributions with an infinite horizon are lacking. In this article, based on the method of Cui et al. (2021...

... capacity (WHC), the study employed differential scanning calorimetry (DSC) and Raman spectroscopy. It was found that proteins in beef denatured in a sequence starting with the myosin head, followed by the myosin tail, sarcoplasmic proteins, and lastly actin. The application of Raman spectroscopy showed...

... subfigures, the individuals belonging to the control and case groups are indicated with blue and orange, respectively. Abstract Differential abundance analysis (DAA) is a key component of microbiome studies. Although dozens of methods exist, there is currently no consensus on the preferred methods. While...

...- simplex in . Such a metric is not classically differentiable in general, but it turns out that one can still attribute meaning to its Einstein curvature in a distributional sense. We study the convergence of the distributional Einstein curvature of to the Einstein curvature of under refinement...

... and therapeutic approaches for this rare malignancy. myoepithelial carcinoma cutaneous neoplasm immunohistochemistry differential diagnosis surgical excision Myoepithelial carcinoma (MEC) is a rare and highly aggressive malignant tumor originating from myoepithelial cells [ 1 ]. It most commonly occurs...

... : 1822 – 34 . 10.1097/PAS.0b013e3181831e68 . 4. Lauer   SR , Zhou   M , Master   VA , et al.   Chromophobe renal cell carcinoma with sarcomatoid differentiation: a clinicopathologic study of 14 cases . Anal Quant Cytopathol Histpathol   2013 ; 35 : 77 – 84 . 5. Zhao   WP...

... differences in Hi-C data between conditions, a comprehensive review and benchmark comparing their effectiveness is lacking. Results This study offers a comprehensive review and benchmark of 10 generic tools for differential analysis of Hi-C matrices at the interaction count level. The benchmark assesses...

... referred to as differential reactivity. ²⁷ Differential reactivity involves more transient behavioral changes, which have also been referred to as “activational” ²⁸ or “contextual” ²⁹ plasticity. Research on differential reactivity has mostly relied on experimental...

... algorithm with a deep neural network model. The statistical algorithm ranks differentially expressed genes by correlating their expression scores with the semantic similarity of their biological context, utilizing gene ontology information to align genes with known pathways. The deep neural network...

...-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact [email protected] Abstract Differential evolution (DE) is widely recognized in global optimization. However, it is not immune to the issue...