Results 21 to 30 of about 569,766 (265)
Robust genetic interaction analysis [PDF]
Briefings in Bioinformatics, 2018 For the risk, progression, and response to treatment of many complex diseases, it has been increasingly recognized that genetic interactions (including gene-gene and gene-environment interactions) play important roles beyond the main genetic and environmental effects.
Mengyun, Wu, Shuangge, Ma
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A New Bayesian Methodology for Nonlinear Model Calibration in Computational Systems Biology
Frontiers in Applied Mathematics and Statistics, 2020 Computational modeling is a common tool to quantitatively describe biological processes. However, most model parameters are usually unknown because they cannot be directly measured.
Fortunato Bianconi +3 more
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ISPRS International Journal of Geo-Information, 2022 Geometrically induced topology plays a major role in applications such as simulations, navigation, spatial or spatio-temporal analysis and many more. This article computes geometrically induced topology useful for such applications and extends previous ...
Markus Wilhelm Jahn +1 more
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Robust DREEM factor analysis [PDF]
Medical Teacher, 2014 Dear SirAt its conference in May 2014, the Korean Medical Education Society reported Dundee Ready Education Environment Measure (DREEM) data from 9096 students in 40/41 of that country’s medical sc...
Roff, Sue, McAleer, Sean
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Applied Sciences, 2023 Marine plankton communities play a vital role in global carbon and nutrient cycles. Ensuring the robustness of these intricate ecosystems is critical for sustainable environmental management.
Danfeng Zhao +4 more
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Frontiers in Bioinformatics, 2022 Brain tumor research has been stapled for human health while brain network research is crucial for us to understand brain activity. Here the structural controllability theory is applied to study three human brain-specific gene regulatory networks ...
Zhihua Chen, Siyuan Chen, Xiaoli Qiang
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System Analysis and Robustness [PDF]
, 2019 Software is increasingly embedded in a variety of physical contexts. This imposes new requirements on tools that support the design and analysis of systems. For instance, modeling embedded and cyber-physical systems needs to blend discrete mathematics, which is suitable for modeling digital components, with continuous mathematics, used for modeling ...
Moggi, Eugenio +2 more
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Robust Sparse Canonical Correlation Analysis [PDF]
SSRN Electronic Journal, 2015 Canonical correlation analysis (CCA) is a multivariate statistical method which describes the associations between two sets of variables. The objective is to find linear combinations of the variables in each data set having maximal correlation. This paper discusses a method for Robust Sparse CCA.
Wilms, Ines, Croux, Christophe
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Cellwise Robust Regularized Discriminant Analysis [PDF]
SSRN Electronic Journal, 2017 Quadratic and linear discriminant analysis (QDAandLDA) are the most often applied classification rules under normality. InQDA, a separate covariance matrix is estimated for each group. If there are more variables than observations in the groups, the usual estimates are singular and cannot be used anymore.
Stéphanie Aerts, Ines Wilms
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IEEE Access, 2023 It is shown in a recently published work that the GNN (gradient-based neural network) model activated by the msbp (modified sign-bi-power) function exhibits superior fixed-time convergence for solving the Sylvester equation in the noise-free case ...
Zhiguo Tan, Zhenlun Yang
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