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Vine copula graphical models in the construction of biological networks
Date
2019-09-19
Author
Farnoudkia, Hajar
Purutçuoğlu Gazi, Vilda
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https://hdl.handle.net/11511/78360
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Vine copula graphical models in the construction of biological networks
Farnoudkia, Hajar; Purutçuoğlu Gazi, Vilda (2021-01-01)
The copula Gaussian graphical model (CGGM) is one of the major mathematical models for high dimensional biological networks which provides a graphical representation, espe-cially, for sparse networks. Basically, this model uses a regression of the Gaussian graphical model (GGM) whose precision matrix describes the conditional dependence between the variables to estimate the coefficients of the linear regression model. The Bayesian inference for the model parameters is used to overcome the dimensional limita...
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Deep learning-based approaches have shown highly successful performance in the categorization of digitized biopsy samples. The commonly used setting in these approaches is to employ convolutional neural networks for classification of data sets consisting of images all having the same size. However, the clinical practice in breast histopathology necessitates multi-class categorization of regions of interest (ROI) in biopsy samples where these regions can have arbitrary shapes and sizes. The typical solution ...
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H. Farnoudkia and V. Purutçuoğlu Gazi, “Vine copula graphical models in the construction of biological networks,” 2019, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/78360.