HILARIO
NAVARRO VEGUILLAS
Profesor Titular Universidad
JORGE
MARTIN AREVALILLO
Profesor Permanente Laboral
Publicaciones en las que colabora con JORGE MARTIN AREVALILLO (21)
2023
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New Insights on the Multivariate Skew Exponential Power Distribution
Mathematica Slovaca, Vol. 73, Núm. 2, pp. 529-544
2021
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Skewness-based projection pursuit as an eigenvector problem in scale mixtures of skew-normal distributions
Symmetry, Vol. 13, Núm. 6
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Skewness-kurtosis model-based projection pursuit with application to summarizing gene expression data
Mathematics, Vol. 9, Núm. 9
2020
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Bayesian networks established functional differences between breast cancer subtypes
PloS one, Vol. 15, Núm. 6, pp. e0234752
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Computational models applied to metabolomics data hints at the relevance of glutamine metabolism in breast cancer
BMC Cancer, Vol. 20, Núm. 1
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Data projections by skewness maximization under scale mixtures of skew-normal vectors
Advances in Data Analysis and Classification, Vol. 14, Núm. 2, pp. 435-461
2019
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A novel approach to triple-negative breast cancer molecular classification reveals a luminal immune-positive subgroup with good prognoses
Scientific Reports, Vol. 9, Núm. 1
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A stochastic ordering based on the canonical transformation of skew-normal vectors
Test, Vol. 28, Núm. 2, pp. 475-498
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Biological molecular layer classification of muscle-invasive bladder cancer opens new treatment opportunities
BMC Cancer, Vol. 19, Núm. 1
2018
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Molecular characterization of breast cancer cell response to metabolic drugs
Oncotarget, Vol. 9, Núm. 11, pp. 9645-9660
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Probabilistic graphical models relate immune status with response to neoadjuvant chemotherapy in breast cancer
Oncotarget, Vol. 9, Núm. 45, pp. 27586-27594
2017
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Functional proteomics outlines the complexity of breast cancer molecular subtypes
Scientific Reports, Vol. 7, Núm. 1
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Urothelial cancer proteomics provides both prognostic and functional information
Scientific Reports, Vol. 7, Núm. 1
2015
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A note on the direction maximizing skewness in multivariate skew-t vectors
Statistics and Probability Letters, Vol. 96, pp. 328-332
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Combined label-free quantitative proteomics and microRNA expression analysis of breast cancer unravel molecular differences with clinical implications
Cancer Research, Vol. 75, Núm. 11, pp. 2243-2253
2013
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Exploring correlations in gene expression microarray data for maximum predictive-minimum redundancy biomarker selection and classification
Computers in Biology and Medicine, Vol. 43, Núm. 10, pp. 1437-1443
2012
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A study of the effect of kurtosis on discriminant analysis under elliptical populations
Journal of Multivariate Analysis, Vol. 107, pp. 53-63
2011
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A new method for identifying bivariate differential expression in high dimensional microarray data using quadratic discriminant analysis.
BMC bioinformatics, Vol. 12 Suppl 12
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Uncovering bivariate interactions in high dimensional data using random forests with data augmentation
Fundamenta Informaticae, Vol. 113, Núm. 2, pp. 97-115
2010
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A new approach for detecting bivariate interactions in high dimensional data using quadratic discriminant analysis
Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining