Universidad Complutense de Madrid-ko ikertzaileekin lankidetzan egindako argitalpenak (18)

2020

  1. Bayesian networks established functional differences between breast cancer subtypes

    PloS one, Vol. 15, Núm. 6, pp. e0234752

  2. Computational models applied to metabolomics data hints at the relevance of glutamine metabolism in breast cancer

    BMC Cancer, Vol. 20, Núm. 1

2019

  1. 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

  2. Biological molecular layer classification of muscle-invasive bladder cancer opens new treatment opportunities

    BMC Cancer, Vol. 19, Núm. 1

2018

  1. Molecular characterization of breast cancer cell response to metabolic drugs

    Oncotarget, Vol. 9, Núm. 11, pp. 9645-9660

  2. Probabilistic graphical models relate immune status with response to neoadjuvant chemotherapy in breast cancer

    Oncotarget, Vol. 9, Núm. 45, pp. 27586-27594

2017

  1. Functional proteomics outlines the complexity of breast cancer molecular subtypes

    Scientific Reports, Vol. 7, Núm. 1

2015

  1. 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

2014

  1. Sensitivity to hyperprior parameters in Gaussian Bayesian networks

    Journal of Multivariate Analysis, Vol. 124, pp. 214-225

2013

  1. Assessing the effect of kurtosis deviations from Gaussianity on conditional distributions

    Applied Mathematics and Computation, Vol. 219, Núm. 21, pp. 10499-10505

2011

  1. Evaluating the difference between graph structures in Gaussian Bayesian networks

    Expert Systems with Applications, Vol. 38, Núm. 10, pp. 12409-12414

  2. The effect of non-normality in the power exponential distributions

    Understanding Complex Systems, Vol. 2011, pp. 119-129

2010

  1. Conditional specification with exponential power distributions

    Communications in Statistics - Theory and Methods, Vol. 39, Núm. 12, pp. 2231-2240

  2. Dealing with uncertainty in Gaussian Bayesian networks from a regression perspective

    Proceedings of the 5th European Workshop on Probabilistic Graphical Models, PGM 2010

  3. Relative sensitivity of conditional distributions to kurtosis deviations in the joint model

    Procedia - Social and Behavioral Sciences

2009

  1. Analyzing the effect of introducing a kurtosis parameter in Gaussian Bayesian networks

    Reliability Engineering and System Safety, Vol. 94, Núm. 5, pp. 922-926

2004

  1. Asymptotic relationships between posterior probabilities and p-values using the hazard rate

    Statistics and Probability Letters, Vol. 66, Núm. 1, pp. 59-66

1997

  1. On tail behavior in Bayesian location inference

    Statistics and Probability Letters, Vol. 35, Núm. 4, pp. 363-370