| Modelling fire ignition probability from satellite estimates of live fuel moisture content S Jurdao, E Chuvieco, JM Arevalillo Fire Ecology 8, 77-97, 2012 | 102 | 2012 |
| A novel approach to triple-negative breast cancer molecular classification reveals a luminal immune-positive subgroup with good prognoses G Prado-Vázquez, A Gámez-Pozo, L Trilla-Fuertes, JM Arevalillo, ... Scientific reports 9 (1), 1538, 2019 | 74 | 2019 |
| Combined label-free quantitative proteomics and microRNA expression analysis of breast cancer unravel molecular differences with clinical implications A Gámez-Pozo, J Berges-Soria, JM Arevalillo, P Nanni, R López-Vacas, ... Cancer research 75 (11), 2243-2253, 2015 | 59 | 2015 |
| Functional proteomics outlines the complexity of breast cancer molecular subtypes A Gámez-Pozo, L Trilla-Fuertes, J Berges-Soria, N Selevsek, ... Scientific Reports 7 (1), 10100, 2017 | 53 | 2017 |
| Problemas resueltos de iniciación al análisis estadístico de datos HN Veguillas, JM Arevalillo Editorial UNED, 2011 | 24 | 2011 |
| Identification of immune correlates of protection in Shigella infection by application of machine learning JM Arevalillo, MB Sztein, KL Kotloff, MM Levine, JK Simon Journal of biomedical informatics 74, 1-9, 2017 | 23 | 2017 |
| Molecular characterization of breast cancer cell response to metabolic drugs L Trilla-Fuertes, A Gámez-Pozo, JM Arevalillo, M Díaz-Almirón, ... Oncotarget 9 (11), 9645, 2018 | 22 | 2018 |
| Urothelial cancer proteomics provides both prognostic and functional information G de Velasco, L Trilla-Fuertes, A Gamez-Pozo, M Urbanowicz, ... Scientific Reports 7 (1), 15819, 2017 | 21 | 2017 |
| Biological molecular layer classification of muscle-invasive bladder cancer opens new treatment opportunities L Trilla-Fuertes, A Gámez-Pozo, G Prado-Vázquez, A Zapater-Moros, ... BMC cancer 19, 1-9, 2019 | 19 | 2019 |
| A machine learning approach to assess price sensitivity with application to automobile loan segmentation JM Arevalillo Applied Soft Computing 76, 390-399, 2019 | 18 | 2019 |
| A study of the effect of kurtosis on discriminant analysis under elliptical populations JM Arevalillo, H Navarro Journal of Multivariate Analysis 107, 53-63, 2012 | 18 | 2012 |
| A note on the direction maximizing skewness in multivariate skew-t vectors JM Arevalillo, H Navarro Statistics & Probability Letters 96, 328-332, 2015 | 16 | 2015 |
| Exploring correlations in gene expression microarray data for maximum predictive–minimum redundancy biomarker selection and classification JM Arevalillo, H Navarro Computers in Biology and Medicine 43 (10), 1437-1443, 2013 | 16 | 2013 |
| A new method for identifying bivariate differential expression in high dimensional microarray data using quadratic discriminant analysis JM Arevalillo, H Navarro BMC bioinformatics 12, 1-17, 2011 | 15 | 2011 |
| Computational models applied to metabolomics data hints at the relevance of glutamine metabolism in breast cancer L Trilla-Fuertes, A Gámez-Pozo, E López-Camacho, G Prado-Vázquez, ... BMC cancer 20, 1-11, 2020 | 14 | 2020 |
| A stochastic ordering based on the canonical transformation of skew-normal vectors JM Arevalillo, H Navarro Test 28, 475-498, 2019 | 14 | 2019 |
| Skewness-Kurtosis Model-Based Projection Pursuit with Application to Summarizing Gene Expression Data JM Arevalillo, H Navarro Mathematics 9 (9), 954, 2021 | 12 | 2021 |
| Probabilistic graphical models relate immune status with response to neoadjuvant chemotherapy in breast cancer A Zapater-Moros, A Gámez-Pozo, G Prado-Vázquez, L Trilla-Fuertes, ... Oncotarget 9 (45), 27586, 2018 | 10 | 2018 |
| Bayesian networks established functional differences between breast cancer subtypes L Trilla-Fuertes, A Gámez-Pozo, JM Arevalillo, R López-Vacas, ... PloS one 15 (6), e0234752, 2020 | 7 | 2020 |
| Using random forests to uncover bivariate interactions in high dimensional small data sets JM Arevalillo, H Navarro Proceedings of the KDD-09 Workshop on Statistical and Relational Learning in …, 2009 | 7 | 2009 |
