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Jorge M Arevalillo

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BMC Bioinformatics|December 16, 2011
A new method for identifying bivariate differential expression in high dimensional microarray data using quadratic discriminant analysisJorge M Arevalillo, Hilario Navarro
Computers in Biology and Medicine|September 17, 2013
Exploring correlations in gene expression microarray data for maximum predictive-minimum redundancy biomarker selection and classificationJorge M Arevalillo, Hilario Navarro
Statistical Applications in Genetics and Molecular Biology|November 22, 2023
Patterns of differential expression by association in omic data using a new measure based on ensemble learningJorge M Arevalillo, Raquel Martin-Arevalillo
Journal of Biomedical Informatics|August 14, 2017
Identification of immune correlates of protection in Shigella infection by application of machine learningJorge M Arevalillo, Marcelo B Sztein, Karen L Kotloff, et al.
Oncotarget|July 3, 2018
Probabilistic graphical models relate immune status with response to neoadjuvant chemotherapy in breast cancerAndrea Zapater-Moros, Angelo Gámez-Pozo, Guillermo Prado-Vázquez, et al.
BMC Cancer|June 30, 2019
Biological molecular layer classification of muscle-invasive bladder cancer opens new treatment opportunitiesLucía Trilla-Fuertes, Angelo Gámez-Pozo, Guillermo Prado-Vázquez, et al.
Cancer Research|April 18, 2015
Combined Label-Free Quantitative Proteomics and microRNA Expression Analysis of Breast Cancer Unravel Molecular Differences with Clinical ImplicationsAngelo Gámez-Pozo, Julia Berges-Soria, Jorge M Arevalillo, et al.
BMC Cancer|April 16, 2020
Computational models applied to metabolomics data hints at the relevance of glutamine metabolism in breast cancerLucía Trilla-Fuertes, Angelo Gámez-Pozo, Elena López-Camacho, et al.
Scientific Reports|February 9, 2019
A novel approach to triple-negative breast cancer molecular classification reveals a luminal immune-positive subgroup with good prognosesGuillermo Prado-Vázquez, Angelo Gámez-Pozo, Lucía Trilla-Fuertes, et al.
Plos One|June 12, 2020
Bayesian networks established functional differences between breast cancer subtypesLucía Trilla-Fuertes, Angelo Gámez-Pozo, Jorge M Arevalillo, et al.
Pageof 2

Showing results (1-10 of 13) with videos related to

Sort By:
Pageof 2
BMC Bioinformatics|December 16, 2011
A new method for identifying bivariate differential expression in high dimensional microarray data using quadratic discriminant analysisJorge M Arevalillo, Hilario Navarro
Computers in Biology and Medicine|September 17, 2013
Exploring correlations in gene expression microarray data for maximum predictive-minimum redundancy biomarker selection and classificationJorge M Arevalillo, Hilario Navarro
Statistical Applications in Genetics and Molecular Biology|November 22, 2023
Patterns of differential expression by association in omic data using a new measure based on ensemble learningJorge M Arevalillo, Raquel Martin-Arevalillo
Journal of Biomedical Informatics|August 14, 2017
Identification of immune correlates of protection in Shigella infection by application of machine learningJorge M Arevalillo, Marcelo B Sztein, Karen L Kotloff, et al.
Oncotarget|July 3, 2018
Probabilistic graphical models relate immune status with response to neoadjuvant chemotherapy in breast cancerAndrea Zapater-Moros, Angelo Gámez-Pozo, Guillermo Prado-Vázquez, et al.
BMC Cancer|June 30, 2019
Biological molecular layer classification of muscle-invasive bladder cancer opens new treatment opportunitiesLucía Trilla-Fuertes, Angelo Gámez-Pozo, Guillermo Prado-Vázquez, et al.
Cancer Research|April 18, 2015
Combined Label-Free Quantitative Proteomics and microRNA Expression Analysis of Breast Cancer Unravel Molecular Differences with Clinical ImplicationsAngelo Gámez-Pozo, Julia Berges-Soria, Jorge M Arevalillo, et al.
BMC Cancer|April 16, 2020
Computational models applied to metabolomics data hints at the relevance of glutamine metabolism in breast cancerLucía Trilla-Fuertes, Angelo Gámez-Pozo, Elena López-Camacho, et al.
Scientific Reports|February 9, 2019
A novel approach to triple-negative breast cancer molecular classification reveals a luminal immune-positive subgroup with good prognosesGuillermo Prado-Vázquez, Angelo Gámez-Pozo, Lucía Trilla-Fuertes, et al.
Plos One|June 12, 2020
Bayesian networks established functional differences between breast cancer subtypesLucía Trilla-Fuertes, Angelo Gámez-Pozo, Jorge M Arevalillo, et al.
Pageof 2