Author

M. Diaz-Almiron

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Cancer Biology· 2 Microbiology· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Approach:statistical model· 3 Research Focus:differential expression· 2 Assay:proteomics· 2 Assay:bulk RNA-seq· 1 Research Focus:cell signaling & trafficking· 1 Research Focus:cell type annotation· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

A. Gamez-Pozo· 3 shared L. Trilla-Fuertes· 3 shared A. Zapater-Moros· 2 shared E. Espinosa· 2 shared G. Prado-Vazquez· 2 shared J. A. Fresno Vara· 2 shared R. Lopez-Vacas· 2 shared A. Moya· 1 shared

Activity by Year

2018-2020 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 30 mutual co-author links

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3 shared papersCancer Biology

A. Gamez-Pozo

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Functional characterization of SARS-CoV-2 infection suggests a complex inflammatory response and metabolic alterations

L. Trilla-Fuertes, R. Ramos-Ruiz, N. Blanca-Lopez, E. Lopez-Camacho, L. Martin-Pedraza, P. Ryan Murua, M. Diaz-Almiron, C. Llorens, T. Gabaldon, A. Moya, J. A. Fresno, A. Gamez-Pozo

This study analyzes RNAseq data from COVID-19 patients and healthy controls to identify inflammatory and metabolic changes associated with SARS-CoV-2 infection.

bioRxiv · Jun 22, 2020 · PreprintMicrobiology

Computational metabolism modeling predicts risk of distant relapse-free survival in breast cancer patients

L. Trilla-Fuertes, A. Gamez-Pozo, M. Diaz-Almiron, G. Prado-Vazquez, A. Zapater-Moros, R. Lopez-Vacas, P. Nanni, P. Zamora, E. Espinosa, J. A. Fresno Vara

The paper uses flux balance analysis on proteomics data to identify metabolic pathways associated with prognosis in breast cancer patients.

bioRxiv · Nov 12, 2018Cancer Biology

Bayesian Networks established functional differences between breast cancer subtypes

L. Trilla-Fuertes, A. Zapater-Moros, A. Gamez-Pozo, J. M. Arevalillo, G. Prado-Vazquez, M. Diaz-Almiron, M. Ferrer-Gomez, R. Lopez-Vacas, H. Navarro, E. Espinosa, P. Main, J. A. Fresno Vara

The paper uses Bayesian networks and proteomics data to identify functional differences between breast cancer subtypes, including a new TN-like subtype, and finds a metastasis-related component with prognostic value.

bioRxiv · May 18, 2018Cancer Biology