Author

C. Chiva

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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Evolutionary Biology· 2 Cancer Biology· 1

Signature Assays, Organisms & Methods

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Organism:human· 2 Assay:proteomics· 2 Approach:statistical model· 2 Research Focus:cell type annotation· 1 Research Focus:chromatin & epigenetic regulation· 1 Research Focus:clustering· 1 Approach:comparative / phylogenetic analysis· 1 Approach:deep learning· 1

Frequent Co-Authors

E. Sabido· 3 shared A. Gamez-Pozo· 1 shared A. Sebe-Pedros· 1 shared A. Zapater-Moros· 1 shared B. F. Lang· 1 shared C. Navarrete· 1 shared C. Schleper· 1 shared D. Hardisson· 1 shared

Activity by Year

2020-2021 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 22 mutual co-author links

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3 shared papersEvolutionary Biology

E. Sabido

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

A phylogenetic and proteomic reconstruction of eukaryotic chromatin evolution

X. Grau-Bove, C. Navarrete, C. Chiva, T. Pribasnig, M. Anto, G. Torruella, L. J. Galindo, B. F. Lang, D. Moreira, P. Lopez-Garcia, I. Ruiz-Trillo, C. Schleper, E. Sabido, A. Sebe-Pedros

This study reconstructs the evolutionary history of eukaryotic chromatin by combining proteomics and phylogenetic analysis, revealing pre-eukaryotic origins of chromatin functions and eukaryotic innovations.

bioRxiv · Nov 30, 2021Evolutionary Biology

Transcriptome innovations in primates revealed by single-molecule long-read sequencing

L. Ferrandez-Peral, X. Zhan, M. Alvarez-Estape, C. Chiva, P. Esteller-Cucala, R. Garcia-Perez, E. Julia, E. Lizano, O. Fornas, E. Sabido, Q. Li, T. Marques-Bonet, D. Juan, G. Zhang

The paper uses long-read sequencing to identify novel transcripts and isoform changes in primate transcriptomes, highlighting immune-related regulatory divergence.

bioRxiv · Nov 10, 2021 · PreprintEvolutionary Biology

Molecular characterization of triple negative breast cancer formaldehyde-fixed paraffin-embedded samples by data independent acquisition proteomics

S. Garcia-Adrian, L. Trilla-Fuertes, A. Gamez-Pozo, C. Chiva, R. Lopez-Vacas, E. Lopez-Camacho, G. Prado-Vazquez, A. Zapater-Moros, M. I. Lumbreras-Herrera, D. Hardisson, L. Yebenes, P. Zamora, E. Sabido, J. A. Fresno Vara, E. Espinosa

This study uses proteomics to identify molecular subgroups and a prognostic signature in triple negative breast cancer samples, revealing differences in biological processes and potential therapeutic targets.

bioRxiv · Sep 21, 2020Cancer Biology