Author

C. Velazquez

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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Animal Behavior & Cognition· 1 Cancer Biology· 1 Immunology· 1

Signature Assays, Organisms & Methods

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Approach:experimental assay· 2 Research Focus:host-pathogen & immune response· 2 Organism:human· 2 Assay:bulk RNA-seq· 1 Research Focus:cancer & tumor microenvironment· 1 Research Focus:cell signaling & trafficking· 1 Research Focus:drug response / drug discovery· 1 Assay:proteomics· 1

Frequent Co-Authors

A. Bouzas· 1 shared A. Chauchereau· 1 shared B. Orsetti· 1 shared C. Ribeyre· 1 shared C. Sardet· 1 shared C. Theillet· 1 shared C. Tiraboschi· 1 shared D. Compagno· 1 shared

Activity by Year

2019-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 16 mutual co-author links

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1 shared paperAnimal Behavior & Cognition

A. Bouzas

Author profile →

3 papers

Recent·Most cited

Replication poison treated BRCA1-deficient breast cancers are prone to MRE11 over-resection resulting in single strand DNA accumulation and mitotic catastrophe

I. Tabet, E. Orhan, E. Candiello, L. Fenou, C. Velazquez, B. Orsetti, G. Rodier, W. Jacot, C. Ribeyre, C. Sardet, C. Theillet

This study shows BRCA1-deficient breast cancers are highly sensitive to gemcitabine, leading to ssDNA accumulation and mitotic catastrophe, which may enhance antitumor immune response.

bioRxiv · Oct 31, 2023 · PreprintCancer Biology

Galectin-3 as a new negative checkpoint of the immune response is the key target for effective immunotherapy against prostate cancer

C. Tiraboschi, L. Gentilini, E. Corapi, F. M. Jaworski, C. Velazquez, A. Chauchereau, D. J. Laderach, D. Compagno

This paper identifies Galectin-3 as a key immune checkpoint in prostate cancer that Docetaxel inhibits, enhancing immunotherapy effectiveness through Th1 response promotion and CD8+ T cell activation.

bioRxiv · Sep 11, 2019 · PreprintImmunology

Velocity estimation in reinforcement learning

C. Velazquez, M. Villarreal, A. Bouzas

The paper investigates how people predict a fluctuating environment using reinforcement learning, finding that a hierarchical model with velocity estimation and uncertainty constraints performs best.

Computational Brain & Behavior · Jun 1, 2019Peer-reviewedAnimal Behavior & Cognition