Author

V. Fernandez-Lanza

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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Microbiology· 2 Ecology· 1

Signature Assays, Organisms & Methods

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Approach:experimental assay· 2 Research Focus:host-pathogen & immune response· 1 Organism:human· 1 Approach:simulation· 1

Frequent Co-Authors

F. Baquero· 3 shared C. Llorens· 2 shared J.-M. Sempere· 2 shared M. Campos· 2 shared R. Canton· 2 shared A. Halperin· 1 shared A. Moya· 1 shared A. Prieto· 1 shared

Activity by Year

2018-2021 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 28 mutual co-author links

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3 shared papersMicrobiology

F. Baquero

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3 papers

Recent·Most cited

Predation Efficiency upon Clinical Isolates: Bdellovibrio bacteriovorus is Prey Specific and Origin Dependent

C. Herencias, C. Saralegui, A. Halperin, J. d. D. Caballero, B. Perez-Viso, S. Salgado-Briegas, V. Fernandez-Lanza, R. Canton, F. Baquero, A. Prieto, R. del Campo

This study evaluates the predation efficiency of Bdellovibrio bacteriovorus on clinical isolates of Serratia marcescens and Pseudomonas aeruginosa, finding that origin, not genetic background or antibiotic resistance, determines prey susceptibility.

bioRxiv · Jul 13, 2021 · PreprintEcology

Simulating the Influence of Conjugative Plasmids Kinetic Values on the Multilevel Dynamics of Antimicrobial Resistance in a Membrane Computing Model

M. Campos, A. San-Milan, J.-M. Sempere, V. Fernandez-Lanza, T. M. Coque, C. Llorens, F. Baquero

This paper simulates how plasmid kinetic values affect antimicrobial resistance dynamics in a membrane computing model, finding that conjugation rates and plasmid loss rates influence plasmid dominance and resistance gene spread.

bioRxiv · Mar 27, 2020Microbiology

Simulating multi-level dynamics of antimicrobial resistance in a membrane computing model

M. Campos, R. Capilla, C. Llorens, R. Canton, A. Moya, J.-M. Sempere, T. Coque, V. Fernandez-Lanza, F. Naya, R. Futami, F. Baquero

The paper uses a membrane computing model to simulate and analyze the multi-level dynamics of antimicrobial resistance across genes, clones, species, hosts, and environments.

bioRxiv · Nov 16, 2018 · PreprintMicrobiology