Fernando Corona

1.6k total citations · 1 hit paper
20 papers, 1.2k citations indexed

About

Fernando Corona is a scholar working on Molecular Biology, Molecular Medicine and Genetics. According to data from OpenAlex, Fernando Corona has authored 20 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 11 papers in Molecular Medicine and 8 papers in Genetics. Recurrent topics in Fernando Corona's work include Antibiotic Resistance in Bacteria (11 papers), Bacterial biofilms and quorum sensing (10 papers) and Bacterial Genetics and Biotechnology (7 papers). Fernando Corona is often cited by papers focused on Antibiotic Resistance in Bacteria (11 papers), Bacterial biofilms and quorum sensing (10 papers) and Bacterial Genetics and Biotechnology (7 papers). Fernando Corona collaborates with scholars based in Spain, United States and Mexico. Fernando Corona's co-authors include José Luis Martínez, Paula Blanco, María Blanca Sánchez, Jose Antonio Reales‐Calderón, Alejandra Bernardini, Manuel Alcalde‐Rico, Sara Hernando‐Amado, Felipe Lira, Jorge Olivares‐Pacheco and Concha Gil and has published in prestigious journals such as Scientific Reports, International Journal of Molecular Sciences and Antimicrobial Agents and Chemotherapy.

In The Last Decade

Fernando Corona

20 papers receiving 1.2k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Bacterial Multidrug Efflux Pumps: Much More Than Antibiotic Resistance Determinants

2016 477 citations Paula Blanco, Sara Hernando‐Amado et al. Microorganisms profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Fernando Corona Spain	14	595	542	272	210	168	20	1.2k
Paula Blanco Spain	15	684 1.1×	539 1.0×	274 1.0×	304 1.4×	125 0.7×	22	1.3k
Manuel Alcalde‐Rico Spain	13	740 1.2×	587 1.1×	264 1.0×	184 0.9×	123 0.7×	28	1.2k
Ilyas Alav United Kingdom	10	619 1.0×	576 1.1×	213 0.8×	172 0.8×	132 0.8×	15	1.5k
Laura Martínez‐Solano Spain	8	430 0.7×	452 0.8×	253 0.9×	132 0.6×	181 1.1×	8	1.0k
Eleftheria Trampari United Kingdom	11	356 0.6×	512 0.9×	143 0.5×	141 0.7×	182 1.1×	20	1.2k
Jingjing Sun China	14	389 0.7×	567 1.0×	143 0.5×	149 0.7×	84 0.5×	29	1.3k
Carolina Alvarez‐Ortega Spain	13	868 1.5×	846 1.6×	337 1.2×	279 1.3×	361 2.1×	18	1.6k
Sara Domingues Portugal	15	690 1.2×	396 0.7×	391 1.4×	313 1.5×	87 0.5×	28	1.1k
João Botelho Portugal	15	569 1.0×	522 1.0×	147 0.5×	210 1.0×	95 0.6×	30	1.0k
Xuan Wang‐Kan United Kingdom	7	518 0.9×	382 0.7×	112 0.4×	147 0.7×	146 0.9×	7	930

Countries citing papers authored by Fernando Corona

Since Specialization

Citations

This map shows the geographic impact of Fernando Corona's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Fernando Corona with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fernando Corona more than expected).

Fields of papers citing papers by Fernando Corona

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fernando Corona. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Fernando Corona. The network helps show where Fernando Corona may publish in the future.

Co-authorship network of co-authors of Fernando Corona

This figure shows the co-authorship network connecting the top 25 collaborators of Fernando Corona. A scholar is included among the top collaborators of Fernando Corona based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Fernando Corona. Fernando Corona is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Gil‐Gil, Teresa, Sara Hernando‐Amado, Jose Antonio Reales‐Calderón, et al.. (2023). Virulence and Metabolism Crosstalk: Impaired Activity of the Type Three Secretion System (T3SS) in a Pseudomonas aeruginosa Crc-Defective Mutant. International Journal of Molecular Sciences. 24(15). 12304–12304. 5 indexed citations

2.

Gil‐Gil, Teresa, José Ramón Valverde, José Luis Martínez, & Fernando Corona. (2023). In vivo genetic analysis of Pseudomonas aeruginosa carbon catabolic repression through the study of CrcZ pseudo-revertants shows that Crc-mediated metabolic robustness is needed for proficient bacterial virulence and antibiotic resistance. Microbiology Spectrum. 11(6). e0235023–e0235023. 5 indexed citations

3.

Gil‐Gil, Teresa, Fernando Corona, José Luis Martínez, & Alejandra Bernardini. (2020). The Inactivation of Enzymes Belonging to the Central Carbon Metabolism Is a Novel Mechanism of Developing Antibiotic Resistance. mSystems. 5(3). 21 indexed citations

4.

Blanco, Paula, Fernando Corona, & José Luis Martínez. (2019). Involvement of the RND efflux pump transporter SmeH in the acquisition of resistance to ceftazidime in Stenotrophomonas maltophilia. Scientific Reports. 9(1). 4917–4917. 35 indexed citations

5.

Blanco, Paula, Fernando Corona, & José Luis Martínez. (2019). Mechanisms and phenotypic consequences of acquisition of tigecycline resistance by Stenotrophomonas maltophilia. Journal of Antimicrobial Chemotherapy. 74(11). 3221–3230. 19 indexed citations

6.

Corona, Fernando, Jose Antonio Reales‐Calderón, Concha Gil, & José Luis Martínez. (2018). The development of a new parameter for tracking post-transcriptional regulation allows the detailed map of the Pseudomonas aeruginosa Crc regulon. Scientific Reports. 8(1). 16793–16793. 24 indexed citations

7.

Blanco, Paula, Fernando Corona, & José Luis Martínez. (2018). Biolog Phenotype Microarray Is a Tool for the Identification of Multidrug Resistance Efflux Pump Inducers. Antimicrobial Agents and Chemotherapy. 62(11). 24 indexed citations

8.

Corona, Fernando, José Luis Martínez, & Pablo I. Nikel. (2018). The global regulator Crc orchestrates the metabolic robustness underlying oxidative stress resistance in Pseudomonas aeruginosa. Environmental Microbiology. 21(3). 898–912. 24 indexed citations

9.

Blanco, Paula, Fernando Corona, María Blanca Sánchez, & José Luis Martínez. (2017). Vitamin K ₃ Induces the Expression of the Stenotrophomonas maltophilia SmeVWX Multidrug Efflux Pump. Antimicrobial Agents and Chemotherapy. 61(5). 22 indexed citations

10.

Hernando‐Amado, Sara, Paula Blanco, Manuel Alcalde‐Rico, et al.. (2016). Multidrug efflux pumps as main players in intrinsic and acquired resistance to antimicrobials. Drug Resistance Updates. 28. 13–27. 149 indexed citations

11.

Minchin, R. Edward, et al.. (2016). Chinese Organizations’ Actions, Attitudes, and Motivations When Faced with Counterfeit Items in Their Construction Supply Chains. Journal of Legal Affairs and Dispute Resolution in Engineering and Construction. 9(2). 7 indexed citations

12.

Corona, Fernando, Paula Blanco, Manuel Alcalde‐Rico, et al.. (2016). The Analysis of the Antibiotic Resistome Offers New Opportunities for Therapeutic Intervention. Future Medicinal Chemistry. 8(10). 1133–1151. 18 indexed citations

13.

Reales‐Calderón, Jose Antonio, Paula Blanco, Manuel Alcalde‐Rico, et al.. (2016). Use of phenotype microarrays to study the effect of acquisition of resistance to antimicrobials in bacterial physiology. Research in Microbiology. 167(9-10). 723–730. 2 indexed citations

14.

Blanco, Paula, Sara Hernando‐Amado, Jose Antonio Reales‐Calderón, et al.. (2016). Bacterial Multidrug Efflux Pumps: Much More Than Antibiotic Resistance Determinants. Microorganisms. 4(1). 14–14. 477 indexed citations breakdown →

15.

Reales‐Calderón, Jose Antonio, Fernando Corona, Lucía Monteoliva, Concha Gil, & José Luis Martínez. (2015). Quantitative proteomics unravels that the post-transcriptional regulator Crc modulates the generation of vesicles and secreted virulence determinants of Pseudomonas aeruginosa. Journal of Proteomics. 127(Pt B). 352–364. 24 indexed citations

16.

Reales‐Calderón, Jose Antonio, Fernando Corona, Lucía Monteoliva, Concha Gil, & José Luis Martínez. (2015). Quantitative proteomics unravels that the post-transcriptional regulator Crc modulates the generation of vesicles and secreted virulence determinants of Pseudomonas aeruginosa. Data in Brief. 4. 450–453. 22 indexed citations

17.

Bernardini, Alejandra, Fernando Corona, Ricardo Dias, María Blanca Sánchez, & José Luis Martínez. (2015). The inactivation of RNase G reduces the Stenotrophomonas maltophilia susceptibility to quinolones by triggering the heat shock response. Frontiers in Microbiology. 6. 1068–1068. 13 indexed citations

18.

Valencia, Marcelo, et al.. (2014). Remisión sintomática y recuperación funcional en pacientes que padecen esquizofrenia. Salud Mental. 37(1). 59–59. 13 indexed citations

19.

Olivares‐Pacheco, Jorge, et al.. (2013). The intrinsic resistome of bacterial pathogens. Frontiers in Microbiology. 4. 103–103. 131 indexed citations

20.

Corona, Fernando & José Luis Martínez. (2013). Phenotypic Resistance to Antibiotics. Antibiotics. 2(2). 237–255. 148 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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