J.M. Ferrero

2.1k total citations
114 papers, 1.2k citations indexed

About

J.M. Ferrero is a scholar working on Cardiology and Cardiovascular Medicine, Molecular Biology and Cellular and Molecular Neuroscience. According to data from OpenAlex, J.M. Ferrero has authored 114 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 98 papers in Cardiology and Cardiovascular Medicine, 63 papers in Molecular Biology and 22 papers in Cellular and Molecular Neuroscience. Recurrent topics in J.M. Ferrero's work include Cardiac electrophysiology and arrhythmias (92 papers), Ion channel regulation and function (59 papers) and Neuroscience and Neural Engineering (17 papers). J.M. Ferrero is often cited by papers focused on Cardiac electrophysiology and arrhythmias (92 papers), Ion channel regulation and function (59 papers) and Neuroscience and Neural Engineering (17 papers). J.M. Ferrero collaborates with scholars based in Spain, United States and Italy. J.M. Ferrero's co-authors include Javier Sáiz, Beatriz Trénor, Nitish V. Thakor, Rafael Sebastián, Lucía Romero, Blanca Rodríguez, Juan F. Gómez, José F. Rodrı́guez, Elvio Heidenreich and M. Doblaré and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Circulation Research.

In The Last Decade

J.M. Ferrero

102 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
J.M. Ferrero Spain 19 982 499 162 113 105 114 1.2k
Steven Girouard United States 15 1.5k 1.5× 737 1.5× 240 1.5× 65 0.6× 57 0.5× 27 1.7k
Takashi Ashihara Japan 22 1.0k 1.0× 472 0.9× 205 1.3× 32 0.3× 103 1.0× 77 1.3k
Emilio Macchi Italy 23 950 1.0× 319 0.6× 125 0.8× 79 0.7× 107 1.0× 56 1.3k
M E Cain United States 15 1.7k 1.7× 306 0.6× 80 0.5× 70 0.6× 63 0.6× 22 1.9k
Rafael J. Ramírez United States 22 2.2k 2.2× 1.0k 2.1× 384 2.4× 59 0.5× 71 0.7× 36 2.5k
André C. Linnenbank Netherlands 22 2.1k 2.1× 722 1.4× 122 0.8× 57 0.5× 77 0.7× 53 2.3k
Dennis L. Rollins United States 20 1.1k 1.2× 241 0.5× 261 1.6× 57 0.5× 68 0.6× 58 1.3k
Mark Potse Netherlands 25 2.1k 2.1× 518 1.0× 141 0.9× 92 0.8× 164 1.6× 105 2.3k
Chris P. Bradley New Zealand 18 808 0.8× 290 0.6× 87 0.5× 88 0.8× 197 1.9× 44 1.2k
N.D. Danieley United States 12 967 1.0× 230 0.5× 220 1.4× 47 0.4× 40 0.4× 15 1.1k

Countries citing papers authored by J.M. Ferrero

Since Specialization
Citations

This map shows the geographic impact of J.M. Ferrero'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 J.M. Ferrero with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites J.M. Ferrero more than expected).

Fields of papers citing papers by J.M. Ferrero

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by J.M. Ferrero. 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 J.M. Ferrero. The network helps show where J.M. Ferrero may publish in the future.

Co-authorship network of co-authors of J.M. Ferrero

This figure shows the co-authorship network connecting the top 25 collaborators of J.M. Ferrero. A scholar is included among the top collaborators of J.M. Ferrero 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 J.M. Ferrero. J.M. Ferrero is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Ferrero, J.M., et al.. (2024). The Role of Population Size in Computational Assessment of Pharmacological Cardiotoxicity. Computing in cardiology. 51.
2.
Ferrero, J.M., et al.. (2023). Towards the Development of an in Silico Model for the Zebrafish Action Potential. Computing in cardiology.
3.
4.
Ferrero, J.M., et al.. (2019). Why Does Extracellular Potassium Rise in Acute Ischemia? Insights from Computational Simulations. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 1 indexed citations
5.
Ferrero, J.M., et al.. (2015). GPU accelerated solver for nonlinear reaction–diffusion systems. Application to the electrophysiology problem. Computer Physics Communications. 196. 280–289. 20 indexed citations
6.
Martínez-Mateu, Laura, Lucía Romero, Catalina Tobón, et al.. (2014). Accurate characterization of rotor activity during atrial fibrillation depends on the properties of the multi-electrode grid. Scopus. 41. 757–760. 1 indexed citations
7.
Trénor, Beatriz, Juan F. Gómez, Sridharan Rajamani, et al.. (2012). Simulation and Mechanistic Investigation of the Arrhythmogenic Role of the Late Sodium Current in Human Heart Failure. PLoS ONE. 7(3). e32659–e32659. 65 indexed citations
8.
Ferrero, J.M., et al.. (2011). COMPORTAMIENTO ANTIARRÍTMICO DE LA HIPOXIA EN SIMULACIONES DE PARED TRANSMURAL CARDÍACA EN PRESENCIA DE ISQUEMIA SUB-EPICÁRDICA. SHILAP Revista de lepidopterología. 2 indexed citations
9.
Romero, Lucía, et al.. (2011). Systematic characterization of the ionic basis of rabbit cellular electrophysiology using two ventricular models. Progress in Biophysics and Molecular Biology. 107(1). 60–73. 29 indexed citations
10.
Tobón, Catalina, et al.. (2010). A biophysical model of atrial fibrillation to simulate the Maze III ablation pattern. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 621–624. 3 indexed citations
11.
Trénor, Beatriz, et al.. (2010). Role of the late sodium current in arrhythmias related to low repolarization reserve. Computing in Cardiology. 617–620. 1 indexed citations
12.
Ferrero, J.M., et al.. (2010). M-cell heterogeneity influence in arrhythmic pattern formation in sub-epicardial regional ischemia: A simulation study. Computing in Cardiology. 189–192. 1 indexed citations
13.
Sáiz, Javier, et al.. (2010). Effects of the Antiarrhythmic Drug Dofetilide on Transmural Dispersion of Repolarization in Ventriculum. A Computer Modeling Study. IEEE Transactions on Biomedical Engineering. 58(1). 43–53. 17 indexed citations
14.
Tobón, Catalina, et al.. (2009). Influence of atrial dilatation in the generation of re-entries caused by ectopic activity in the left atrium. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 457–460. 7 indexed citations
15.
Doblaré, M., et al.. (2009). Electrical propagation patterns in a 3D regionally ischemic human heart: A simulation study. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 665–668. 1 indexed citations
16.
Ferrero, J.M., et al.. (2007). Arritmias cardiacas generadas por heterogeneidad electrofisiológica: estudio mediante simulación. Revista Colombiana de Cardiología. 14(4). 185–197. 1 indexed citations
17.
Ferrero, J.M., et al.. (2006). Spectrum estimation and adaptive denoising of eElectrocardiographic signals using Kalman filters. Computing in Cardiology Conference. 925–928. 2 indexed citations
18.
Romero, Lucía, Beatriz Trénor, J.M. Ferrero, et al.. (2006). Safety factor in simulated 2D cardiac tissue. influence of altered membrane excitability. Computing in Cardiology Conference. 217–220. 1 indexed citations
19.
Ferrero, J.M., et al.. (2006). The ECG T-Wave duration as an index of dispersion of ventricular repolarization: Insights from simulations. Computing in Cardiology Conference. 793–796. 5 indexed citations
20.
Sáiz, Javier, et al.. (2000). Ectopic Activity in Ventricular Cells Induced by Early Afterdepolarizations Developed in Purkinje Cells. Annals of Biomedical Engineering. 28(11). 1343–1351. 8 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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