Pedro Bernaola‐Galván
- Molecular Biology top 5%
- Economics and Econometrics top 2%
- Statistical and Nonlinear Physics top 2%
- Artificial Intelligence top 5%
- Organic Chemistry top 10%
- Co-authors
- Pedro CarpenaJosé Luis Tejera OliverRamón Román-RoldánPlamen Ch. IvanovH. Eugene StanleyC. Carnero RuizJeffery A. AguiarIvo Große
- Topics
- Fractal and DNA sequence analysis (26 papers)RNA and protein synthesis mechanisms (26 papers)Machine Learning in Bioinformatics (23 papers)
- Partner nations
- SpainUnited StatesBulgaria
In The Last Decade
Pedro Bernaola‐Galván
53 papers receiving 2.7k citations
Peers
Comparison fields: 5 of 141
- Molecular Biology 1.4k
- Economics and Econometrics 556
- Statistical and Nonlinear Physics 419
- Artificial Intelligence 340
- Organic Chemistry 268
Countries citing papers authored by Pedro Bernaola‐Galván
This map shows the geographic impact of Pedro Bernaola‐Galván'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 Pedro Bernaola‐Galván with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pedro Bernaola‐Galván more than expected).
Fields of papers citing papers by Pedro Bernaola‐Galván
This network shows the impact of papers produced by Pedro Bernaola‐Galván. 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 Pedro Bernaola‐Galván. The network helps show where Pedro Bernaola‐Galván may publish in the future.
Co-authorship network of co-authors of Pedro Bernaola‐Galván
This figure shows the co-authorship network connecting the top 25 collaborators of Pedro Bernaola‐Galván. A scholar is included among the top collaborators of Pedro Bernaola‐Galván 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 Pedro Bernaola‐Galván. Pedro Bernaola‐Galván is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 6 | |
| 3 | 34 | |
| 4 | 13 | |
| 5 | 22 | |
| 6 | 21 | |
| 7 | 18 | |
| 8 | 17 | |
| 9 | 7 | |
| 10 | 38 | |
| 11 | 37 | |
| 12 | 21 | |
| 13 | 61 | |
| 14 | 12 | |
| 15 | 17 | |
| 16 | 74 | |
| 17 | 85 | |
| 18 | 238 | |
| 19 | 106 | |
| 20 | 46 |
About Pedro Bernaola‐Galván
Pedro Bernaola‐Galván is a scholar working on Statistical and Nonlinear Physics, Molecular Biology and Condensed Matter Physics, having authored 53 papers that have together received 2.7k indexed citations. Recurring topics across this work include Fractal and DNA sequence analysis (26 papers), RNA and protein synthesis mechanisms (26 papers) and Machine Learning in Bioinformatics (23 papers). The work is most often cited by research in Filtration and Separation (84 citations), Statistical and Nonlinear Physics (419 citations) and Economics and Econometrics (556 citations). Pedro Bernaola‐Galván has collaborated with scholars based in Spain, United States and Bulgaria. Frequent co-authors include Pedro Carpena, José Luis Tejera Oliver, Ramón Román-Roldán, Plamen Ch. Ivanov, H. Eugene Stanley, C. Carnero Ruiz, Jeffery A. Aguiar, Ivo Große, Michael Hackenberg and Luı́s A. Nunes Amaral. Their work appears in journals such as Physical Review Letters, Nucleic Acids Research and Journal of Neuroscience.
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.