E. Vila

18 papers receiving 374 citations

Peers

E. Vila
Comparison fields: 5 of 86
  • Computational Theory and Mathematics 108
  • Biochemistry 31
  • Physiology 107
  • Pharmacology 26
  • Molecular Biology 172
Replace Toshiji Igarashi with:
Toshiji Igarashi Japan
Alfred Binggeli Switzerland
Uyen Thao Nguyen United States
Mahmoud H. Elbatreek Egypt
Dennis M. Gross United States
Declan Flynn United States
Daniel Sauter Denmark
Gong‐Hua Li China
H. Roger Brown United States
E. Vila relative to Toshiji Igarashi Japan Toshiji Igarashi's profile →
Citations per field
00.5×11.7×
Toshiji Igarashi · 1×
Citations per year

Countries citing papers authored by E. Vila

Since Specialization
Citations

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

Fields of papers citing papers by E. Vila

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by E. Vila. 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 E. Vila. The network helps show where E. Vila may publish in the future.

Co-authors

The 25 scholars most cited alongside E. Vila, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with E. Vila Line = papers co-authored together E. Vila links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 2017155
2 201355
3 200527
4 201126
5 201320
6 199117
7 199916
8 199515
9 199212
10 20238
11 19907
12 19906
13 20006
14 19864
15 20162
16 20231
17
3-dimensional analysis of vascular structure, function & receptor distribution using confocal laser scanning microscopy
20001
18 19821
19 20250
20 20140

About E. Vila

E. Vila is a scholar working on Physiology, Molecular Biology, Cellular and Molecular Neuroscience, Cardiology and Cardiovascular Medicine and Computational Theory and Mathematics, having authored 20 papers that have together received 379 indexed citations. Recurring topics across this work include Nitric Oxide and Endothelin Effects (6 papers), Receptor Mechanisms and Signaling (5 papers), Neuropeptides and Animal Physiology (4 papers), Computational Drug Discovery Methods (3 papers), Pain Mechanisms and Treatments (3 papers), Neuroscience and Neuropharmacology Research (3 papers), Renin-Angiotensin System Studies (2 papers) and Hormonal Regulation and Hypertension (2 papers). The work is most often cited by research in Computational Theory and Mathematics (108 citations), Biochemistry (31 citations), Physiology (107 citations), Pharmacology (26 citations) and Molecular Biology (172 citations). E. Vila has collaborated with scholars based in Spain, United Kingdom and Sweden. Frequent co-authors include Luca Pinzi, Noé Sturm, Ola Engkvist, Hongming Chen, Giulio Rastelli, Annachiara Tinivella, Jesús Giraldo, I. Mhairi Macrae, Pilar D’Ocón and Ana M. Briones. Their work appears in journals such as British Journal of Pharmacology, Journal of Pharmacy and Pharmacology, Acta Physiologica, Nutrition Metabolism and Cardiovascular Diseases and Journal of Pharmacology and Experimental Therapeutics.

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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