Daniel Casellas

1.5k citations
61 papers · 1.2k · h-index 21

Impact in

Papers in

Daniel Casellas

60 papers receiving 1.2k citations

Peers

Daniel Casellas
Comparison fields: 5 of 94
  • Nephrology 269
  • Cardiology and Cardiovascular Medicine 522
  • Physiology 447
  • Physiology 55
  • Transplantation 30
Replace B. J. Tucker with:
B. J. Tucker United States
En Yin Lai China
Masahito Imanishi Japan
M. Hermle Switzerland
Ulla G. Friis Denmark
L. Gabriel Navar United States
Francisco J. Fenoy Spain
Ruisheng Liu United States
Gabriela A. Eppel Australia
J. C. Romero United States
Daniel Casellas relative to B. J. Tucker United States B. J. Tucker's profile →
Citations per field
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B. J. Tucker · 1×
Citations per year

Countries citing papers authored by Daniel Casellas

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Casellas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Daniel Casellas, 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 Daniel Casellas Line = papers co-authored together Daniel Casellas links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 61 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1984114
2 1990104
3 199977
4 199063
5 198554
6 198152
7
Cyclosporine and the renin-angiotensin system.
199147
8 200543
9 199641
10 199336
11 199335
12 199433
13 199433
14 200224
15 200424
16 199724
17 199421
18
Direct assessment of renal microcirculatory dynamics.
198621
19 199620
20 199020

About Daniel Casellas

Daniel Casellas is a scholar working on Cardiology and Cardiovascular Medicine, Pulmonary and Respiratory Medicine, Physiology, Molecular Biology and Nephrology, having authored 61 papers that have together received 1.2k indexed citations. Recurring topics across this work include Renin-Angiotensin System Studies (19 papers), Nitric Oxide and Endothelin Effects (17 papers), Renal and Vascular Pathologies (13 papers), Hormonal Regulation and Hypertension (7 papers), Chronic Kidney Disease and Diabetes (7 papers), Electrolyte and hormonal disorders (5 papers), Coagulation, Bradykinin, Polyphosphates, and Angioedema (4 papers) and Birth, Development, and Health (4 papers). The work is most often cited by research in Nephrology (269 citations), Cardiology and Cardiovascular Medicine (522 citations), Physiology (447 citations), Physiology (55 citations) and Transplantation (30 citations). Daniel Casellas has collaborated with scholars based in France, United States and Sweden. Frequent co-authors include L. C. Moore, A Mimran, L. Gabriel Navar, Leon C. Moore, Madeleine Dupont, Pamela K. Carmines, Bernard Jover, Adam Rich, L. Gabriel Navar and Frederick J. Kaskel. Their work appears in journals such as American Journal of Physiology-Renal Physiology, Kidney International, Journal of Hypertension, Hypertension and American Journal of Physiology-Regulatory, Integrative and Comparative Physiology.

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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