María G. Barderas

3.1k citations
123 papers · 2.5k indexed · h-index 30

María G. Barderas

120 papers receiving 2.4k citations

Peers

María G. Barderas
Comparison fields: 5 of 111
  • Nephrology 270
  • Cardiology and Cardiovascular Medicine 627
  • Spectroscopy 450
  • Cancer Research 356
  • Molecular Biology 1.1k
Replace Eiji Uchida with:
Eiji Uchida Japan
Takahiro Doi Japan
David E. Bowyer United Kingdom
Javier Corral Spain
Justyna Siwy Germany
Thekkelnaycke M. Rajendiran United States
Pierre Lescuyer Switzerland
Hirofumi Uto Japan
Yusuke Higuchi Japan
Jinping Li China
María G. Barderas relative to Eiji Uchida Japan Eiji Uchida's profile →
Citations per field
00.5×10×14.5×
Eiji Uchida · 1×
Citations per year

Countries citing papers authored by María G. Barderas

Since Specialization
Citations

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

Fields of papers citing papers by María G. Barderas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by María G. Barderas. 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 María G. Barderas. The network helps show where María G. Barderas may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20250
3 20244
4 20241
5 20242
6 20242
7 202412
8 20234
9 20234
10 202247
11 202110
12 20215
13 202112
14 20209
15 20202
16 202013
17 20194
18 201811
19 201321
20 20129

About María G. Barderas

María G. Barderas is a scholar working on Spectroscopy, Cardiology and Cardiovascular Medicine and Nephrology, having authored 123 papers that have together received 2.5k indexed citations. Recurring topics across this work include Advanced Proteomics Techniques and Applications (33 papers), Cardiac Valve Diseases and Treatments (19 papers), Protease and Inhibitor Mechanisms (18 papers), Metabolomics and Mass Spectrometry Studies (17 papers), Blood Pressure and Hypertension Studies (13 papers), Lipoproteins and Cardiovascular Health (12 papers), Infective Endocarditis Diagnosis and Management (11 papers) and Adipokines, Inflammation, and Metabolic Diseases (10 papers). The work is most often cited by research in Nephrology (270 citations), Cardiology and Cardiovascular Medicine (627 citations) and Spectroscopy (450 citations). María G. Barderas has collaborated with scholars based in Spain, United States and United Kingdom. Frequent co-authors include Fernando Vivanco, Gloria Álvarez‐Llamas, Fernando de la Cuesta, Luis Rodrı́guez Padial, Verónica M. Dardé, Irene Zubiri, María Posada-Ayala, Félix Gil-Dones, Marta Martin‐Lorenzo and Luís M. Ruilope. Their work appears in journals such as Antioxidants, Journal of Proteomics, Journal of Proteome Research, Translational research and Scientific Reports.

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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