Raquel Cano

26 papers receiving 643 citations

Peers

Raquel Cano
Comparison fields: 5 of 89
  • Genetics 187
  • Cellular and Molecular Neuroscience 132
  • Cell Biology 80
  • Molecular Biology 320
  • Health, Toxicology and Mutagenesis 52
Replace Kon‐Ping Lin with:
Kon‐Ping Lin Taiwan
Ya Ou China
Graciela L. Mazzone Italy
Alireza Abdanipour Iran
Hirokazu Matsuzaki Japan
Samuel Shribman United Kingdom
Luís Gustavo Oliveira de Sousa Brazil
Vincenzo Macaione Italy
Yasuko Kozaki Japan
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Citations per field
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Citations per year

Countries citing papers authored by Raquel Cano

Since Specialization
Citations

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

Fields of papers citing papers by Raquel Cano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010144
2 2011100
3 202178
4 201173
5 200751
6 200728
7 201027
8 201019
9 200816
10 201215
11 201715
12 202114
13 200814
14 201213
15 201910
16 20089
17 20169
18
Insulinorresistencia e hiperinsulinemia como factores de riesgo para enfermedad cardiovascular
20076
19 20104
20
Aspectos Psicológicos y Personales en el manejo de la Diabetes Mellitus
20043

About Raquel Cano

Raquel Cano is a scholar working on Molecular Biology, Physiology, Endocrinology, Diabetes and Metabolism, Surgery and Genetics, having authored 31 papers that have together received 660 indexed citations. Recurring topics across this work include Health and Lifestyle Studies (5 papers), Cellular transport and secretion (5 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (5 papers), Adipose Tissue and Metabolism (5 papers), Neuroscience and Neuropharmacology Research (4 papers), Neurogenetic and Muscular Disorders Research (4 papers), Lipid Membrane Structure and Behavior (4 papers) and Adipokines, Inflammation, and Metabolic Diseases (4 papers). The work is most often cited by research in Genetics (187 citations), Cellular and Molecular Neuroscience (132 citations), Cell Biology (80 citations), Molecular Biology (320 citations) and Health, Toxicology and Mutagenesis (52 citations). Raquel Cano has collaborated with scholars based in Venezuela, Spain and United States. Frequent co-authors include Lucı́a Tabares, Rocío Ruiz, Laura Torres‐Benito, Juan José Casañas, William J. Betz, Valmore Bermúdez, Michael A. Gaffield, Clímaco Cano, Freddy Contreras and Maricarmen Chacín. Their work appears in journals such as American Journal of Therapeutics, Journal of Neuroscience, Human Molecular Genetics, Molecular Neurobiology and International Journal of Molecular Sciences.

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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