Gérard Cabello
Impact in
-
- Thyroid Disorders and Treatments
- Growth Hormone and Insulin-like Growth Factors
- Physiology top 5%
- Adipose Tissue and Metabolism
Papers in
-
- Mitochondrial Function and Pathology 17
- Muscle Physiology and Disorders 13
- RNA Research and Splicing 5
- Peroxisome Proliferator-Activated Receptors 5
- Retinoids in leukemia and cellular processes 3
- Physiology 16
- Adipose Tissue and Metabolism 15
- Co-authors
- François Casas (29 shared papers)Chantal Wrutniak‐Cabello (25 shared papers)Chantal Wrutniak (12 shared papers)Isabelle Cassar‐Malek (10 shared papers)Pierrick Rochard (9 shared papers)Laurence Pessemesse (17 shared papers)Anne Rodier (4 shared papers)Sophie Marchal-Victorion (3 shared papers)
In The Last Decade
Gérard Cabello
44 papers receiving 2.1k citations
Peers
Comparison fields: 5 of 96
- Endocrinology, Diabetes and Metabolism 427
- Physiology 563
- Molecular Biology 1.5k
- Aging 35
- Biochemistry 107
Countries citing papers authored by Gérard Cabello
This map shows the geographic impact of Gérard Cabello'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 Gérard Cabello with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gérard Cabello more than expected).
Fields of papers citing papers by Gérard Cabello
This network shows the impact of papers produced by Gérard Cabello. 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 Gérard Cabello. The network helps show where Gérard Cabello may publish in the future.
Co-authors
The 25 scholars most cited alongside Gérard Cabello, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2003 | 270 | |
| 2 | 2000 | 178 | |
| 3 | 1999 | 174 | |
| 4 | 1995 | 167 | |
| 5 | 2006 | 153 | |
| 6 | 2012 | 98 | |
| 7 | 2003 | 72 | |
| 8 | 2013 | 72 | |
| 9 | 2005 | 70 | |
| 10 | 2000 | 53 | |
| 11 | 2005 | 52 | |
| 12 | 2009 | 49 | |
| 13 | 2008 | 49 | |
| 14 | 1999 | 46 | |
| 15 | 2007 | 46 | |
| 16 | 2011 | 43 | |
| 17 | 2011 | 42 | |
| 18 | 2013 | 42 | |
| 19 | 1995 | 37 | |
| 20 | 2011 | 36 |
About Gérard Cabello
Gérard Cabello is a scholar working on Molecular Biology, Physiology, Endocrinology, Diabetes and Metabolism, Genetics and Cancer Research, having authored 45 papers that have together received 2.2k indexed citations. Recurring topics across this work include Mitochondrial Function and Pathology (17 papers), Adipose Tissue and Metabolism (15 papers), Muscle Physiology and Disorders (13 papers), RNA Research and Splicing (5 papers), Peroxisome Proliferator-Activated Receptors (5 papers), Thyroid Disorders and Treatments (4 papers), Cancer, Hypoxia, and Metabolism (4 papers) and Retinoids in leukemia and cellular processes (3 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (427 citations), Physiology (563 citations), Molecular Biology (1.5k citations), Aging (35 citations) and Biochemistry (107 citations). Gérard Cabello has collaborated with scholars based in France, Morocco and Belgium. Frequent co-authors include François Casas, Chantal Wrutniak‐Cabello, Chantal Wrutniak, Isabelle Cassar‐Malek, Pierrick Rochard, Laurence Pessemesse, Anne Rodier, Sophie Marchal-Victorion, Stéphanie Grandemange and Pascal Seyer. Their work appears in journals such as PLoS ONE, Experimental Cell Research, FEBS Letters, The FASEB Journal and Journal of Biological Chemistry.
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.