G Férard
Impact in
- Clinical Biochemistry top 5%
- Metabolism and Genetic Disorders
- Physiology top 10%
- Clinical Laboratory Practices and Quality Control
Papers in
-
- Biomedical Text Mining and Ontologies 6
- Physiology 18
- Clinical Laboratory Practices and Quality Control 13
- Co-authors
- F.-Javier Gella (11 shared papers)Takashi Kanno (10 shared papers)Ferruccio Ceriotti (11 shared papers)Ibrahima Sall (8 shared papers)C. A. Ferrero (9 shared papers)Poul J. Jørgensen (9 shared papers)R Bonora (7 shared papers)Paul Franck (8 shared papers)
In The Last Decade
G Férard
91 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 126
- Clinical Biochemistry 97
- Physiology 264
- Statistics, Probability and Uncertainty 72
- Endocrinology, Diabetes and Metabolism 143
- Nephrology 61
Countries citing papers authored by G Férard
This map shows the geographic impact of G Férard'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 G Férard with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites G Férard more than expected).
Fields of papers citing papers by G Férard
This network shows the impact of papers produced by G Férard. 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 G Férard. The network helps show where G Férard may publish in the future.
Co-authors
The 25 scholars most cited alongside G Férard, 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 99 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2002 | 310 | |
| 2 | 2002 | 120 | |
| 3 | 2002 | 99 | |
| 4 | 2002 | 80 | |
| 5 | 2007 | 79 | |
| 6 | 2002 | 68 | |
| 7 | 2006 | 65 | |
| 8 | 2002 | 47 | |
| 9 | 2002 | 40 | |
| 10 | 2006 | 32 | |
| 11 | 1992 | 31 | |
| 12 | 1996 | 29 | |
| 13 | 1988 | 27 | |
| 14 | 2003 | 27 | |
| 15 | 2002 | 23 | |
| 16 | 1978 | 19 | |
| 17 | 1978 | 17 | |
| 18 | 1997 | 16 | |
| 19 | 2006 | 13 | |
| 20 | 1998 | 13 |
About G Férard
G Férard is a scholar working on Molecular Biology, Physiology, Surgery, Endocrinology, Diabetes and Metabolism and Epidemiology, having authored 99 papers that have together received 1.5k indexed citations. Recurring topics across this work include Clinical Laboratory Practices and Quality Control (13 papers), Diabetes Management and Research (9 papers), Analytical Chemistry and Chromatography (7 papers), Pancreatic function and diabetes (7 papers), Metabolism and Genetic Disorders (7 papers), Diabetes and associated disorders (6 papers), Pesticide Residue Analysis and Safety (6 papers) and Biomedical Text Mining and Ontologies (6 papers). The work is most often cited by research in Clinical Biochemistry (97 citations), Physiology (264 citations), Statistics, Probability and Uncertainty (72 citations), Endocrinology, Diabetes and Metabolism (143 citations) and Nephrology (61 citations). G Férard has collaborated with scholars based in France, Germany and Denmark. Frequent co-authors include F.-Javier Gella, Takashi Kanno, Ferruccio Ceriotti, Ibrahima Sall, C. A. Ferrero, Poul J. Jørgensen, R Bonora, Paul Franck, Wieland Hoelzel and N. Kristiansen. Their work appears in journals such as Clinical Chemistry and Laboratory Medicine (CCLM), Clinica Chimica Acta, Clinical Chemistry, Pure and Applied Chemistry and Clinical Biochemistry.
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.