Fernando Garcés
Impact in
- Virology top 1%
- HIV Research and Treatment
-
- Monoclonal and Polyclonal Antibodies Research
Papers in
-
- Glycosylation and Glycoproteins Research 8
- Protein purification and stability 4
- Porphyrin Metabolism and Disorders 3
-
- Monoclonal and Polyclonal Antibodies Research 9
- Co-authors
- Ian A. Wilson (8 shared papers)Leopold Kong (5 shared papers)Andrew B. Ward (6 shared papers)Dennis R. Burton (5 shared papers)Yuanzi Hua (3 shared papers)Robyn L. Stanfield (3 shared papers)John P. Moore (2 shared papers)Natalia de Val (4 shared papers)
- Journals
- Cell Reports (4 papers)Immunity (2 papers)mAbs (2 papers)iScience (1 paper)Journal of Bacteriology (1 paper)
- Partner nations
- United StatesSpainUnited Kingdom
In The Last Decade
Fernando Garcés
32 papers receiving 1000 citations
Peers
Comparison fields: 5 of 105
- Virology 457
- Radiology, Nuclear Medicine and Imaging 284
- Immunology 242
- Molecular Biology 572
- Infectious Diseases 141
Countries citing papers authored by Fernando Garcés
This map shows the geographic impact of Fernando Garcés'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 Fernando Garcés with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fernando Garcés more than expected).
Fields of papers citing papers by Fernando Garcés
This network shows the impact of papers produced by Fernando Garcés. 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 Fernando Garcés. The network helps show where Fernando Garcés may publish in the future.
Co-authors
The 25 scholars most cited alongside Fernando Garcés, 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 33 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 138 | |
| 2 | 2014 | 133 | |
| 3 | 2016 | 67 | |
| 4 | 2019 | 63 | |
| 5 | 2014 | 63 | |
| 6 | 2017 | 62 | |
| 7 | 2015 | 57 | |
| 8 | 1982 | 47 | |
| 9 | 2017 | 42 | |
| 10 | 2020 | 39 | |
| 11 | 2011 | 31 | |
| 12 | 2008 | 27 | |
| 13 | 2023 | 25 | |
| 14 | 2010 | 24 | |
| 15 | 2007 | 23 | |
| 16 | 2021 | 21 | |
| 17 | 2008 | 20 | |
| 18 | 2014 | 19 | |
| 19 | 2019 | 17 | |
| 20 | 2020 | 17 |
About Fernando Garcés
Fernando Garcés is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging, Virology, Nutrition and Dietetics and Immunology, having authored 33 papers that have together received 1.0k indexed citations. Recurring topics across this work include Monoclonal and Polyclonal Antibodies Research (9 papers), HIV Research and Treatment (8 papers), Glycosylation and Glycoproteins Research (8 papers), Enzyme Structure and Function (5 papers), Vitamin C and Antioxidants Research (4 papers), Protein purification and stability (4 papers), Bacterial Genetics and Biotechnology (3 papers) and Porphyrin Metabolism and Disorders (3 papers). The work is most often cited by research in Virology (457 citations), Radiology, Nuclear Medicine and Imaging (284 citations), Immunology (242 citations), Molecular Biology (572 citations) and Infectious Diseases (141 citations). Fernando Garcés has collaborated with scholars based in United States, Spain and United Kingdom. Frequent co-authors include Ian A. Wilson, Leopold Kong, Andrew B. Ward, Dennis R. Burton, Yuanzi Hua, Robyn L. Stanfield, John P. Moore, Natalia de Val, Devin Sok and Alba Torrents de la Peña. Their work appears in journals such as Cell Reports, Immunity, mAbs, iScience and Journal of Bacteriology.
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.