Pál Gergely
Impact in
- Physiology top 0.5%
- Adenosine and Purinergic Signaling
- Geriatrics and Gerontology top 1%
Papers in
-
- Biochemical and Molecular Research 24
- Protein Kinase Regulation and GTPase Signaling 21
- Glycosylation and Glycoproteins Research 19
-
- Carbohydrate Chemistry and Synthesis 47
- Click Chemistry and Applications 12
- Co-authors
- László Virág (22 shared papers)Tibor Docsa (51 shared papers)László Somsák (44 shared papers)Csaba Szabó (11 shared papers)Éva Szabó (8 shared papers)Péter Bai (20 shared papers)Ferenc Erdődi (18 shared papers)Edina Bakondi (10 shared papers)
- Journals
- Carbohydrate Research (11 papers)Bioorganic & Medicinal Chemistry (11 papers)FEBS Letters (7 papers)PLoS ONE (4 papers)Biochemical and Biophysical Research Communications (4 papers)
- Partner nations
- HungaryUnited StatesFrance
In The Last Decade
Pál Gergely
172 papers receiving 4.9k citations
Peers
Comparison fields: 5 of 125
- Physiology 379
- Geriatrics and Gerontology 181
- Organic Chemistry 1.4k
- Molecular Biology 2.5k
- Rheumatology 499
Countries citing papers authored by Pál Gergely
This map shows the geographic impact of Pál Gergely'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 Pál Gergely with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pál Gergely more than expected).
Fields of papers citing papers by Pál Gergely
This network shows the impact of papers produced by Pál Gergely. 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 Pál Gergely. The network helps show where Pál Gergely may publish in the future.
Co-authors
The 25 scholars most cited alongside Pál Gergely, 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 174 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2003 | 391 | |
| 2 | 2011 | 212 | |
| 3 | 2007 | 174 | |
| 4 | 2003 | 166 | |
| 5 | 2001 | 129 | |
| 6 | 1993 | 99 | |
| 7 | 2011 | 89 | |
| 8 | 2005 | 89 | |
| 9 | 2009 | 88 | |
| 10 | 2013 | 84 | |
| 11 | 2002 | 79 | |
| 12 | 2002 | 76 | |
| 13 | 2005 | 76 | |
| 14 | 2009 | 73 | |
| 15 | 2012 | 72 | |
| 16 | 2000 | 70 | |
| 17 | 1999 | 69 | |
| 18 | 2005 | 69 | |
| 19 | 2015 | 65 | |
| 20 | 1984 | 62 |
About Pál Gergely
Pál Gergely is a scholar working on Molecular Biology, Organic Chemistry, Rheumatology, Cell Biology and Oncology, having authored 174 papers that have together received 5.0k indexed citations. Recurring topics across this work include Carbohydrate Chemistry and Synthesis (47 papers), Glycogen Storage Diseases and Myoclonus (32 papers), Biochemical and Molecular Research (24 papers), Protein Kinase Regulation and GTPase Signaling (21 papers), Glycosylation and Glycoproteins Research (19 papers), PARP inhibition in cancer therapy (18 papers), Click Chemistry and Applications (12 papers) and Pancreatic function and diabetes (10 papers). The work is most often cited by research in Physiology (379 citations), Geriatrics and Gerontology (181 citations), Organic Chemistry (1.4k citations), Molecular Biology (2.5k citations) and Rheumatology (499 citations). Pál Gergely has collaborated with scholars based in Hungary, United States and France. Frequent co-authors include László Virág, Tibor Docsa, László Somsák, Csaba Szabó, Éva Szabó, Péter Bai, Ferenc Erdődi, Edina Bakondi, Éva Bokor and Béla Tóth. Their work appears in journals such as Carbohydrate Research, Bioorganic & Medicinal Chemistry, FEBS Letters, PLoS ONE and Biochemical and Biophysical Research Communications.
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.