P. Kása
Impact in
-
- Neuroscience and Neuropharmacology Research
- Pharmacology top 0.5%
- Cholinesterase and Neurodegenerative Diseases
Papers in
-
- Neuroscience and Neuropharmacology Research 45
-
- Nicotinic Acetylcholine Receptors Study 17
- Receptor Mechanisms and Signaling 9
- Co-authors
- Károly Gulya (27 shared papers)Zoltán Rakonczay (18 shared papers)Ferenc Joó (20 shared papers)B. Csillik (8 shared papers)Magdolna Pákáski (20 shared papers)Joachim Wolff (20 shared papers)Klára Pintye‐Hódi (29 shared papers)Péter Szerdahelyi (6 shared papers)
- Journals
- Journal of Neurochemistry (14 papers)Brain Research (7 papers)Neuroscience (6 papers)The Journal of Comparative Neurology (4 papers)Acta Histochemica (4 papers)
- Partner nations
- HungaryGermanyUnited States
In The Last Decade
P. Kása
161 papers receiving 3.5k citations
Peers
Comparison fields: 5 of 136
- Cellular and Molecular Neuroscience 1.4k
- Pharmacology 946
- Neurology 400
- Pharmaceutical Science 288
- Biological Psychiatry 105
Countries citing papers authored by P. Kása
This map shows the geographic impact of P. Kása'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 P. Kása with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites P. Kása more than expected).
Fields of papers citing papers by P. Kása
This network shows the impact of papers produced by P. Kása. 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 P. Kása. The network helps show where P. Kása may publish in the future.
Co-authors
The 25 scholars most cited alongside P. Kása, 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 166 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1997 | 364 | |
| 2 | 1986 | 198 | |
| 3 | 2010 | 149 | |
| 4 | 1990 | 112 | |
| 5 | 2000 | 92 | |
| 6 | 1970 | 86 | |
| 7 | 1969 | 84 | |
| 8 | 1968 | 83 | |
| 9 | 2000 | 80 | |
| 10 | 1966 | 77 | |
| 11 | 2009 | 76 | |
| 12 | 1997 | 68 | |
| 13 | 2010 | 67 | |
| 14 | 2008 | 65 | |
| 15 | 1995 | 65 | |
| 16 | 1981 | 59 | |
| 17 | 2011 | 57 | |
| 18 | 2007 | 55 | |
| 19 | 1992 | 52 | |
| 20 | 1963 | 51 |
About P. Kása
P. Kása is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology, Pharmacology, Physiology and Pharmaceutical Science, having authored 166 papers that have together received 3.7k indexed citations. Recurring topics across this work include Neuroscience and Neuropharmacology Research (45 papers), Cholinesterase and Neurodegenerative Diseases (44 papers), Alzheimer's disease research and treatments (29 papers), Drug Solubulity and Delivery Systems (22 papers), Nicotinic Acetylcholine Receptors Study (17 papers), Computational Drug Discovery Methods (10 papers), Memory and Neural Mechanisms (10 papers) and Receptor Mechanisms and Signaling (9 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (1.4k citations), Pharmacology (946 citations), Neurology (400 citations), Pharmaceutical Science (288 citations) and Biological Psychiatry (105 citations). P. Kása has collaborated with scholars based in Hungary, Germany and United States. Frequent co-authors include Károly Gulya, Zoltán Rakonczay, Ferenc Joó, B. Csillik, Magdolna Pákáski, Joachim Wolff, Klára Pintye‐Hódi, Péter Szerdahelyi, Henrietta Papp and Catherine O. Hebb. Their work appears in journals such as Journal of Neurochemistry, Brain Research, Neuroscience, The Journal of Comparative Neurology and Acta Histochemica.
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.