Lajos László
Impact in
- Neurology top 1%
- Neurological diseases and metabolism
- Parkinson's Disease Mechanisms and Treatments
- Developmental Neuroscience top 5%
Papers in
-
- Prion Diseases and Protein Misfolding 23
- Ubiquitin and proteasome pathways 10
- Neurology 20
- Neurological diseases and metabolism 19
- Co-authors
- R. John Mayer (20 shared papers)Michael Landon (14 shared papers)James Lowe (12 shared papers)Gábor G. Kovács (18 shared papers)Kinga Molnár (17 shared papers)Herbert Budka (11 shared papers)James Hope (5 shared papers)F J Doherty (6 shared papers)
- Journals
- Neurobiology of Disease (5 papers)The Journal of Pathology (4 papers)FEBS Letters (4 papers)Acta Neuropathologica (4 papers)Experimental Cell Research (4 papers)
- Partner nations
- HungaryUnited KingdomAustria
In The Last Decade
Lajos László
72 papers receiving 2.6k citations
Peers
Comparison fields: 5 of 101
- Neurology 705
- Developmental Neuroscience 116
- Molecular Biology 1.8k
- Neurology 386
- Physiology 633
Countries citing papers authored by Lajos László
This map shows the geographic impact of Lajos László'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 Lajos László with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lajos László more than expected).
Fields of papers citing papers by Lajos László
This network shows the impact of papers produced by Lajos László. 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 Lajos László. The network helps show where Lajos László may publish in the future.
Co-authors
The 25 scholars most cited alongside Lajos László, 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 74 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2004 | 261 | |
| 2 | 1997 | 235 | |
| 3 | 2017 | 166 | |
| 4 | 1992 | 154 | |
| 5 | 1995 | 140 | |
| 6 | 2004 | 128 | |
| 7 | 1991 | 115 | |
| 8 | 2014 | 108 | |
| 9 | 2017 | 89 | |
| 10 | 2002 | 86 | |
| 11 | 2010 | 83 | |
| 12 | 1989 | 83 | |
| 13 | 1990 | 76 | |
| 14 | 2011 | 62 | |
| 15 | 2007 | 41 | |
| 16 | 1999 | 40 | |
| 17 | Receptor-like properties of the 26 kDa transmembrane form of TNF. | 2002 | 40 |
| 18 | 1996 | 39 | |
| 19 | 1992 | 37 | |
| 20 | 2000 | 37 |
About Lajos László
Lajos László is a scholar working on Molecular Biology, Neurology, Physiology, Epidemiology and Cell Biology, having authored 74 papers that have together received 2.7k indexed citations. Recurring topics across this work include Prion Diseases and Protein Misfolding (23 papers), Neurological diseases and metabolism (19 papers), Autophagy in Disease and Therapy (15 papers), Ubiquitin and proteasome pathways (10 papers), Alzheimer's disease research and treatments (9 papers), Cellular transport and secretion (8 papers), Endoplasmic Reticulum Stress and Disease (7 papers) and Trace Elements in Health (7 papers). The work is most often cited by research in Neurology (705 citations), Developmental Neuroscience (116 citations), Molecular Biology (1.8k citations), Neurology (386 citations) and Physiology (633 citations). Lajos László has collaborated with scholars based in Hungary, United Kingdom and Austria. Frequent co-authors include R. John Mayer, Michael Landon, James Lowe, Gábor G. Kovács, Kinga Molnár, Herbert Budka, James Hope, F J Doherty, Steffen Biechele and Claudio Monetti. Their work appears in journals such as Neurobiology of Disease, The Journal of Pathology, FEBS Letters, Acta Neuropathologica and Experimental Cell Research.
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.