Richard C. Scarpa
- Physiology top 0.5%
- Nutrition and Dietetics top 0.5%
- Molecular Biology top 10%
- Pharmacology top 2%
- Computational Theory and Mathematics top 1%
- Co-authors
- Rudolph E. TanziCraig AtwoodAshley I. BushXudong HuangRobert D. MoirMariana A. HartshornLee E. GoldsteinJames Lim
- Topics
- Alzheimer's disease research and treatments (5 papers)Trace Elements in Health (3 papers)Computational Drug Discovery Methods (2 papers)
- Partner nations
- United StatesGermanyAustralia
In The Last Decade
Richard C. Scarpa
10 papers receiving 3.2k citations
Hit Papers
Peers
Comparison fields: 5 of 106
- Physiology 2.4k
- Nutrition and Dietetics 1.2k
- Molecular Biology 1.0k
- Pharmacology 542
- Computational Theory and Mathematics 423
Countries citing papers authored by Richard C. Scarpa
This map shows the geographic impact of Richard C. Scarpa'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 Richard C. Scarpa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Richard C. Scarpa more than expected).
Fields of papers citing papers by Richard C. Scarpa
This network shows the impact of papers produced by Richard C. Scarpa. 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 Richard C. Scarpa. The network helps show where Richard C. Scarpa may publish in the future.
Co-authorship network of co-authors of Richard C. Scarpa
This figure shows the co-authorship network connecting the top 25 collaborators of Richard C. Scarpa. A scholar is included among the top collaborators of Richard C. Scarpa based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Richard C. Scarpa. Richard C. Scarpa is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 16 | |
| 2 | 14 | |
| 3 | 13 | |
| 4 | 6 | |
| 5 | Characterization of Copper Interactions with Alzheimer Amyloid β Peptidesbreakdown → | 545 |
| 6 | 166 | |
| 7 | The Aβ Peptide of Alzheimer's Disease Directly Produces Hydrogen Peroxide through Metal Ion Reductionbreakdown → | 942 |
| 8 | Cu(II) Potentiation of Alzheimer Aβ Neurotoxicitybreakdown → | 644 |
| 9 | Cu (II ) Potentiation of Alzheimer Ab Neurotoxicity | 27 |
| 10 | Dramatic Aggregation of Alzheimer Aβ by Cu(II) Is Induced by Conditions Representing Physiological Acidosisbreakdown → | 880 |
| 11 | Determinants of Non-Timber Values in Wisconsin Northern Hardwoods | 0 |
About Richard C. Scarpa
Richard C. Scarpa is a scholar working on Biological Psychiatry, Geriatrics and Gerontology and Physiology, having authored 11 papers that have together received 3.3k indexed citations. Recurring topics across this work include Alzheimer's disease research and treatments (5 papers), Trace Elements in Health (3 papers) and Computational Drug Discovery Methods (2 papers). The work is most often cited by research in Physiology (2.4k citations), Biological Psychiatry (197 citations) and Nutrition and Dietetics (1.2k citations). Richard C. Scarpa has collaborated with scholars based in United States, Germany and Australia. Frequent co-authors include Rudolph E. Tanzi, Craig Atwood, Ashley I. Bush, Xudong Huang, Robert D. Moir, Mariana A. Hartshorn, Lee E. Goldstein, James Lim, Math P. Cuajungco and Gerd Multhaup. Their work appears in journals such as Journal of Biological Chemistry, Biochemistry and Journal of Neurochemistry.
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.