J Wiegand
Impact in
- Hematology top 5%
- Iron Metabolism and Disorders
- Multiple Myeloma Research and Treatments
- Equine top 5%
Papers in
- Oncology 11
- Peptidase Inhibition and Analysis 4
- Drug Transport and Resistance Mechanisms 4
- CAR-T cell therapy research 2
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- Iron Metabolism and Disorders 6
- Multiple Myeloma Research and Treatments 3
- Co-authors
- G Luchetta (6 shared papers)Peiyi Zhang (5 shared papers)Sajid Khan (6 shared papers)Daohong Zhou (6 shared papers)W. King (3 shared papers)Guangrong Zheng (6 shared papers)Xuan Zhang (4 shared papers)Vivekananda Budamagunta (5 shared papers)
- Journals
- Blood (6 papers)Drug Metabolism and Disposition (3 papers)Molecular Cancer Therapeutics (1 paper)Cell Death Discovery (1 paper)Journal of Veterinary Pharmacology and Therapeutics (1 paper)
- Partner nations
- United StatesGermanyRussia
In The Last Decade
J Wiegand
18 papers receiving 476 citations
Peers
Comparison fields: 5 of 74
- Hematology 180
- Equine 24
- Genetics 150
- Oncology 146
- Nutrition and Dietetics 55
Countries citing papers authored by J Wiegand
This map shows the geographic impact of J Wiegand'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 J Wiegand with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites J Wiegand more than expected).
Fields of papers citing papers by J Wiegand
This network shows the impact of papers produced by J Wiegand. 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 J Wiegand. The network helps show where J Wiegand may publish in the future.
Co-authors
The 25 scholars most cited alongside J Wiegand, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 92 | |
| 2 | 1992 | 72 | |
| 3 | 2021 | 51 | |
| 4 | 1993 | 47 | |
| 5 | 1993 | 45 | |
| 6 | 1969 | 42 | |
| 7 | 2023 | 31 | |
| 8 | 1992 | 30 | |
| 9 | 1995 | 22 | |
| 10 | 2024 | 14 | |
| 11 | 1993 | 11 | |
| 12 | 2007 | 10 | |
| 13 | Metabolism and pharmacokinetics of N1,N11-diethylnorspermine in a Cebus apella primate model. | 2000 | 8 |
| 14 | 1999 | 7 | |
| 15 | 2019 | 4 | |
| 16 | 1996 | 3 | |
| 17 | 1992 | 3 | |
| 18 | 2022 | 1 |
About J Wiegand
J Wiegand is a scholar working on Oncology, Hematology, Molecular Biology, Genetics and Pharmacology, having authored 18 papers that have together received 493 indexed citations. Recurring topics across this work include Hemoglobinopathies and Related Disorders (6 papers), Iron Metabolism and Disorders (6 papers), Peptidase Inhibition and Analysis (4 papers), Protein Degradation and Inhibitors (4 papers), Drug Transport and Resistance Mechanisms (4 papers), Multiple Myeloma Research and Treatments (3 papers), CAR-T cell therapy research (2 papers) and Inflammatory mediators and NSAID effects (1 paper). The work is most often cited by research in Hematology (180 citations), Equine (24 citations), Genetics (150 citations), Oncology (146 citations) and Nutrition and Dietetics (55 citations). J Wiegand has collaborated with scholars based in United States, Germany and Russia. Frequent co-authors include G Luchetta, Peiyi Zhang, Sajid Khan, Daohong Zhou, W. King, Guangrong Zheng, Xuan Zhang, Vivekananda Budamagunta, Dinesh Thummuri and Horst‐Dieter Försterling. Their work appears in journals such as Blood, Drug Metabolism and Disposition, Molecular Cancer Therapeutics, Cell Death Discovery and Journal of Veterinary Pharmacology and Therapeutics.
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.