J Wiegand
Impact in
- Hematology top 5%
- Iron Metabolism and Disorders
- Multiple Myeloma Research and Treatments
- Genetics top 5%
- Hemoglobinopathies and Related Disorders
Papers in
- Oncology 10
- Peptidase Inhibition and Analysis 4
- Drug Transport and Resistance Mechanisms 4
- Lung Cancer Research Studies 1
- Pancreatic and Hepatic Oncology Research 1
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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)Guangrong Zheng (6 shared papers)Daohong Zhou (6 shared papers)W. King (3 shared papers)Vivekananda Budamagunta (5 shared papers)Dinesh Thummuri (4 shared papers)
- Journals
- Blood (6 papers)Drug Metabolism and Disposition (3 papers)Cancer Gene Therapy (1 paper)Journal of Hematology & Oncology (1 paper)Journal of Veterinary Pharmacology and Therapeutics (1 paper)
- Partner nations
- United StatesGermanyRussia
In The Last Decade
J Wiegand
18 papers receiving 492 citations
Peers
Comparison fields: 5 of 73
- Hematology 169
- Genetics 150
- Equine 19
- Oncology 142
- Nutrition and Dietetics 54
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 | 97 | |
| 2 | 1992 | 72 | |
| 3 | 2021 | 58 | |
| 4 | 1993 | 47 | |
| 5 | 1993 | 45 | |
| 6 | 1969 | 42 | |
| 7 | 2023 | 31 | |
| 8 | 1992 | 31 | |
| 9 | 1995 | 22 | |
| 10 | 2024 | 16 | |
| 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 | 1992 | 3 | |
| 17 | 1996 | 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 508 indexed citations. Recurring topics across this work include Hemoglobinopathies and Related Disorders (6 papers), Iron Metabolism and Disorders (6 papers), Protein Degradation and Inhibitors (4 papers), Peptidase Inhibition and Analysis (4 papers), Drug Transport and Resistance Mechanisms (4 papers), Multiple Myeloma Research and Treatments (3 papers), Lung Cancer Research Studies (1 paper) and Pancreatic and Hepatic Oncology Research (1 paper). The work is most often cited by research in Hematology (169 citations), Genetics (150 citations), Equine (19 citations), Oncology (142 citations) and Nutrition and Dietetics (54 citations). J Wiegand has collaborated with scholars based in United States, Germany and Russia. Frequent co-authors include G Luchetta, Peiyi Zhang, Sajid Khan, Guangrong Zheng, Daohong Zhou, W. King, Vivekananda Budamagunta, Dinesh Thummuri, Xuan Zhang and H. Kühn. Their work appears in journals such as Blood, Drug Metabolism and Disposition, Cancer Gene Therapy, Journal of Hematology & Oncology 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.