Gregory M. Podsakoff
- Genetics top 1%
- Molecular Biology top 5%
- Oncology top 5%
- Cardiology and Cardiovascular Medicine top 10%
- Hematology top 5%
- Co-authors
- Gary J. KurtzmanKatherine A. HighPeter ColosiBarry J. ByrnePaul KesslerXiaojuan ChenKah Keng WongSom S. Chatterjee
- Topics
- Virus-based gene therapy research (11 papers)CRISPR and Genetic Engineering (6 papers)Acute Myeloid Leukemia Research (4 papers)
- Cited by
- GeneticsMolecular BiologyOncology
- Partner nations
- United StatesTunisiaFrance
In The Last Decade
Gregory M. Podsakoff
19 papers receiving 2.3k citations
Hit Papers
Peers
Comparison fields: 5 of 74
- Genetics 1.8k
- Molecular Biology 1.7k
- Oncology 633
- Cardiology and Cardiovascular Medicine 280
- Hematology 258
Countries citing papers authored by Gregory M. Podsakoff
This map shows the geographic impact of Gregory M. Podsakoff'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 Gregory M. Podsakoff with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gregory M. Podsakoff more than expected).
Fields of papers citing papers by Gregory M. Podsakoff
This network shows the impact of papers produced by Gregory M. Podsakoff. 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 Gregory M. Podsakoff. The network helps show where Gregory M. Podsakoff may publish in the future.
Co-authorship network of co-authors of Gregory M. Podsakoff
This figure shows the co-authorship network connecting the top 25 collaborators of Gregory M. Podsakoff. A scholar is included among the top collaborators of Gregory M. Podsakoff 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 Gregory M. Podsakoff. Gregory M. Podsakoff is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 78 | |
| 2 | 30 | |
| 3 | 29 | |
| 4 | 67 | |
| 5 | 1 | |
| 6 | 64 | |
| 7 | 16 | |
| 8 | 15 | |
| 9 | 264 | |
| 10 | 179 | |
| 11 | 5 | |
| 12 | 452 | |
| 13 | 423 | |
| 14 | Single dose, long-term treatment of beta-thalassemia in mice following intramuscular administration of the erythropoietin gene | 1 |
| 15 | Gene delivery to skeletal muscle results in sustained expression and systemic delivery of a therapeutic proteinbreakdown → | 516 |
| 16 | 84 | |
| 17 | 186 | |
| 18 | 8 | |
| 19 | 1 |
About Gregory M. Podsakoff
Gregory M. Podsakoff is a scholar working on Genetics, Hematology and Genetics, having authored 19 papers that have together received 2.4k indexed citations. Recurring topics across this work include Virus-based gene therapy research (11 papers), CRISPR and Genetic Engineering (6 papers) and Acute Myeloid Leukemia Research (4 papers). The work is most often cited by research in Genetics (1.8k citations), Molecular Biology (1.7k citations) and Oncology (633 citations). Gregory M. Podsakoff has collaborated with scholars based in United States, Tunisia and France. Frequent co-authors include Gary J. Kurtzman, Katherine A. High, Peter Colosi, Barry J. Byrne, Paul Kessler, Xiaojuan Chen, Kah Keng Wong, Som S. Chatterjee, Luis P. Villarreal and Takashi Matsushita. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Medicine and Blood.
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.