Michael G. Rosenblum
- Statistical and Nonlinear Physics top 0.02%
- Chaos control and synchronization 27
- stochastic dynamics and bifurcation 21
- Computer Networks and Communications top 0.05%
- Nonlinear Dynamics and Pattern Formation 67
- Cognitive Neuroscience top 0.2%
- Neural dynamics and brain function 48
- Immunology top 1%
- Toxin Mechanisms and Immunotoxins 45
- Immunotherapy and Immune Responses 19
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- Monoclonal and Polyclonal Antibodies Research 56
- Radiopharmaceutical Chemistry and Applications 20
Michael G. Rosenblum
276 papers receiving 20.8k citations
Hit Papers
Peers
Comparison fields: 5 of 191
- Statistical and Nonlinear Physics 7.6k
- Computer Networks and Communications 9.3k
- Cognitive Neuroscience 5.6k
- Immunology 2.0k
- Radiology, Nuclear Medicine and Imaging 1.7k
Countries citing papers authored by Michael G. Rosenblum
This map shows the geographic impact of Michael G. Rosenblum'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 Michael G. Rosenblum with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael G. Rosenblum more than expected).
Fields of papers citing papers by Michael G. Rosenblum
This network shows the impact of papers produced by Michael G. Rosenblum. 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 Michael G. Rosenblum. The network helps show where Michael G. Rosenblum may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Michael G. Rosenblum, 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 | 2019 | 15 | |
| 2 | 2018 | 22 | |
| 3 | 2018 | 15 | |
| 4 | 2014 | 21 | |
| 5 | 2013 | 12 | |
| 6 | 2013 | 25 | |
| 7 | 2011 | 18 | |
| 8 | 2011 | 23 | |
| 9 | 2011 | 30 | |
| 10 | 2006 | 25 | |
| 11 | 2006 | 228 | |
| 12 | Targeting PSMA on tumor cells using novel aptamer-gelonin conjugates | 2005 | 1 |
| 13 | 2005 | 23 | |
| 14 | 2004 | 14 | |
| 15 | Multifractality in Human Heartbeat Dynamics | 1998 | 1 |
| 16 | 1996 | 414 | |
| 17 | 1995 | 41 | |
| 18 | 1990 | 56 | |
| 19 | 1988 | 7 | |
| 20 | Human leukocyte interferon (IFN) and mismatched, double-stranded RNA (dsRNA): synergistic antiproliferative activity in vitro | 1985 | 1 |
About Michael G. Rosenblum
Michael G. Rosenblum is a scholar working on Statistical and Nonlinear Physics, Immunology and Biotechnology, having authored 279 papers that have together received 21.6k indexed citations. Recurring topics across this work include Nonlinear Dynamics and Pattern Formation (67 papers), Monoclonal and Polyclonal Antibodies Research (56 papers), Neural dynamics and brain function (48 papers), Toxin Mechanisms and Immunotoxins (45 papers), Chaos control and synchronization (27 papers), stochastic dynamics and bifurcation (21 papers), Radiopharmaceutical Chemistry and Applications (20 papers) and Immunotherapy and Immune Responses (19 papers). The work is most often cited by research in Statistical and Nonlinear Physics (7.6k citations), Computer Networks and Communications (9.3k citations) and Cognitive Neuroscience (5.6k citations). Michael G. Rosenblum has collaborated with scholars based in United States, Germany and Russia. Frequent co-authors include Arkady Pikovsky, Jürgen Kurths, Lawrence H. Cheung, Peter A. Tass, Grigory V. Osipov, Jordan U. Gutterman, John W. Marks, Jens Volkmann, Alfons Schnitzler and Hans‐Joachim Freund. Their work appears in journals such as Nature, Science and Proceedings of the National Academy of Sciences.
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.