Todd E. Meyerrose
Impact in
- Genetics top 1%
- Mesenchymal stem cell research
- Hematology top 2%
- Hematopoietic Stem Cell Transplantation
- Acute Myeloid Leukemia Research
Papers in
- Genetics 11
- Mesenchymal stem cell research 11
- Virus-based gene therapy research 5
-
- RNA Interference and Gene Delivery 4
- Muscle Physiology and Disorders 3
- Co-authors
- Jan A. Nolta (12 shared papers)Barry Grimes (6 shared papers)Phillip E. Herrbrich (5 shared papers)Louisa Wirthlin (4 shared papers)Michael H. Creer (2 shared papers)Craig T. Jordan (1 shared paper)GL Phillips (1 shared paper)R. Rossi (1 shared paper)
- Journals
- Blood (5 papers)Molecular Therapy (3 papers)Journal of Clinical Investigation (3 papers)Stem Cells (2 papers)The FASEB Journal (2 papers)
- Partner nations
- United StatesNetherlandsGermany
In The Last Decade
Todd E. Meyerrose
20 papers receiving 2.2k citations
Todd E. Meyerrose's Hit Papers
Peers
Comparison fields: 5 of 93
- Genetics 664
- Hematology 591
- Oncology 592
- Immunology 355
- Molecular Biology 951
Countries citing papers authored by Todd E. Meyerrose
This map shows the geographic impact of Todd E. Meyerrose'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 Todd E. Meyerrose with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Todd E. Meyerrose more than expected).
Fields of papers citing papers by Todd E. Meyerrose
This network shows the impact of papers produced by Todd E. Meyerrose. 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 Todd E. Meyerrose. The network helps show where Todd E. Meyerrose may publish in the future.
Co-authors
The 25 scholars most cited alongside Todd E. Meyerrose, 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 | The interleukin-3 receptor alpha chain is a unique marker for human acute myelogenous leukemia stem cells Hit paper breakdown → | 2000 | 656 |
| 2 | 2004 | 286 | |
| 3 | 2007 | 269 | |
| 4 | 2002 | 164 | |
| 5 | 2006 | 152 | |
| 6 | 2010 | 137 | |
| 7 | 2002 | 126 | |
| 8 | 2001 | 90 | |
| 9 | 2008 | 80 | |
| 10 | 2008 | 59 | |
| 11 | 2003 | 50 | |
| 12 | 2000 | 48 | |
| 13 | 2000 | 47 | |
| 14 | 2001 | 32 | |
| 15 | 2003 | 26 | |
| 16 | 2002 | 23 | |
| 17 | 2004 | 18 | |
| 18 | 2006 | 11 | |
| 19 | 2000 | 3 | |
| 20 | 2006 | 1 |
About Todd E. Meyerrose
Todd E. Meyerrose is a scholar working on Genetics, Molecular Biology, Surgery, Hematology and Oncology, having authored 20 papers that have together received 2.3k indexed citations. Recurring topics across this work include Mesenchymal stem cell research (11 papers), Hematopoietic Stem Cell Transplantation (5 papers), Tissue Engineering and Regenerative Medicine (5 papers), Virus-based gene therapy research (5 papers), RNA Interference and Gene Delivery (4 papers), Immune Cell Function and Interaction (4 papers), Muscle Physiology and Disorders (3 papers) and CAR-T cell therapy research (2 papers). The work is most often cited by research in Genetics (664 citations), Hematology (591 citations), Oncology (592 citations), Immunology (355 citations) and Molecular Biology (951 citations). Todd E. Meyerrose has collaborated with scholars based in United States, Netherlands and Germany. Frequent co-authors include Jan A. Nolta, Barry Grimes, Phillip E. Herrbrich, Louisa Wirthlin, Michael H. Creer, Craig T. Jordan, GL Phillips, R. Rossi, Stephen J. Szilvassy and S. M. Luger. Their work appears in journals such as Blood, Molecular Therapy, Journal of Clinical Investigation, Stem Cells and The FASEB Journal.
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.