Michael L. Bloom
Impact in
- Hematology top 10%
- Hematopoietic Stem Cell Transplantation
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- Virus-based gene therapy research
- Hemoglobinopathies and Related Disorders
Papers in
-
- RNA modifications and cancer 2
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- Erythrocyte Function and Pathophysiology 7
- Co-authors
- Jane E. Barker (4 shared papers)Karen L. Simon-Stoos (4 shared papers)Warren E. Zimmer (4 shared papers)Steven R. Goodman (4 shared papers)Ian S. Zagon (2 shared papers)Jichun Chen (1 shared paper)Neal S. Young (1 shared paper)Connie S. Birkenmeier (3 shared papers)
- Journals
- Blood (5 papers)Mammalian Genome (3 papers)Experimental Hematology (2 papers)Proceedings of the National Academy of Sciences (2 papers)Human Gene Therapy (1 paper)
- Partner nations
- United StatesGermanyThailand
In The Last Decade
Michael L. Bloom
18 papers receiving 467 citations
Peers
Comparison fields: 5 of 58
- Hematology 117
- Genetics 62
- Physiology 132
- Immunology 89
- Cell Biology 61
Countries citing papers authored by Michael L. Bloom
This map shows the geographic impact of Michael L. Bloom'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 L. Bloom with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael L. Bloom more than expected).
Fields of papers citing papers by Michael L. Bloom
This network shows the impact of papers produced by Michael L. Bloom. 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 L. Bloom. The network helps show where Michael L. Bloom may publish in the future.
Co-authors
The 25 scholars most cited alongside Michael L. Bloom, 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 | 1995 | 107 | |
| 2 | 2004 | 86 | |
| 3 | 1999 | 59 | |
| 4 | 1999 | 49 | |
| 5 | 1994 | 30 | |
| 6 | 1994 | 29 | |
| 7 | 1992 | 28 | |
| 8 | 1985 | 19 | |
| 9 | 1998 | 15 | |
| 10 | 1997 | 12 | |
| 11 | 1997 | 10 | |
| 12 | 1992 | 8 | |
| 13 | 1998 | 7 | |
| 14 | 1999 | 5 | |
| 15 | 1994 | 3 | |
| 16 | 1999 | 3 | |
| 17 | 1999 | 2 | |
| 18 | 1997 | 1 |
About Michael L. Bloom
Michael L. Bloom is a scholar working on Molecular Biology, Physiology, Genetics, Hematology and Genetics, having authored 18 papers that have together received 473 indexed citations. Recurring topics across this work include Erythrocyte Function and Pathophysiology (7 papers), Hemoglobinopathies and Related Disorders (5 papers), Hematopoietic Stem Cell Transplantation (3 papers), Immune Cell Function and Interaction (3 papers), T-cell and B-cell Immunology (2 papers), Blood groups and transfusion (2 papers), RNA modifications and cancer (2 papers) and Virus-based gene therapy research (2 papers). The work is most often cited by research in Hematology (117 citations), Genetics (62 citations), Physiology (132 citations), Immunology (89 citations) and Cell Biology (61 citations). Michael L. Bloom has collaborated with scholars based in United States, Germany and Thailand. Frequent co-authors include Jane E. Barker, Karen L. Simon-Stoos, Warren E. Zimmer, Steven R. Goodman, Ian S. Zagon, Jichun Chen, Neal S. Young, Connie S. Birkenmeier, Kazunori Imada and Maria Berg. Their work appears in journals such as Blood, Mammalian Genome, Experimental Hematology, Proceedings of the National Academy of Sciences and Human Gene Therapy.
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.