Brian S. Garrison
Impact in
- Aging top 5%
- Hematology top 5%
- Hematopoietic Stem Cell Transplantation
Papers in
-
- RNA Interference and Gene Delivery 5
- CRISPR and Genetic Engineering 4
- Advanced biosensing and bioanalysis techniques 2
- Epigenetics and DNA Methylation 2
- Oncology 8
- CAR-T cell therapy research 7
- Co-authors
- Derrick J. Rossi (9 shared papers)Stephen R. Yant (2 shared papers)Mark A. Kay (2 shared papers)Isabel Beerman (3 shared papers)Zachary D. Smith (1 shared paper)Hongcang Gu (1 shared paper)Alexander Meissner (1 shared paper)Christoph Bock (1 shared paper)
- Journals
- Blood (4 papers)Cell stem cell (3 papers)Cell (3 papers)Cancer Research (3 papers)Molecular and Cellular Biology (2 papers)
- Partner nations
- United StatesSwedenItaly
In The Last Decade
Brian S. Garrison
19 papers receiving 1.7k citations
Hit Papers
Peers
Comparison fields: 5 of 88
- Aging 65
- Hematology 293
- Business and International Management 51
- Molecular Biology 1.3k
- Immunology 341
Countries citing papers authored by Brian S. Garrison
This map shows the geographic impact of Brian S. Garrison'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 Brian S. Garrison with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Brian S. Garrison more than expected).
Fields of papers citing papers by Brian S. Garrison
This network shows the impact of papers produced by Brian S. Garrison. 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 Brian S. Garrison. The network helps show where Brian S. Garrison may publish in the future.
Co-authors
The 25 scholars most cited alongside Brian S. Garrison, 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 | Efficient Ablation of Genes in Human Hematopoietic Stem and Effector Cells using CRISPR/Cas9 Hit paper breakdown → | 2014 | 379 |
| 2 | 2013 | 344 | |
| 3 | 2005 | 248 | |
| 4 | 2014 | 238 | |
| 5 | 2018 | 129 | |
| 6 | 2013 | 83 | |
| 7 | 2000 | 79 | |
| 8 | 2007 | 56 | |
| 9 | 2008 | 40 | |
| 10 | 1997 | 38 | |
| 11 | 2017 | 36 | |
| 12 | 2024 | 19 | |
| 13 | 2017 | 17 | |
| 14 | 2014 | 16 | |
| 15 | 2021 | 10 | |
| 16 | 2014 | 9 | |
| 17 | 2021 | 7 | |
| 18 | 2025 | 2 | |
| 19 | 2023 | 1 | |
| 20 | 2023 | 0 |
About Brian S. Garrison
Brian S. Garrison is a scholar working on Molecular Biology, Oncology, Immunology, Hematology and Epidemiology, having authored 20 papers that have together received 1.8k indexed citations. Recurring topics across this work include CAR-T cell therapy research (7 papers), RNA Interference and Gene Delivery (5 papers), Hematopoietic Stem Cell Transplantation (4 papers), CRISPR and Genetic Engineering (4 papers), Immune Cell Function and Interaction (4 papers), Advanced biosensing and bioanalysis techniques (2 papers), Acute Myeloid Leukemia Research (2 papers) and Epigenetics and DNA Methylation (2 papers). The work is most often cited by research in Aging (65 citations), Hematology (293 citations), Business and International Management (51 citations), Molecular Biology (1.3k citations) and Immunology (341 citations). Brian S. Garrison has collaborated with scholars based in United States, Sweden and Italy. Frequent co-authors include Derrick J. Rossi, Stephen R. Yant, Mark A. Kay, Isabel Beerman, Zachary D. Smith, Hongcang Gu, Alexander Meissner, Christoph Bock, Pankaj Kumar Mandal and Xiaolin Wu. Their work appears in journals such as Blood, Cell stem cell, Cell, Cancer Research and Molecular and Cellular Biology.
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.