Samson Koelle
Impact in
- Hematology top 10%
- Hematopoietic Stem Cell Transplantation
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- Immune Cell Function and Interaction
- T-cell and B-cell Immunology
- IL-33, ST2, and ILC Pathways
Papers in
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- Single-cell and spatial transcriptomics 5
- CRISPR and Genetic Engineering 2
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- Hematopoietic Stem Cell Transplantation 6
- Co-authors
- Chuanfeng Wu (10 shared papers)Cynthia E. Dunbar (10 shared papers)Robert E. Donahue (7 shared papers)Rong Lu (5 shared papers)Brian Li (4 shared papers)Diego A. Espinoza (7 shared papers)Mark E. Metzger (4 shared papers)Frank Liang (1 shared paper)
- Journals
- Blood (2 papers)Molecular Therapy — Methods & Clinical Development (2 papers)Science Immunology (1 paper)The Annals of Applied Statistics (1 paper)Nature Computational Science (1 paper)
- Partner nations
- United StatesChinaSweden
In The Last Decade
Samson Koelle
11 papers receiving 280 citations
Peers
Comparison fields: 5 of 43
- Hematology 100
- Immunology 147
- Genetics 27
- Genetics 61
- Cancer Research 29
Countries citing papers authored by Samson Koelle
This map shows the geographic impact of Samson Koelle'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 Samson Koelle with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Samson Koelle more than expected).
Fields of papers citing papers by Samson Koelle
This network shows the impact of papers produced by Samson Koelle. 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 Samson Koelle. The network helps show where Samson Koelle may publish in the future.
Co-authors
The 25 scholars most cited alongside Samson Koelle, 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 | 2014 | 128 | |
| 2 | 2017 | 37 | |
| 3 | 2018 | 36 | |
| 4 | 2018 | 29 | |
| 5 | 2017 | 24 | |
| 6 | 2021 | 15 | |
| 7 | 2018 | 8 | |
| 8 | 2019 | 7 | |
| 9 | 2023 | 2 | |
| 10 | Statistical inference in partially observed stochastic compartmental models with application to cell lineage tracking of in vivo hematopoiesis | 2016 | 1 |
| 11 | 2021 | 1 |
About Samson Koelle
Samson Koelle is a scholar working on Molecular Biology, Hematology, Immunology, Genetics and Genetics, having authored 11 papers that have together received 288 indexed citations. Recurring topics across this work include Hematopoietic Stem Cell Transplantation (6 papers), Single-cell and spatial transcriptomics (5 papers), T-cell and B-cell Immunology (5 papers), Virus-based gene therapy research (3 papers), CRISPR and Genetic Engineering (2 papers), Immune Cell Function and Interaction (2 papers), Mesenchymal stem cell research (1 paper) and Cell Image Analysis Techniques (1 paper). The work is most often cited by research in Hematology (100 citations), Immunology (147 citations), Genetics (27 citations), Genetics (61 citations) and Cancer Research (29 citations). Samson Koelle has collaborated with scholars based in United States, China and Sweden. Frequent co-authors include Chuanfeng Wu, Cynthia E. Dunbar, Robert E. Donahue, Rong Lu, Brian Li, Diego A. Espinoza, Mark E. Metzger, Frank Liang, Karin Loré and Irvin S. Y. Chen. Their work appears in journals such as Blood, Molecular Therapy — Methods & Clinical Development, Science Immunology, The Annals of Applied Statistics and Nature Computational Science.
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.