Daniel R. Matson
Impact in
- Cell Biology top 5%
- Microtubule and mitosis dynamics
-
- Genomics and Chromatin Dynamics
- Ubiquitin and proteasome pathways
- Photosynthetic Processes and Mechanisms
- DNA Repair Mechanisms
Papers in
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- Protein Degradation and Inhibitors 3
- Photosynthetic Processes and Mechanisms 3
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- Acute Myeloid Leukemia Research 7
- Co-authors
- P. Todd Stukenberg (7 shared papers)David T. Yang (3 shared papers)John G. Tooley (2 shared papers)William M. Rehrauer (3 shared papers)Molly A. Accola (3 shared papers)Gregory M. Alushin (1 shared paper)Eva Nogales (1 shared paper)Emery H. Bresnick (8 shared papers)
- Journals
- Blood (3 papers)Leukemia (2 papers)Developmental Cell (2 papers)Cancer Discovery (1 paper)Molecular Interventions (1 paper)
- Partner nations
- United StatesNetherlandsSouth Korea
In The Last Decade
Daniel R. Matson
29 papers receiving 598 citations
Peers
Comparison fields: 5 of 72
- Cell Biology 231
- Molecular Biology 368
- Hematology 51
- Oncology 120
- Immunology 84
Countries citing papers authored by Daniel R. Matson
This map shows the geographic impact of Daniel R. Matson'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 Daniel R. Matson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel R. Matson more than expected).
Fields of papers citing papers by Daniel R. Matson
This network shows the impact of papers produced by Daniel R. Matson. 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 Daniel R. Matson. The network helps show where Daniel R. Matson may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel R. Matson, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 104 | |
| 2 | 2012 | 81 | |
| 3 | 2017 | 58 | |
| 4 | 2019 | 42 | |
| 5 | 2014 | 42 | |
| 6 | 2017 | 39 | |
| 7 | 2017 | 30 | |
| 8 | 2021 | 29 | |
| 9 | 2012 | 29 | |
| 10 | 2005 | 27 | |
| 11 | 2021 | 21 | |
| 12 | 2017 | 18 | |
| 13 | 2017 | 11 | |
| 14 | 2017 | 11 | |
| 15 | 2023 | 10 | |
| 16 | 2021 | 10 | |
| 17 | 2020 | 9 | |
| 18 | 2010 | 6 | |
| 19 | 2021 | 5 | |
| 20 | 2023 | 4 |
About Daniel R. Matson
Daniel R. Matson is a scholar working on Molecular Biology, Hematology, Cell Biology, Immunology and Oncology, having authored 31 papers that have together received 604 indexed citations. Recurring topics across this work include Acute Myeloid Leukemia Research (7 papers), Microtubule and mitosis dynamics (7 papers), Immune Cell Function and Interaction (4 papers), Protein Degradation and Inhibitors (3 papers), Photosynthetic Processes and Mechanisms (3 papers), Erythrocyte Function and Pathophysiology (3 papers), Cancer-related Molecular Pathways (3 papers) and Cellular transport and secretion (3 papers). The work is most often cited by research in Cell Biology (231 citations), Molecular Biology (368 citations), Hematology (51 citations), Oncology (120 citations) and Immunology (84 citations). Daniel R. Matson has collaborated with scholars based in United States, Netherlands and South Korea. Frequent co-authors include P. Todd Stukenberg, David T. Yang, John G. Tooley, William M. Rehrauer, Molly A. Accola, Gregory M. Alushin, Eva Nogales, Emery H. Bresnick, Daniel J. Burke and Owen Pornillos. Their work appears in journals such as Blood, Leukemia, Developmental Cell, Cancer Discovery and Molecular Interventions.
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.