Jonathan Mitchell
Impact in
- Hematology top 10%
- Acute Myeloid Leukemia Research
- Genetics top 10%
- Myeloproliferative Neoplasms: Diagnosis and Treatment
- Genetic diversity and population structure
- Genetic Associations and Epidemiology
Papers in
-
- Genomics and Phylogenetic Studies 3
- Gene expression and cancer classification 1
- Genetics 5
- Genetic Associations and Epidemiology 2
- Genetic diversity and population structure 2
- Genomics and Rare Diseases 1
- Co-authors
- John A. Rhodes (3 shared papers)Elizabeth S. Allman (3 shared papers)Slavé Petrovski (3 shared papers)Margarete A. Fabre (2 shared papers)Stephen Burgess (1 shared paper)Vivek Iyer (1 shared paper)Pedro M. Quirós (1 shared paper)Clea Bárcena (1 shared paper)
- Journals
- Systematic Biology (2 papers)Nature Genetics (2 papers)Journal of Mathematical Biology (1 paper)Genome Biology and Evolution (1 paper)Bioinformatics (1 paper)
- Partner nations
- AustraliaUnited StatesUnited Kingdom
In The Last Decade
Jonathan Mitchell
9 papers receiving 341 citations
Jonathan Mitchell's Hit Papers
Peers
Comparison fields: 5 of 64
- Hematology 114
- Genetics 77
- Cancer Research 52
- Genetics 68
- Molecular Biology 122
Countries citing papers authored by Jonathan Mitchell
This map shows the geographic impact of Jonathan Mitchell'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 Jonathan Mitchell with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonathan Mitchell more than expected).
Fields of papers citing papers by Jonathan Mitchell
This network shows the impact of papers produced by Jonathan Mitchell. 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 Jonathan Mitchell. The network helps show where Jonathan Mitchell may publish in the future.
Co-authors
The 25 scholars most cited alongside Jonathan Mitchell, 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 | Genome-wide analyses of 200,453 individuals yield new insights into the causes and consequences of clonal hematopoiesis Hit paper breakdown → | 2022 | 205 |
| 2 | 2020 | 46 | |
| 3 | 2024 | 45 | |
| 4 | 2021 | 25 | |
| 5 | 2022 | 12 | |
| 6 | 2022 | 6 | |
| 7 | 2024 | 3 | |
| 8 | 2018 | 2 | |
| 9 | 2025 | 1 |
About Jonathan Mitchell
Jonathan Mitchell is a scholar working on Molecular Biology, Genetics, Cancer Research, Hematology and Paleontology, having authored 9 papers that have together received 345 indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (3 papers), Genomics and Phylogenetic Studies (3 papers), Acute Myeloid Leukemia Research (2 papers), Genetic Associations and Epidemiology (2 papers), Genetic diversity and population structure (2 papers), Genomics and Rare Diseases (1 paper), Ferroptosis and cancer prognosis (1 paper) and Gene expression and cancer classification (1 paper). The work is most often cited by research in Hematology (114 citations), Genetics (77 citations), Cancer Research (52 citations), Genetics (68 citations) and Molecular Biology (122 citations). Jonathan Mitchell has collaborated with scholars based in Australia, United States and United Kingdom. Frequent co-authors include John A. Rhodes, Elizabeth S. Allman, Slavé Petrovski, Margarete A. Fabre, Stephen Burgess, Vivek Iyer, Pedro M. Quirós, Clea Bárcena, Hector Baños and Tao Jiang. Their work appears in journals such as Systematic Biology, Nature Genetics, Journal of Mathematical Biology, Genome Biology and Evolution and Bioinformatics.
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.