Thomas J. Mitchell
Impact in
- Cancer Research top 0.1%
- Cancer Genomics and Diagnostics
- Oncology top 0.5%
- Cancer Immunotherapy and Biomarkers
- Cancer Cells and Metastasis
Papers in
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- Cancer Genomics and Diagnostics 38
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- Renal cell carcinoma treatment 18
- Co-authors
- Mark A.F. Kendall (5 shared papers)Peter Wrighton-Smith (1 shared paper)Valerie G. Brunton (3 shared papers)Joanne Edwards (4 shared papers)Freddie Bray (1 shared paper)Laura Bukavina (1 shared paper)Tim O’Brien (1 shared paper)Sarah P. Psutka (1 shared paper)
- Journals
- Nature Communications (19 papers)Nature (13 papers)Science (5 papers)Nature Genetics (5 papers)British Journal of Cancer (3 papers)
- Partner nations
- United KingdomUnited StatesCanada
In The Last Decade
Thomas J. Mitchell
116 papers receiving 17.6k citations
Thomas J. Mitchell's Hit Papers
Peers
Comparison fields: 5 of 162
- Cancer Research 5.6k
- Oncology 2.7k
- Reproductive Medicine 990
- Molecular Biology 4.9k
- Aging 122
Countries citing papers authored by Thomas J. Mitchell
This map shows the geographic impact of Thomas J. 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 Thomas J. Mitchell with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas J. Mitchell more than expected).
Fields of papers citing papers by Thomas J. Mitchell
This network shows the impact of papers produced by Thomas J. 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 Thomas J. Mitchell. The network helps show where Thomas J. Mitchell may publish in the future.
Co-authors
The 25 scholars most cited alongside Thomas J. 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
Showing the 20 most-cited of 121 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | The repertoire of mutational signatures in human cancer Hit paper breakdown → | 2020 | 2401 |
| 2 | Pan-cancer analysis of whole genomes Hit paper breakdown → | 2020 | 2169 |
| 3 | Whole–genome characterization of chemoresistant ovarian cancer Hit paper breakdown → | 2015 | 1249 |
| 4 | The evolutionary history of 2,658 cancers Hit paper breakdown → | 2020 | 730 |
| 5 | Single-cell transcriptomes from human kidneys reveal the cellular identity of renal tumors Hit paper breakdown → | 2018 | 566 |
| 6 | Patterns of somatic structural variation in human cancer genomes Hit paper breakdown → | 2020 | 564 |
| 7 | Deterministic Evolutionary Trajectories Influence Primary Tumor Growth: TRACERx Renal Hit paper breakdown → | 2018 | 494 |
| 8 | Epidemiology of Renal Cell Carcinoma: 2022 Update Hit paper breakdown → | 2022 | 493 |
| 9 | Comprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing Hit paper breakdown → | 2020 | 489 |
| 10 | Intra-tumour diversification in colorectal cancer at the single-cell level Hit paper breakdown → | 2018 | 445 |
| 11 | Analyses of non-coding somatic drivers in 2,658 cancer whole genomes Hit paper breakdown → | 2020 | 428 |
| 12 | Timing the Landmark Events in the Evolution of Clear Cell Renal Cell Cancer: TRACERx Renal Hit paper breakdown → | 2018 | 405 |
| 13 | The mutational landscape of normal human endometrial epithelium Hit paper breakdown → | 2020 | 372 |
| 14 | Characterizing genetic intra-tumor heterogeneity across 2,658 human cancer genomes Hit paper breakdown → | 2021 | 362 |
| 15 | Mechanisms generating cancer genome complexity from a single cell division error Hit paper breakdown → | 2020 | 329 |
| 16 | Clonal dynamics of haematopoiesis across the human lifespan Hit paper breakdown → | 2022 | 329 |
| 17 | 2019 | 328 | |
| 18 | Comprehensive molecular characterization of mitochondrial genomes in human cancers Hit paper breakdown → | 2020 | 319 |
| 19 | Pan-cancer analysis of whole genomes identifies driver rearrangements promoted by LINE-1 retrotransposition Hit paper breakdown → | 2020 | 315 |
| 20 | Genomic basis for RNA alterations in cancer Hit paper breakdown → | 2020 | 310 |
About Thomas J. Mitchell
Thomas J. Mitchell is a scholar working on Cancer Research, Pulmonary and Respiratory Medicine, Hematology, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging, having authored 121 papers that have together received 17.8k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (38 papers), Renal cell carcinoma treatment (18 papers), Music Technology and Sound Studies (8 papers), Genomic variations and chromosomal abnormalities (6 papers), Single-cell and spatial transcriptomics (5 papers), Ovarian cancer diagnosis and treatment (4 papers), Advanced MRI Techniques and Applications (4 papers) and Multiple Myeloma Research and Treatments (4 papers). The work is most often cited by research in Cancer Research (5.6k citations), Oncology (2.7k citations), Reproductive Medicine (990 citations), Molecular Biology (4.9k citations) and Aging (122 citations). Thomas J. Mitchell has collaborated with scholars based in United Kingdom, United States and Canada. Frequent co-authors include Mark A.F. Kendall, Peter Wrighton-Smith, Valerie G. Brunton, Joanne Edwards, Freddie Bray, Laura Bukavina, Tim O’Brien, Sarah P. Psutka, Valeria Panebianco and Maria Isabel Carlo. Their work appears in journals such as Nature Communications, Nature, Science, Nature Genetics and British Journal of Cancer.
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.