Ultan McDermott
Impact in
- Cancer Research top 0.05%
- Cancer Genomics and Diagnostics
- Oncology top 0.05%
- Cancer Immunotherapy and Biomarkers
- Cancer Cells and Metastasis
Papers in
-
- Cancer Genomics and Diagnostics 64
- Oncology 43
- Colorectal Cancer Treatments and Studies 10
- Co-authors
- Michael R. Stratton (6 shared papers)Mathew J. Garnett (23 shared papers)Sridhar Ramaswamy (4 shared papers)Cyril H. Benes (13 shared papers)Nidhi Bindal (3 shared papers)Simon Andrew Forbes (3 shared papers)Patrick G. Johnston (10 shared papers)Daniel A. Haber (8 shared papers)
- Journals
- Nature Communications (21 papers)Nature (13 papers)Nature Genetics (12 papers)Cancer Research (6 papers)Cell (5 papers)
- Partner nations
- United KingdomUnited StatesGermany
In The Last Decade
Ultan McDermott
161 papers receiving 43.8k citations
Ultan McDermott's Hit Papers
Peers
Comparison fields: 5 of 192
- Cancer Research 13.7k
- Oncology 13.5k
- Molecular Biology 22.2k
- Pulmonary and Respiratory Medicine 8.3k
- Pathology and Forensic Medicine 3.9k
Countries citing papers authored by Ultan McDermott
This map shows the geographic impact of Ultan McDermott'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 Ultan McDermott with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ultan McDermott more than expected).
Fields of papers citing papers by Ultan McDermott
This network shows the impact of papers produced by Ultan McDermott. 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 Ultan McDermott. The network helps show where Ultan McDermott may publish in the future.
Co-authors
The 25 scholars most cited alongside Ultan McDermott, 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 165 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Signatures of mutational processes in human cancer Hit paper breakdown → | 2013 | 7583 |
| 2 | Genomics of Drug Sensitivity in Cancer (GDSC): a resource for therapeutic biomarker discovery in cancer cells Hit paper breakdown → | 2012 | 2903 |
| 3 | The repertoire of mutational signatures in human cancer Hit paper breakdown → | 2020 | 2339 |
| 4 | A Chromatin-Mediated Reversible Drug-Tolerant State in Cancer Cell Subpopulations Hit paper breakdown → | 2010 | 2127 |
| 5 | Pan-cancer analysis of whole genomes Hit paper breakdown → | 2020 | 2109 |
| 6 | Systematic identification of genomic markers of drug sensitivity in cancer cells Hit paper breakdown → | 2012 | 1947 |
| 7 | Prospective Derivation of a Living Organoid Biobank of Colorectal Cancer Patients Hit paper breakdown → | 2015 | 1939 |
| 8 | COSMIC: exploring the world's knowledge of somatic mutations in human cancer Hit paper breakdown → | 2014 | 1913 |
| 9 | Clinical Features and Outcome of Patients With Non–Small-Cell Lung Cancer Who Harbor EML4-ALK Hit paper breakdown → | 2009 | 1615 |
| 10 | A Landscape of Pharmacogenomic Interactions in Cancer Hit paper breakdown → | 2016 | 1451 |
| 11 | The evolutionary history of lethal metastatic prostate cancer Hit paper breakdown → | 2015 | 1097 |
| 12 | The evolutionary history of 2,658 cancers Hit paper breakdown → | 2020 | 705 |
| 13 | Patterns of somatic structural variation in human cancer genomes Hit paper breakdown → | 2020 | 550 |
| 14 | Targeting MYCN in Neuroblastoma by BET Bromodomain Inhibition Hit paper breakdown → | 2013 | 535 |
| 15 | A CRISPR Dropout Screen Identifies Genetic Vulnerabilities and Therapeutic Targets in Acute Myeloid Leukemia Hit paper breakdown → | 2016 | 506 |
| 16 | Low MITF/AXL ratio predicts early resistance to multiple targeted drugs in melanoma Hit paper breakdown → | 2014 | 484 |
| 17 | Comprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing Hit paper breakdown → | 2020 | 476 |
| 18 | 2008 | 443 | |
| 19 | Analyses of non-coding somatic drivers in 2,658 cancer whole genomes Hit paper breakdown → | 2020 | 419 |
| 20 | Machine Learning Prediction of Cancer Cell Sensitivity to Drugs Based on Genomic and Chemical Properties Hit paper breakdown → | 2013 | 403 |
About Ultan McDermott
Ultan McDermott is a scholar working on Cancer Research, Oncology, Molecular Biology, Pathology and Forensic Medicine and Pulmonary and Respiratory Medicine, having authored 165 papers that have together received 44.5k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (64 papers), Genetic factors in colorectal cancer (20 papers), Lung Cancer Treatments and Mutations (18 papers), Computational Drug Discovery Methods (11 papers), Colorectal Cancer Treatments and Studies (10 papers), DNA Repair Mechanisms (10 papers), CRISPR and Genetic Engineering (10 papers) and RNA modifications and cancer (8 papers). The work is most often cited by research in Cancer Research (13.7k citations), Oncology (13.5k citations), Molecular Biology (22.2k citations), Pulmonary and Respiratory Medicine (8.3k citations) and Pathology and Forensic Medicine (3.9k citations). Ultan McDermott has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Michael R. Stratton, Mathew J. Garnett, Sridhar Ramaswamy, Cyril H. Benes, Nidhi Bindal, Simon Andrew Forbes, Patrick G. Johnston, Daniel A. Haber, Patricia Greninger and Jeffrey E. Settleman. Their work appears in journals such as Nature Communications, Nature, Nature Genetics, Cancer Research and Cell.
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.