Daniel J. Murphy
Impact in
- Cancer Research top 5%
- Cancer, Hypoxia, and Metabolism
- Molecular Biology top 5%
- Ubiquitin and proteasome pathways
- Protein Degradation and Inhibitors
- Cell death mechanisms and regulation
- Epigenetics and DNA Methylation
- RNA modifications and cancer
- Metabolism, Diabetes, and Cancer
Papers in
-
- Cancer, Hypoxia, and Metabolism 5
- Oncology 15
- Cancer-related Molecular Pathways 8
- Co-authors
- Gérard I. EvanLamorna Brown SwigartAnthony N. KarnezisCarla P. MartinsAndrew J. FinchSergio NasiLaura SoucekJonathan R. Whitfield
- Journals
- Oncogene (3 papers)Molecular and Cellular Biology (3 papers)Cell Metabolism (2 papers)Scientific Reports (2 papers)Nature (2 papers)
- Partner nations
- United KingdomUnited StatesGermany
In The Last Decade
Daniel J. Murphy
42 papers receiving 2.9k citations
Hit Papers
Peers
Comparison fields: 5 of 122
- Cancer Research 645
- Molecular Biology 2.2k
- Oncology 843
- Immunology 317
- Aging 26
Countries citing papers authored by Daniel J. Murphy
This map shows the geographic impact of Daniel J. Murphy'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 J. Murphy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel J. Murphy more than expected).
Fields of papers citing papers by Daniel J. Murphy
This network shows the impact of papers produced by Daniel J. Murphy. 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 J. Murphy. The network helps show where Daniel J. Murphy may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel J. Murphy, 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 | 2025 | 1 | |
| 2 | 2024 | 5 | |
| 3 | 2024 | 4 | |
| 4 | 2023 | 3 | |
| 5 | 2023 | 6 | |
| 6 | 2018 | 4 | |
| 7 | 2018 | 70 | |
| 8 | CRISPR/Cas9-derived models of ovarian high grade serous carcinoma targeting Brca1, Pten and Nf1, and correlation with platinum sensitivity | 2017 | 2 |
| 9 | 2017 | 27 | |
| 10 | 2017 | 17 | |
| 11 | 2016 | 35 | |
| 12 | 2015 | 195 | |
| 13 | 2015 | 336 | |
| 14 | 2014 | 1 | |
| 15 | 2012 | 43 | |
| 16 | 2010 | 41 | |
| 17 | 2008 | 340 | |
| 18 | Modelling Myc inhibition as a cancer therapy Hit paper breakdown → | 2008 | 644 |
| 19 | 2005 | 14 | |
| 20 | 2004 | 53 |
About Daniel J. Murphy
Daniel J. Murphy is a scholar working on Cancer Research, Oncology, Biotechnology, Cell Biology and Molecular Biology, having authored 43 papers that have together received 3.0k indexed citations. Recurring topics across this work include Cancer-related Molecular Pathways (8 papers), Ubiquitin and proteasome pathways (5 papers), Metabolism, Diabetes, and Cancer (5 papers), Cancer, Hypoxia, and Metabolism (5 papers), Mitochondrial Function and Pathology (4 papers), Occupational and environmental lung diseases (4 papers), Cancer Research and Treatments (4 papers) and Microtubule and mitosis dynamics (3 papers). The work is most often cited by research in Cancer Research (645 citations), Molecular Biology (2.2k citations), Oncology (843 citations), Immunology (317 citations) and Aging (26 citations). Daniel J. Murphy has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Gérard I. Evan, Lamorna Brown Swigart, Anthony N. Karnezis, Carla P. Martins, Andrew J. Finch, Sergio Nasi, Laura Soucek, Jonathan R. Whitfield, Nicole M. Sodir and Nathiya Muthalagu. Their work appears in journals such as Oncogene, Molecular and Cellular Biology, Cell Metabolism, Scientific Reports and Nature.
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.