G. Daniel Grass
- Oncology top 5%
- Cancer Immunotherapy and Biomarkers 16
- Cancer Research top 10%
- Cancer Genomics and Diagnostics 10
- Otorhinolaryngology top 5%
- Immunology top 10%
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- Prostate Cancer Diagnosis and Treatment 8
- Lung Cancer Treatments and Mutations 7
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- Bladder and Urothelial Cancer Treatments 14
- Genital Health and Disease 9
- Urinary and Genital Oncology Studies 8
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- Radiomics and Machine Learning in Medical Imaging 8
- Co-authors
- Bryan P. TooleSungjune KimLauren B. TolliverMomka BratoevaMark G. SlomianyKelley M. ArgravesW. Scott ArgravesBrent A. Wilkerson
- Journals
- International Journal of Radiation Oncology*Biology*Physics (13 papers)Journal of Clinical Oncology (8 papers)Journal of Thoracic Oncology (3 papers)
- Partner nations
- United StatesGermanyItaly
In The Last Decade
G. Daniel Grass
75 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 92
- Oncology 493
- Cancer Research 241
- Otorhinolaryngology 61
- Immunology 282
- Pulmonary and Respiratory Medicine 348
Countries citing papers authored by G. Daniel Grass
This map shows the geographic impact of G. Daniel Grass'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 G. Daniel Grass with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites G. Daniel Grass more than expected).
Fields of papers citing papers by G. Daniel Grass
This network shows the impact of papers produced by G. Daniel Grass. 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 G. Daniel Grass. The network helps show where G. Daniel Grass may publish in the future.
Co-authorship network
The 25 scholars most cited alongside G. Daniel Grass, 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 | 0 | |
| 2 | 2025 | 1 | |
| 3 | 2025 | 1 | |
| 4 | 2024 | 8 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 1 | |
| 7 | 2024 | 2 | |
| 8 | 2024 | 0 | |
| 9 | 2023 | 1 | |
| 10 | 2023 | 14 | |
| 11 | 2023 | 27 | |
| 12 | 2023 | 1 | |
| 13 | 2023 | 2 | |
| 14 | 2023 | 2 | |
| 15 | 2023 | 1 | |
| 16 | 2019 | 14 | |
| 17 | 2019 | 39 | |
| 18 | 2018 | 52 | |
| 19 | 2017 | 42 | |
| 20 | 2009 | 121 |
About G. Daniel Grass
G. Daniel Grass is a scholar working on Urology, Cancer Research, Oncology, Pulmonary and Respiratory Medicine and Modeling and Simulation, having authored 78 papers that have together received 1.5k indexed citations. Recurring topics across this work include Cancer Immunotherapy and Biomarkers (16 papers), Bladder and Urothelial Cancer Treatments (14 papers), Cancer Genomics and Diagnostics (10 papers), Genital Health and Disease (9 papers), Prostate Cancer Diagnosis and Treatment (8 papers), Radiomics and Machine Learning in Medical Imaging (8 papers), Urinary and Genital Oncology Studies (8 papers) and Lung Cancer Treatments and Mutations (7 papers). The work is most often cited by research in Oncology (493 citations), Cancer Research (241 citations), Otorhinolaryngology (61 citations), Immunology (282 citations) and Pulmonary and Respiratory Medicine (348 citations). G. Daniel Grass has collaborated with scholars based in United States, Germany and Italy. Frequent co-authors include Bryan P. Toole, Sungjune Kim, Lauren B. Tolliver, Momka Bratoeva, Mark G. Slomiany, Kelley M. Argraves, W. Scott Argraves, Brent A. Wilkerson, Kamran A. Ahmed and Bernard L. Maria. Their work appears in journals such as International Journal of Radiation Oncology*Biology*Physics, Journal of Clinical Oncology, Journal of Thoracic Oncology, Bioinformatics and Cancers.
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.