Daniel H.D. Gray
- Immunology top 0.5%
- Immune Cell Function and Interaction 38
- T-cell and B-cell Immunology 38
- Immunotherapy and Immune Responses 24
- Oncology top 2%
- CAR-T cell therapy research 6
- Hematology top 2%
-
- Adrenal Hormones and Disorders 9
- Genetics top 2%
- Chronic Lymphocytic Leukemia Research 9
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- Cell death mechanisms and regulation 8
- Single-cell and spatial transcriptomics 6
- Co-authors
- Adrian ListonRichard L. BoydChristophe BenoıstAnn P. ChidgeyTomoo UenoAndreas StrasserDiane MathisJohn Chalmers
- Cited by
- ImmunologyOncologyHematology
- Journals
- The Journal of Immunology (10 papers)Cell Death and Differentiation (10 papers)Blood (8 papers)
- Partner nations
- AustraliaUnited StatesNew Zealand
In The Last Decade
Daniel H.D. Gray
117 papers receiving 7.1k citations
Hit Papers
Peers
Comparison fields: 5 of 128
- Immunology 3.7k
- Oncology 1.5k
- Hematology 574
- Endocrinology, Diabetes and Metabolism 688
- Genetics 432
Countries citing papers authored by Daniel H.D. Gray
This map shows the geographic impact of Daniel H.D. Gray'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 H.D. Gray with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel H.D. Gray more than expected).
Fields of papers citing papers by Daniel H.D. Gray
This network shows the impact of papers produced by Daniel H.D. Gray. 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 H.D. Gray. The network helps show where Daniel H.D. Gray may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Daniel H.D. Gray, 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 | 2023 | 2 | |
| 2 | 2022 | 1 | |
| 3 | 2020 | 70 | |
| 4 | 2020 | 19 | |
| 5 | 2020 | 12 | |
| 6 | 2020 | 2 | |
| 7 | Acquisition of the Recurrent Gly101Val Mutation in BCL2 Confers Resistance to Venetoclax in Patients with Progressive Chronic Lymphocytic Leukemiabreakdown → | 2018 | 276 |
| 8 | 2017 | 214 | |
| 9 | 2017 | 16 | |
| 10 | 2014 | 10 | |
| 11 | TRANSGENIC OVER-EXPRESSION OF GM-CSF IN T CELLS CAUSES HISTIOCYTOSIS | 2012 | 1 |
| 12 | 2011 | 18 | |
| 13 | 2008 | 87 | |
| 14 | 2008 | 171 | |
| 15 | 2007 | 81 | |
| 16 | 2005 | 163 | |
| 17 | 2004 | 241 | |
| 18 | 2002 | 67 | |
| 19 | The modulation of bone marrow killer cells by cytokines | 1990 | 2 |
| 20 | 1971 | 2 |
About Daniel H.D. Gray
Daniel H.D. Gray is a scholar working on Immunology, Oncology and Genetics, having authored 120 papers that have together received 7.2k indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (38 papers), T-cell and B-cell Immunology (38 papers), Immunotherapy and Immune Responses (24 papers), Chronic Lymphocytic Leukemia Research (9 papers), Adrenal Hormones and Disorders (9 papers), Cell death mechanisms and regulation (8 papers), Single-cell and spatial transcriptomics (6 papers) and CAR-T cell therapy research (6 papers). The work is most often cited by research in Immunology (3.7k citations), Oncology (1.5k citations) and Hematology (574 citations). Daniel H.D. Gray has collaborated with scholars based in Australia, United States and New Zealand. Frequent co-authors include Adrian Liston, Richard L. Boyd, Christophe Benoıst, Ann P. Chidgey, Tomoo Ueno, Andreas Strasser, Diane Mathis, John Chalmers, James S. Rush and Christopher C. Goodnow. Their work appears in journals such as The Journal of Immunology, Cell Death and Differentiation, Blood, Cell Reports and Immunology and Cell Biology.
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.