Daniel J. Noonan
- Immunology top 2%
- T-cell and B-cell Immunology 12
- Immune Cell Function and Interaction 5
- Physiology top 2%
- Tuberous Sclerosis Complex Research 9
- Oncology top 2%
- Molecular Biology top 2%
- Peroxisome Proliferator-Activated Receptors 10
- Retinoids in leukemia and cellular processes 8
- Cancer Research top 5%
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- Monoclonal and Polyclonal Antibodies Research 11
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- Estrogen and related hormone effects 8
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- Cell Adhesion Molecules Research 4
- Co-authors
- Ronald M. EvansSteven A. KliewerKazuhiko UmesonoRichard A. HeymanM V HobbsCary WeinbergerAnthony E. OroJasmine Chen
- Cited by
- ImmunologyPhysiologyOncology
- Partner nations
- United StatesItalyAustria
In The Last Decade
Daniel J. Noonan
58 papers receiving 5.3k citations
Hit Papers
Peers
Comparison fields: 5 of 113
- Immunology 1.2k
- Physiology 1.2k
- Oncology 1.2k
- Molecular Biology 2.9k
- Cancer Research 423
Countries citing papers authored by Daniel J. Noonan
This map shows the geographic impact of Daniel J. Noonan'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. Noonan 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. Noonan more than expected).
Fields of papers citing papers by Daniel J. Noonan
This network shows the impact of papers produced by Daniel J. Noonan. 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. Noonan. The network helps show where Daniel J. Noonan may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Daniel J. Noonan, 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 | 2010 | 9 | |
| 2 | 2004 | 89 | |
| 3 | 2003 | 6 | |
| 4 | 2002 | 350 | |
| 5 | 2001 | 95 | |
| 6 | 2001 | 32 | |
| 7 | 2000 | 56 | |
| 8 | 1997 | 40 | |
| 9 | 1997 | 23 | |
| 10 | 1997 | 1 | |
| 11 | 1996 | 4 | |
| 12 | 1996 | 2 | |
| 13 | 1996 | 25 | |
| 14 | Identification of a nuclear receptor that is activated by farnesol metabolitesbreakdown → | 1995 | 989 |
| 15 | 1991 | 22 | |
| 16 | 1990 | 12 | |
| 17 | 1990 | 124 | |
| 18 | 1988 | 27 | |
| 19 | 1986 | 61 | |
| 20 | 1985 | 79 |
About Daniel J. Noonan
Daniel J. Noonan is a scholar working on Immunology, Immunology and Allergy and Molecular Biology, having authored 58 papers that have together received 5.4k indexed citations. Recurring topics across this work include T-cell and B-cell Immunology (12 papers), Monoclonal and Polyclonal Antibodies Research (11 papers), Peroxisome Proliferator-Activated Receptors (10 papers), Tuberous Sclerosis Complex Research (9 papers), Retinoids in leukemia and cellular processes (8 papers), Estrogen and related hormone effects (8 papers), Immune Cell Function and Interaction (5 papers) and Cell Adhesion Molecules Research (4 papers). The work is most often cited by research in Immunology (1.2k citations), Physiology (1.2k citations) and Oncology (1.2k citations). Daniel J. Noonan has collaborated with scholars based in United States, Italy and Austria. Frequent co-authors include Ronald M. Evans, Steven A. Kliewer, Kazuhiko Umesono, Richard A. Heyman, M V Hobbs, Cary Weinberger, Anthony E. Oro, Jasmine Chen, Leo T. Burka and Trevor C. McMorris. Their work appears in journals such as Nature, Cell and Proceedings of the National Academy of Sciences.
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.