Daniel J. Noonan

6.3k total citations · 2 hit papers
58 papers, 5.4k citations indexed

About

Daniel J. Noonan is a scholar working on Molecular Biology, Immunology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Daniel J. Noonan has authored 58 papers receiving a total of 5.4k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Molecular Biology, 19 papers in Immunology and 11 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Daniel J. Noonan's work include T-cell and B-cell Immunology (12 papers), Monoclonal and Polyclonal Antibodies Research (11 papers) and Peroxisome Proliferator-Activated Receptors (10 papers). Daniel J. Noonan is often cited by papers focused on T-cell and B-cell Immunology (12 papers), Monoclonal and Polyclonal Antibodies Research (11 papers) and Peroxisome Proliferator-Activated Receptors (10 papers). Daniel J. Noonan collaborates with scholars based in United States, Italy and Austria. Daniel J. Noonan's 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 and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Daniel J. Noonan

58 papers receiving 5.3k citations

Hit Papers

Convergence of 9-cis retinoic acid and peroxisome prolife... 1992 2026 2003 2014 1992 1995 500 1000 1.5k

Peers

Daniel J. Noonan
Roger White United Kingdom
Vilmos Thomázy United States
Sam W. Lee United States
Brian Varnum United States
Warren S.‐L. Liao United States
Jeffrey I. Kreisberg United States
Daniel J. Noonan
Citations per year, relative to Daniel J. Noonan Daniel J. Noonan (= 1×) peers Jeffrey A. Medin

Countries citing papers authored by Daniel J. Noonan

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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 of co-authors of Daniel J. Noonan

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel J. Noonan. A scholar is included among the top collaborators of Daniel J. Noonan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Daniel J. Noonan. Daniel J. Noonan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Wendlandt, Alison E., et al.. (2010). Synthesis and functional analysis of novel bivalent estrogens. Steroids. 75(12). 825–833. 9 indexed citations
2.
Goncharova, Elena A., Dmitry A. Goncharov, Daniel J. Noonan, & Vera P. Krymskaya. (2004). TSC2 modulates actin cytoskeleton and focal adhesion through TSC1-binding domain and the Rac1 GTPase. The Journal of Cell Biology. 167(6). 1171–1182. 89 indexed citations
3.
Henry, Kenneth W., Michael Spencer, Maria Theodosiou, Dingyuan Lou, & Daniel J. Noonan. (2003). A neuronal-specific differentiation protein that directly modulates retinoid receptor transcriptional activation. PubMed. 1(1). 7–7. 6 indexed citations
4.
Goncharova, Elena A., Dmitry A. Goncharov, Andrew Eszterhas, et al.. (2002). Tuberin Regulates p70 S6 Kinase Activation and Ribosomal Protein S6 Phosphorylation. Journal of Biological Chemistry. 277(34). 30958–30967. 350 indexed citations
6.
Lou, Dingyuan, et al.. (2001). The Tuberous Sclerosis 2 Gene Product Can Localize to Nuclei in a Phosphorylation-Dependent Manner. PubMed. 4(6). 374–380. 32 indexed citations
7.
Howard, William R, et al.. (2000). Catabolites of Cholesterol Synthesis Pathways and Forskolin as Activators of the Farnesoid X-Activated Nuclear Receptor. Toxicology and Applied Pharmacology. 163(2). 195–202. 56 indexed citations
8.
Rochford, Rosemary, Martin J. Cannon, Rebecca Sabbe, et al.. (1997). Common and Idiosyncratic Patterns of Cytokine Gene Expression by Epstein-Barr Virus Transformed Human B Cell Lines. Viral Immunology. 10(4). 183–195. 40 indexed citations
9.
Rangwala, Shamina M., Michelle L. O’Brien, Vincenzo Tortorella, et al.. (1997). Stereoselective effects of chiral clofibric acid analogs on rat peroxisome proliferator-activated receptor ? (rPPAR?) activation and peroxisomal fatty acid ?-oxidation. Chirality. 9(1). 37–47. 23 indexed citations
10.
Noonan, Daniel J. & Michelle L. O’Brien. (1997). A Hypothetical Mechanism for Fat-Induced Rodent Hepatocarcinogenesis. Advances in experimental medicine and biology. 422. 127–135. 1 indexed citations
11.
Eacho, Patrick I., Patricia Foxworthy, Jeffrey Lawrence, David K. Herron, & Daniel J. Noonan. (1996). Common Structural Requirements for Peroxisome Proliferation by Tetrazole and Carboxylic Acid‐Containing Compounds. Annals of the New York Academy of Sciences. 804(1). 387–402. 4 indexed citations
12.
FELLER, D. R., Michelle L. O’Brien, Shamina M. Rangwala, et al.. (1996). Structural Requirements of Chiral Clofibric Acid Analogs for Activation of the Rat Peroxisome Proliferator‐activated Receptor α. Annals of the New York Academy of Sciences. 804(1). 713–714. 2 indexed citations
13.
O’Brien, Michelle L., Shamina M. Rangwala, Kenneth W. Henry, et al.. (1996). Convergence of three steroid receptor pathways in the mediation of nongenotoxic hepatocarcinogenesis. Carcinogenesis. 17(2). 185–190. 25 indexed citations
14.
Forman, Barry M., Elizabeth C. Goode, Jasmine Chen, et al.. (1995). Identification of a nuclear receptor that is activated by farnesol metabolites. Cell. 81(5). 687–693. 989 indexed citations breakdown →
15.
Hobbs, M V, et al.. (1991). Interleukin-6 production by murine B cells and B cell lines. Cellular Immunology. 132(2). 442–450. 22 indexed citations
16.
Noonan, Daniel J., et al.. (1990). Correlations of autoimmunity with H2 and T cell receptor β chain genotypesin (NZB x NZW) F2 mice. European Journal of Immunology. 20(5). 1105–1110. 12 indexed citations
17.
Scholz, Wolfgang, et al.. (1990). C5a-mediated release of interleukin 6 by human monocytes. Clinical Immunology and Immunopathology. 57(2). 297–307. 124 indexed citations
18.
Morgan, Eric Lease, M V Hobbs, Daniel J. Noonan, & W O Weigle. (1988). Induction of IL-1 secretion from human monocytes by Fc region subfragments of human IgG1.. The Journal of Immunology. 140(9). 3014–3020. 27 indexed citations
19.
Noonan, Daniel J., et al.. (1986). Delineation of a defect in T cell receptor beta genes of NZW mice predisposed to autoimmunity.. The Journal of Experimental Medicine. 163(3). 644–653. 61 indexed citations
20.
Kofler, Reinhard, Daniel J. Noonan, David T. Levy, et al.. (1985). Genetic elements used for a murine lupus anti-DNA autoantibody are closely related to those for antibodies to exogenous antigens.. The Journal of Experimental Medicine. 161(4). 805–815. 79 indexed citations

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.

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