Jonathan Q. Tran

1.3k total citations
43 papers, 1.0k citations indexed

About

Jonathan Q. Tran is a scholar working on Molecular Biology, Immunology and Infectious Diseases. According to data from OpenAlex, Jonathan Q. Tran has authored 43 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 10 papers in Immunology and 8 papers in Infectious Diseases. Recurrent topics in Jonathan Q. Tran's work include Multiple Sclerosis Research Studies (8 papers), Monoclonal and Polyclonal Antibodies Research (8 papers) and HIV/AIDS drug development and treatment (8 papers). Jonathan Q. Tran is often cited by papers focused on Multiple Sclerosis Research Studies (8 papers), Monoclonal and Polyclonal Antibodies Research (8 papers) and HIV/AIDS drug development and treatment (8 papers). Jonathan Q. Tran collaborates with scholars based in United States, Switzerland and Egypt. Jonathan Q. Tran's co-authors include Hugh M. Davis, Thomas McIntosh, David E. Martin, Steven J. Kovacs, Ahmed A. Othman, Jeffrey Hartung, Paul Frohna, John G. Gerber, Gregg Timony and Marcus F. Boehm and has published in prestigious journals such as Neurology, Antimicrobial Agents and Chemotherapy and Journal of Hepatology.

In The Last Decade

Jonathan Q. Tran

40 papers receiving 992 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jonathan Q. Tran United States 19 287 185 170 170 169 43 1.0k
Josepmaria Argemí Spain 19 429 1.5× 195 1.1× 93 0.5× 155 0.9× 421 2.5× 82 1.2k
Salah‐Dine Chibout Switzerland 18 352 1.2× 64 0.3× 95 0.6× 232 1.4× 122 0.7× 40 1.1k
Monia Baldoni Italy 18 241 0.8× 87 0.5× 83 0.5× 184 1.1× 295 1.7× 30 1.0k
Pilar Justo Spain 19 570 2.0× 147 0.8× 43 0.3× 271 1.6× 127 0.8× 24 1.4k
Constantine Vagianos Greece 22 289 1.0× 165 0.9× 80 0.5× 59 0.3× 231 1.4× 39 1.3k
Laurence Chauvelot‐Moachon France 19 213 0.7× 40 0.2× 130 0.8× 173 1.0× 261 1.5× 33 1.2k
Rongqi Wang China 22 672 2.3× 110 0.6× 67 0.4× 132 0.8× 524 3.1× 60 1.9k
Zongguo Yang China 22 562 2.0× 77 0.4× 124 0.7× 93 0.5× 308 1.8× 51 1.4k
Sen Zhong China 18 231 0.8× 50 0.3× 97 0.6× 109 0.6× 477 2.8× 67 1.3k

Countries citing papers authored by Jonathan Q. Tran

Since Specialization
Citations

This map shows the geographic impact of Jonathan Q. Tran'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 Jonathan Q. Tran with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonathan Q. Tran more than expected).

Fields of papers citing papers by Jonathan Q. Tran

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jonathan Q. Tran. 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 Jonathan Q. Tran. The network helps show where Jonathan Q. Tran may publish in the future.

Co-authorship network of co-authors of Jonathan Q. Tran

This figure shows the co-authorship network connecting the top 25 collaborators of Jonathan Q. Tran. A scholar is included among the top collaborators of Jonathan Q. Tran 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 Jonathan Q. Tran. Jonathan Q. Tran 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.
Cilliers, Cornelius, Eleanor Howgate, Hannah M. Jones, Lisa Rahbæk, & Jonathan Q. Tran. (2024). Clinical and Physiologically Based Pharmacokinetic Model Evaluations of Adagrasib Drug–Drug Interactions. Clinical Pharmacology & Therapeutics. 117(3). 732–741. 1 indexed citations
2.
Rahbæk, Lisa, Cornelius Cilliers, Christopher J. Wegerski, et al.. (2024). Absorption, single-dose and steady-state metabolism, excretion, and pharmacokinetics of adagrasib, a KRASG12C inhibitor. Cancer Chemotherapy and Pharmacology. 95(1). 7–7. 2 indexed citations
3.
Liu, Yong, et al.. (2024). Concentration‐QTc modeling of sitravatinib in patients with advanced solid malignancies. Clinical and Translational Science. 17(5). e13808–e13808.
4.
Surapaneni, Sekhar, Usha Yerramilli, Deepak Dalvie, et al.. (2021). Absorption, Metabolism, and Excretion, In Vitro Pharmacology, and Clinical Pharmacokinetics of Ozanimod, a Novel Sphingosine 1-Phosphate Receptor Modulator. Drug Metabolism and Disposition. 49(5). 405–419. 56 indexed citations
7.
Diao, Lei, Yaming Hang, Ahmed A. Othman, Ivan Nestorov, & Jonathan Q. Tran. (2016). Population Pharmacokinetics of Daclizumab High-Yield Process in Healthy Volunteers and Subjects with Multiple Sclerosis: Analysis of Phase I–III Clinical Trials. Clinical Pharmacokinetics. 55(8). 943–955. 18 indexed citations
8.
Tran, Jonathan Q., et al.. (2016). Pharmacokinetics of daclizumab high-yield process with repeated administration of the clinical subcutaneous regimen in patients with relapsing-remitting multiple sclerosis. Clinical Pharmacology Advances and Applications. 8. 9–9. 12 indexed citations
11.
Minocha, Mukul, Jonathan Q. Tran, James P. Sheridan, & Ahmed A. Othman. (2015). Blockade of the High-Affinity Interleukin-2 Receptors with Daclizumab High-Yield Process: Pharmacokinetic/Pharmacodynamic Analysis of Single- and Multiple-Dose Phase I Trials. Clinical Pharmacokinetics. 55(1). 121–130. 8 indexed citations
12.
Othman, Ahmed A., Jonathan Q. Tran, Meina Tang, & Sandeep Dutta. (2014). Population Pharmacokinetics of Daclizumab High-Yield Process in Healthy Volunteers: Integrated Analysis of Intravenous and Subcutaneous, Single- and Multiple-Dose Administration. Clinical Pharmacokinetics. 53(10). 907–918. 29 indexed citations
13.
Morcos, Peter N., Linda Chang, Rohit Kulkarni, et al.. (2013). A randomised study of the effect of danoprevir/ritonavir or ritonavir on substrates of cytochrome P450 (CYP) 3A and 2C9 in chronic hepatitis C patients using a drug cocktail. European Journal of Clinical Pharmacology. 69(11). 1939–1949. 24 indexed citations
14.
Reddy, Micaela B., Yuan Chen, Joshua Haznedar, et al.. (2012). Impact of Low-Dose Ritonavir on Danoprevir Pharmacokinetics. Clinical Pharmacokinetics. 51(7). 457–465. 16 indexed citations
15.
Jinesh, Goodwin G., et al.. (2012). Lenalidomide augments the efficacy of bacillus Calmette-Guerin (BCG) immunotherapy in vivo. Urologic Oncology Seminars and Original Investigations. 31(8). 1676–1682. 19 indexed citations
16.
Gane, Edward, Roman Rouzier, Catherine Stedman, et al.. (2011). Antiviral activity, safety, and pharmacokinetics of danoprevir/ritonavir plus PEG-IFN α-2a/RBV in hepatitis C patients. Journal of Hepatology. 55(5). 972–979. 42 indexed citations
17.
Tran, Jonathan Q.. (2002). Pharmacokinetic interaction between amprenavir and delavirdine: Evidence of induced clearance by amprenavir. Clinical Pharmacology & Therapeutics. 72(6). 615–626. 19 indexed citations
18.
Tran, Jonathan Q., et al.. (2001). Delavirdine. Clinical Pharmacokinetics. 40(3). 207–226. 50 indexed citations
20.
Tran, Jonathan Q., Steven J. Kovacs, Thomas McIntosh, Hugh M. Davis, & David E. Martin. (1999). Morning Spot and 24‐Hour Urinary 6β‐Hydroxycortisol to Cortisol Ratios: Intraindividual Variability and Correlation under Basal Conditions and Conditions of CYP 3A4 Induction. The Journal of Clinical Pharmacology. 39(5). 487–494. 58 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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