Justin Earp
Impact in
- Pharmacology top 5%
- Pharmacogenetics and Drug Metabolism
- Statistics and Probability top 5%
- Statistical Methods in Clinical Trials
Papers in
- Pharmacology 16
- Pharmacogenetics and Drug Metabolism 14
-
- Statistical Methods in Clinical Trials 11
- Co-authors
- William J. JuskoJane P. F. BaiDebra C. DuBoisRichard R. AlmonHao ZhuNancy A. PyszczynskiYaning WangVenkateswaran C. Pillai
- Journals
- The Journal of Clinical Pharmacology (7 papers)Clinical Pharmacology & Therapeutics (4 papers)CPT Pharmacometrics & Systems Pharmacology (4 papers)Clinical Cancer Research (3 papers)The AAPS Journal (3 papers)
- Partner nations
- United StatesNetherlandsSweden
In The Last Decade
Justin Earp
34 papers receiving 805 citations
Peers
Comparison fields: 5 of 101
- Pharmacology 156
- Statistics and Probability 124
- Pediatrics, Perinatology and Child Health 146
- Immunology 151
- Genetics 73
Countries citing papers authored by Justin Earp
This map shows the geographic impact of Justin Earp'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 Justin Earp with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Justin Earp more than expected).
Fields of papers citing papers by Justin Earp
This network shows the impact of papers produced by Justin Earp. 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 Justin Earp. The network helps show where Justin Earp may publish in the future.
Co-authors
The 25 scholars most cited alongside Justin Earp, 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 | 2024 | 7 | |
| 2 | 2023 | 0 | |
| 3 | 2023 | 5 | |
| 4 | 2021 | 13 | |
| 5 | 2021 | 27 | |
| 6 | 2021 | 16 | |
| 7 | 2019 | 41 | |
| 8 | 2018 | 15 | |
| 9 | 2017 | 7 | |
| 10 | 2016 | 58 | |
| 11 | 2016 | 21 | |
| 12 | 2013 | 33 | |
| 13 | 2011 | 112 | |
| 14 | 2008 | 27 | |
| 15 | 2008 | 55 | |
| 16 | 2008 | 28 | |
| 17 | 2008 | 14 | |
| 18 | 2008 | 41 | |
| 19 | 2006 | 1 | |
| 20 | 2004 | 39 |
About Justin Earp
Justin Earp is a scholar working on Pharmacology, Statistics and Probability, Computational Theory and Mathematics, Pediatrics, Perinatology and Child Health and Infectious Diseases, having authored 36 papers that have together received 829 indexed citations. Recurring topics across this work include Pharmacogenetics and Drug Metabolism (14 papers), Statistical Methods in Clinical Trials (11 papers), Pharmaceutical studies and practices (8 papers), Computational Drug Discovery Methods (7 papers), Cytokine Signaling Pathways and Interactions (4 papers), SARS-CoV-2 and COVID-19 Research (3 papers), COVID-19 Clinical Research Studies (3 papers) and Retinoids in leukemia and cellular processes (3 papers). The work is most often cited by research in Pharmacology (156 citations), Statistics and Probability (124 citations), Pediatrics, Perinatology and Child Health (146 citations), Immunology (151 citations) and Genetics (73 citations). Justin Earp has collaborated with scholars based in United States, Netherlands and Sweden. Frequent co-authors include William J. Jusko, Jane P. F. Bai, Debra C. DuBois, Richard R. Almon, Hao Zhu, Nancy A. Pyszczynski, Yaning Wang, Venkateswaran C. Pillai, Nitin Mehrotra and Kevin Krudys. Their work appears in journals such as The Journal of Clinical Pharmacology, Clinical Pharmacology & Therapeutics, CPT Pharmacometrics & Systems Pharmacology, Clinical Cancer Research and The AAPS Journal.
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.