Paul Baverel
Impact in
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- Cancer Immunotherapy and Biomarkers
- CAR-T cell therapy research
- Statistics and Probability top 10%
- Statistical Methods in Clinical Trials
Papers in
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- Statistical Methods in Clinical Trials 3
- Statistical Methods and Bayesian Inference 2
- Co-authors
- Lorin K. Roskos (5 shared papers)Rajesh Narwal (3 shared papers)Ashley A. Woodcock (1 shared paper)John A. Smith (1 shared paper)Piet H. van der Graaf (1 shared paper)Paolo Vicini (5 shared papers)Pralay Mukhopadhyay (2 shared papers)Ashok Kumar Gupta (2 shared papers)
- Journals
- CPT Pharmacometrics & Systems Pharmacology (3 papers)Clinical Pharmacology & Therapeutics (3 papers)British Journal of Clinical Pharmacology (1 paper)Clinical and Translational Science (1 paper)Pharmaceutics (1 paper)
- Partner nations
- United StatesUnited KingdomSwitzerland
In The Last Decade
Paul Baverel
19 papers receiving 465 citations
Peers
Comparison fields: 5 of 62
- Oncology 159
- Statistics and Probability 51
- Pulmonary and Respiratory Medicine 123
- Sensory Systems 18
- Immunology 75
Countries citing papers authored by Paul Baverel
This map shows the geographic impact of Paul Baverel'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 Paul Baverel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paul Baverel more than expected).
Fields of papers citing papers by Paul Baverel
This network shows the impact of papers produced by Paul Baverel. 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 Paul Baverel. The network helps show where Paul Baverel may publish in the future.
Co-authors
The 25 scholars most cited alongside Paul Baverel, 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 | 2017 | 131 | |
| 2 | 2013 | 80 | |
| 3 | 2017 | 48 | |
| 4 | 2019 | 39 | |
| 5 | 2023 | 35 | |
| 6 | 2015 | 24 | |
| 7 | 2019 | 19 | |
| 8 | 2022 | 18 | |
| 9 | 2017 | 15 | |
| 10 | 2021 | 13 | |
| 11 | 2021 | 11 | |
| 12 | 2017 | 10 | |
| 13 | 2022 | 10 | |
| 14 | 2010 | 9 | |
| 15 | 2009 | 7 | |
| 16 | 2021 | 7 | |
| 17 | 2021 | 4 | |
| 18 | 2018 | 1 | |
| 19 | 2026 | 1 |
About Paul Baverel
Paul Baverel is a scholar working on Statistics and Probability, Pulmonary and Respiratory Medicine, Oncology, Occupational Therapy and Cancer Research, having authored 19 papers that have together received 482 indexed citations. Recurring topics across this work include Cancer Immunotherapy and Biomarkers (4 papers), Statistical Methods in Clinical Trials (3 papers), Asthma and respiratory diseases (3 papers), Cancer Genomics and Diagnostics (2 papers), Monoclonal and Polyclonal Antibodies Research (2 papers), Statistical Methods and Bayesian Inference (2 papers), Safe Handling of Antineoplastic Drugs (2 papers) and Pharmaceutical studies and practices (2 papers). The work is most often cited by research in Oncology (159 citations), Statistics and Probability (51 citations), Pulmonary and Respiratory Medicine (123 citations), Sensory Systems (18 citations) and Immunology (75 citations). Paul Baverel has collaborated with scholars based in United States, United Kingdom and Switzerland. Frequent co-authors include Lorin K. Roskos, Rajesh Narwal, Ashley A. Woodcock, John A. Smith, Piet H. van der Graaf, Paolo Vicini, Pralay Mukhopadhyay, Ashok Kumar Gupta, Xiaoping Jin and Yong Ben. Their work appears in journals such as CPT Pharmacometrics & Systems Pharmacology, Clinical Pharmacology & Therapeutics, British Journal of Clinical Pharmacology, Clinical and Translational Science and Pharmaceutics.
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.