Mason McComb
Impact in
- Statistics and Probability top 10%
- Statistical Methods in Clinical Trials
Papers in
-
- Metabolomics and Mass Spectrometry Studies 2
- Kruppel-like factors research 1
-
- Computational Drug Discovery Methods 3
- Co-authors
- Murali Ramanathan (6 shared papers)Robert R. Bies (1 shared paper)Jens Kühle (3 shared papers)Robert Zivadinov (3 shared papers)Niels Bergsland (2 shared papers)Barbora Srpová (1 shared paper)Christian Barro (1 shared paper)Eva Havrdová (1 shared paper)
- Journals
- Multiple Sclerosis and Related Disorders (2 papers)Journal of Pharmacokinetics and Pharmacodynamics (1 paper)British Journal of Clinical Pharmacology (1 paper)Frontiers in Immunology (1 paper)Clinical Pharmacology & Therapeutics (1 paper)
- Partner nations
- United StatesSwitzerlandItaly
In The Last Decade
Mason McComb
9 papers receiving 241 citations
Peers
Comparison fields: 5 of 73
- Statistics and Probability 41
- Health Informatics 4
- Pathology and Forensic Medicine 35
- Computational Theory and Mathematics 33
- Pharmacology 13
Countries citing papers authored by Mason McComb
This map shows the geographic impact of Mason McComb'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 Mason McComb with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mason McComb more than expected).
Fields of papers citing papers by Mason McComb
This network shows the impact of papers produced by Mason McComb. 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 Mason McComb. The network helps show where Mason McComb may publish in the future.
Co-authors
The 25 scholars most cited alongside Mason McComb, 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 | 2021 | 87 | |
| 2 | 2020 | 62 | |
| 3 | 2013 | 26 | |
| 4 | 2020 | 20 | |
| 5 | 2019 | 16 | |
| 6 | 2023 | 15 | |
| 7 | 2021 | 11 | |
| 8 | 2021 | 7 | |
| 9 | Nonlinear Mixed Effects Models in Population PK/PD [R package nlmixr version 2.0.4] | 2021 | 1 |
About Mason McComb
Mason McComb is a scholar working on Molecular Biology, Computational Theory and Mathematics, Pathology and Forensic Medicine, Statistics and Probability and Surgery, having authored 9 papers that have together received 245 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (3 papers), Metabolomics and Mass Spectrometry Studies (2 papers), Multiple Sclerosis Research Studies (2 papers), Statistical Methods in Clinical Trials (2 papers), Kruppel-like factors research (1 paper), Neurogenesis and neuroplasticity mechanisms (1 paper), Barrier Structure and Function Studies (1 paper) and Biosensors and Analytical Detection (1 paper). The work is most often cited by research in Statistics and Probability (41 citations), Health Informatics (4 citations), Pathology and Forensic Medicine (35 citations), Computational Theory and Mathematics (33 citations) and Pharmacology (13 citations). Mason McComb has collaborated with scholars based in United States, Switzerland and Italy. Frequent co-authors include Murali Ramanathan, Robert R. Bies, Jens Kühle, Robert Zivadinov, Niels Bergsland, Barbora Srpová, Christian Barro, Eva Havrdová, Tomáš Uher and Jan Krásenský. Their work appears in journals such as Multiple Sclerosis and Related Disorders, Journal of Pharmacokinetics and Pharmacodynamics, British Journal of Clinical Pharmacology, Frontiers in Immunology and Clinical Pharmacology & Therapeutics.
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.