Philip J. Brown
- Statistics and Probability top 0.2%
- Molecular Biology top 10%
- Immunology top 5%
- Artificial Intelligence top 2%
- Analytical Chemistry top 0.5%
- Co-authors
- Jim E. GriffinMarina VannucciTom FearnAlison H. BanhamLeon Jay GleserClive PayneJames V. ZidekJeffrey S. Morris
- Topics
- Advanced Statistical Methods and Models (33 papers)Spectroscopy and Chemometric Analyses (27 papers)Statistical Methods and Inference (22 papers)
- Partner nations
- United KingdomUnited StatesAustralia
In The Last Decade
Philip J. Brown
130 papers receiving 4.9k citations
Peers
Comparison fields: 5 of 208
- Statistics and Probability 1.4k
- Molecular Biology 829
- Immunology 740
- Artificial Intelligence 700
- Analytical Chemistry 621
Countries citing papers authored by Philip J. Brown
This map shows the geographic impact of Philip J. Brown'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 Philip J. Brown with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Philip J. Brown more than expected).
Fields of papers citing papers by Philip J. Brown
This network shows the impact of papers produced by Philip J. Brown. 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 Philip J. Brown. The network helps show where Philip J. Brown may publish in the future.
Co-authorship network of co-authors of Philip J. Brown
This figure shows the co-authorship network connecting the top 25 collaborators of Philip J. Brown. A scholar is included among the top collaborators of Philip J. Brown 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 Philip J. Brown. Philip J. Brown is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 3 | |
| 4 | 25 | |
| 5 | 34 | |
| 6 | 25 | |
| 7 | 8 | |
| 8 | 56 | |
| 9 | 80 | |
| 10 | 122 | |
| 11 | 30 | |
| 12 | 90 | |
| 13 | Principles of Post-coordination Concept Construction and Retrieval | 1 |
| 14 | 15 | |
| 15 | 37 | |
| 16 | Logistic discrimination with many variables | 3 |
| 17 | 42 | |
| 18 | 31 | |
| 19 | Statistical analysis of measurement error models and applications : proceedings of the AMS-IMS-SIAM Joint Summer Research conference held June 10-16, 1989, with support from the National Science Foundation and the U.S. Army Research Office | 6 |
| 20 | 10 |
About Philip J. Brown
Philip J. Brown is a scholar working on Statistics and Probability, Analytical Chemistry and Biophysics, having authored 134 papers that have together received 5.1k indexed citations. Recurring topics across this work include Advanced Statistical Methods and Models (33 papers), Spectroscopy and Chemometric Analyses (27 papers) and Statistical Methods and Inference (22 papers). The work is most often cited by research in Statistics and Probability (1.4k citations), Analytical Chemistry (621 citations) and Statistics, Probability and Uncertainty (260 citations). Philip J. Brown has collaborated with scholars based in United Kingdom, United States and Australia. Frequent co-authors include Jim E. Griffin, Marina Vannucci, Tom Fearn, Alison H. Banham, Leon Jay Gleser, Clive Payne, James V. Zidek, Jeffrey S. Morris, Bridget C. Fox and Rolf Sundberg. Their work appears in journals such as Journal of the American Statistical Association, Blood and Technometrics.
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.