Daniel Barth-Jones
- Infectious Diseases top 5%
- Epidemiology
- Computational Theory and Mathematics top 5%
- Artificial Intelligence top 10%
- Virology top 5%
- Co-authors
- Hao YingRodger D. MacArthurLawrence R. CraneJonathan CohnFeng LinMarcus ZervosJosé A. VázquezJack D. Sobel
- Topics
- Formal Methods in Verification (6 papers)Distributed systems and fault tolerance (5 papers)Petri Nets in System Modeling (5 papers)
- Journals
- The American Journal of MedicineJournal of Clinical MicrobiologyThe American Journal of Cardiology
- Partner nations
- United StatesChinaIndia
In The Last Decade
Daniel Barth-Jones
24 papers receiving 737 citations
Peers
Comparison fields: 5 of 106
- Infectious Diseases 342
- Epidemiology 227
- Computational Theory and Mathematics 173
- Artificial Intelligence 127
- Virology 115
Countries citing papers authored by Daniel Barth-Jones
This map shows the geographic impact of Daniel Barth-Jones'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 Daniel Barth-Jones with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Barth-Jones more than expected).
Fields of papers citing papers by Daniel Barth-Jones
This network shows the impact of papers produced by Daniel Barth-Jones. 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 Daniel Barth-Jones. The network helps show where Daniel Barth-Jones may publish in the future.
Co-authorship network of co-authors of Daniel Barth-Jones
This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Barth-Jones. A scholar is included among the top collaborators of Daniel Barth-Jones 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 Daniel Barth-Jones. Daniel Barth-Jones is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 48 | |
| 2 | 79 | |
| 3 | 56 | |
| 4 | 14 | |
| 5 | 1 | |
| 6 | 7 | |
| 7 | 14 | |
| 8 | 10 | |
| 9 | 19 | |
| 10 | 11 | |
| 11 | 17 | |
| 12 | 5 | |
| 13 | 8 | |
| 14 | 5 | |
| 15 | The Retrospective Partner Trials (RPT) HIV vaccine study design for the measurement of vaccine effects on susceptibility and infectiousness. | 3 |
| 16 | 18 | |
| 17 | 30 | |
| 18 | 184 | |
| 19 | 108 | |
| 20 | 0 |
About Daniel Barth-Jones
Daniel Barth-Jones is a scholar working on Toxicology, Virology and Computational Theory and Mathematics, having authored 25 papers that have together received 776 indexed citations. Recurring topics across this work include Formal Methods in Verification (6 papers), Distributed systems and fault tolerance (5 papers) and Petri Nets in System Modeling (5 papers). The work is most often cited by research in Virology (115 citations), Infectious Diseases (342 citations) and Computational Theory and Mathematics (173 citations). Daniel Barth-Jones has collaborated with scholars based in United States, China and India. Frequent co-authors include Hao Ying, Rodger D. MacArthur, Lawrence R. Crane, Jonathan Cohn, Feng Lin, Marcus Zervos, José A. Vázquez, Jack D. Sobel, Verónica Sánchez and James S. Koopman. Their work appears in journals such as The American Journal of Medicine, Journal of Clinical Microbiology and The American Journal of Cardiology.
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.