Joseph M. Tonning
- Toxicology top 1%
- Computational Theory and Mathematics top 5%
- Molecular Biology
- Pharmacology
- Epidemiology
- Co-authors
- Ana SzarfmanJonathan G. LevineP. Murali DoraiswamyKirk RobertsDina Demner‐FushmanAlfred SorbelloVaishali PatadiaSusan T. Sacks
- Topics
- Pharmacovigilance and Adverse Drug Reactions (9 papers)Computational Drug Discovery Methods (4 papers)Biomedical Text Mining and Ontologies (3 papers)
- Journals
- SHILAP Revista de lepidopterologíaScientific DataDrug Safety
- Partner nations
- United StatesUnited KingdomThailand
In The Last Decade
Joseph M. Tonning
13 papers receiving 483 citations
Peers
Comparison fields: 5 of 102
- Toxicology 196
- Computational Theory and Mathematics 98
- Molecular Biology 97
- Pharmacology 75
- Epidemiology 58
Countries citing papers authored by Joseph M. Tonning
This map shows the geographic impact of Joseph M. Tonning'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 Joseph M. Tonning with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joseph M. Tonning more than expected).
Fields of papers citing papers by Joseph M. Tonning
This network shows the impact of papers produced by Joseph M. Tonning. 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 Joseph M. Tonning. The network helps show where Joseph M. Tonning may publish in the future.
Co-authorship network of co-authors of Joseph M. Tonning
This figure shows the co-authorship network connecting the top 25 collaborators of Joseph M. Tonning. A scholar is included among the top collaborators of Joseph M. Tonning 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 Joseph M. Tonning. Joseph M. Tonning is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 22 | |
| 2 | 15 | |
| 3 | Adverse Reactions and Drug-Drug Interaction Extraction tracks at the Text Analysis Conference (TAC). | 1 |
| 4 | 38 | |
| 5 | Overview of the TAC 2017 Adverse Reaction Extraction from Drug Labels Track. | 27 |
| 6 | 7 | |
| 7 | 5 | |
| 8 | 18 | |
| 9 | 1 | |
| 10 | 29 | |
| 11 | 61 | |
| 12 | 106 | |
| 13 | 173 |
About Joseph M. Tonning
Joseph M. Tonning is a scholar working on Toxicology, Health Informatics and Computational Theory and Mathematics, having authored 13 papers that have together received 503 indexed citations. Recurring topics across this work include Pharmacovigilance and Adverse Drug Reactions (9 papers), Computational Drug Discovery Methods (4 papers) and Biomedical Text Mining and Ontologies (3 papers). The work is most often cited by research in Toxicology (196 citations), Computational Theory and Mathematics (98 citations) and Statistics and Probability (48 citations). Joseph M. Tonning has collaborated with scholars based in United States, United Kingdom and Thailand. Frequent co-authors include Ana Szarfman, Jonathan G. Levine, P. Murali Doraiswamy, Kirk Roberts, Dina Demner‐Fushman, Alfred Sorbello, Vaishali Patadia, Susan T. Sacks, Nancy Yuen and Louisa Walsh. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Data and Drug Safety.
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.