Nicholas P. Tatonetti
- Molecular Biology top 2%
- Computational Theory and Mathematics top 0.2%
- Pulmonary and Respiratory Medicine top 2%
- Cancer Research top 2%
- Toxicology top 0.05%
- Co-authors
- Russ B. AltmanScott J. DixonRoxana DaneshjouMiki HayanoBrent R. StockwellEric D. LeeSantiago VilarCaroline E. Gleason
- Topics
- Computational Drug Discovery Methods (32 papers)Pharmacovigilance and Adverse Drug Reactions (27 papers)Biomedical Text Mining and Ontologies (18 papers)
- Partner nations
- United StatesSpainUnited Kingdom
In The Last Decade
Nicholas P. Tatonetti
139 papers receiving 6.7k citations
Hit Papers
Peers
Comparison fields: 5 of 178
- Molecular Biology 2.9k
- Computational Theory and Mathematics 1.6k
- Pulmonary and Respiratory Medicine 1.3k
- Cancer Research 970
- Toxicology 808
Countries citing papers authored by Nicholas P. Tatonetti
This map shows the geographic impact of Nicholas P. Tatonetti'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 Nicholas P. Tatonetti with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nicholas P. Tatonetti more than expected).
Fields of papers citing papers by Nicholas P. Tatonetti
This network shows the impact of papers produced by Nicholas P. Tatonetti. 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 Nicholas P. Tatonetti. The network helps show where Nicholas P. Tatonetti may publish in the future.
Co-authorship network of co-authors of Nicholas P. Tatonetti
This figure shows the co-authorship network connecting the top 25 collaborators of Nicholas P. Tatonetti. A scholar is included among the top collaborators of Nicholas P. Tatonetti 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 Nicholas P. Tatonetti. Nicholas P. Tatonetti 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 | 0 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 7 | |
| 6 | 1 | |
| 7 | 4 | |
| 8 | 9 | |
| 9 | 3 | |
| 10 | 3 | |
| 11 | 30 | |
| 12 | 282 | |
| 13 | 38 | |
| 14 | 3 | |
| 15 | Abstract 19311: Identification of Novel Primary Graft Dysfunction Biomarkers Using Exosome Proteomics | 2 |
| 16 | 106 | |
| 17 | 161 | |
| 18 | 65 | |
| 19 | 16 | |
| 20 | 39 |
About Nicholas P. Tatonetti
Nicholas P. Tatonetti is a scholar working on Toxicology, Health Informatics and Computational Theory and Mathematics, having authored 152 papers that have together received 6.8k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (32 papers), Pharmacovigilance and Adverse Drug Reactions (27 papers) and Biomedical Text Mining and Ontologies (18 papers). The work is most often cited by research in Toxicology (808 citations), Computational Theory and Mathematics (1.6k citations) and Health Informatics (101 citations). Nicholas P. Tatonetti has collaborated with scholars based in United States, Spain and United Kingdom. Frequent co-authors include Russ B. Altman, Scott J. Dixon, Roxana Daneshjou, Miki Hayano, Brent R. Stockwell, Eric D. Lee, Santiago Vilar, Caroline E. Gleason, Barbara S. Slusher and Matthew Welsch. Their work appears in journals such as Cell, Proceedings of the National Academy of Sciences and Circulation.
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.