Preeti Iyer
- Computational Theory and Mathematics top 2%
- Molecular Biology
- Public Health, Environmental and Occupational Health
- Materials Chemistry
- General Health Professions
- Co-authors
- Jürgen BajorathJeongyoung ParkXinxin HanClese EriksonLisa PeltasonMartin VogtDilyana DimovaOla Engkvist
- Topics
- Computational Drug Discovery Methods (15 papers)Machine Learning in Materials Science (5 papers)Plant biochemistry and biosynthesis (5 papers)
- Cited by
- Computational Theory and MathematicsPublic Health, Environmental and Occupational HealthGeneral Health Professions
- Partner nations
- GermanyUnited StatesUnited Kingdom
In The Last Decade
Preeti Iyer
24 papers receiving 447 citations
Peers
Comparison fields: 5 of 98
- Computational Theory and Mathematics 223
- Molecular Biology 192
- Public Health, Environmental and Occupational Health 109
- Materials Chemistry 85
- General Health Professions 73
Countries citing papers authored by Preeti Iyer
This map shows the geographic impact of Preeti Iyer'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 Preeti Iyer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Preeti Iyer more than expected).
Fields of papers citing papers by Preeti Iyer
This network shows the impact of papers produced by Preeti Iyer. 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 Preeti Iyer. The network helps show where Preeti Iyer may publish in the future.
Co-authorship network of co-authors of Preeti Iyer
This figure shows the co-authorship network connecting the top 25 collaborators of Preeti Iyer. A scholar is included among the top collaborators of Preeti Iyer 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 Preeti Iyer. Preeti Iyer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 28 | |
| 2 | 9 | |
| 3 | 22 | |
| 4 | 27 | |
| 5 | 10 | |
| 6 | 110 | |
| 7 | 2 | |
| 8 | 20 | |
| 9 | 20 | |
| 10 | 8 | |
| 11 | 14 | |
| 12 | 8 | |
| 13 | 23 | |
| 14 | 19 | |
| 15 | 11 | |
| 16 | 8 | |
| 17 | 8 | |
| 18 | 16 | |
| 19 | 4 | |
| 20 | 10 |
About Preeti Iyer
Preeti Iyer is a scholar working on Computational Theory and Mathematics, Pharmacology and Molecular Biology, having authored 24 papers that have together received 456 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (15 papers), Machine Learning in Materials Science (5 papers) and Plant biochemistry and biosynthesis (5 papers). The work is most often cited by research in Computational Theory and Mathematics (223 citations), Public Health, Environmental and Occupational Health (109 citations) and General Health Professions (73 citations). Preeti Iyer has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include Jürgen Bajorath, Jeongyoung Park, Xinxin Han, Clese Erikson, Lisa Peltason, Martin Vogt, Dilyana Dimova, Ola Engkvist, Vigneshwaran Namasivayam and Dagmar Stumpfe. Their work appears in journals such as International Journal of Molecular Sciences, Journal of Medicinal Chemistry and eLife.
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.