David Rouquié
- Molecular Biology top 10%
- Plant Science top 5%
- Computational Theory and Mathematics top 2%
- Materials Chemistry
- Health, Toxicology and Mutagenesis top 10%
- Co-authors
- Eva BenkováIkram BlilouBen ScheresJustyna WiśniewskaPhilip B. BrewerDaniela SeifertováKamil RůžičkaJian Xu
- Topics
- Computational Drug Discovery Methods (9 papers)Effects and risks of endocrine disrupting chemicals (6 papers)Estrogen and related hormone effects (6 papers)
- Journals
- ScienceNature CommunicationsPLoS ONE
- Partner nations
- FranceGermanyUnited States
In The Last Decade
David Rouquié
27 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 108
- Molecular Biology 909
- Plant Science 804
- Computational Theory and Mathematics 214
- Materials Chemistry 130
- Health, Toxicology and Mutagenesis 80
Countries citing papers authored by David Rouquié
This map shows the geographic impact of David Rouquié'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 David Rouquié with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Rouquié more than expected).
Fields of papers citing papers by David Rouquié
This network shows the impact of papers produced by David Rouquié. 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 David Rouquié. The network helps show where David Rouquié may publish in the future.
Co-authorship network of co-authors of David Rouquié
This figure shows the co-authorship network connecting the top 25 collaborators of David Rouquié. A scholar is included among the top collaborators of David Rouquié 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 David Rouquié. David Rouquié is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 10 | |
| 3 | 12 | |
| 4 | 12 | |
| 5 | 19 | |
| 6 | De novo generation of hit-like molecules from gene expression signatures using artificial intelligencebreakdown → | 283 |
| 7 | 19 | |
| 8 | 25 | |
| 9 | 32 | |
| 10 | 35 | |
| 11 | 15 | |
| 12 | 5 | |
| 13 | 20 | |
| 14 | 13 | |
| 15 | 25 | |
| 16 | 14 | |
| 17 | 22 | |
| 18 | 17 | |
| 19 | 91 | |
| 20 | 21 |
About David Rouquié
David Rouquié is a scholar working on Computational Theory and Mathematics, Small Animals and Biophysics, having authored 27 papers that have together received 1.4k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (9 papers), Effects and risks of endocrine disrupting chemicals (6 papers) and Estrogen and related hormone effects (6 papers). The work is most often cited by research in Plant Science (804 citations), Computational Theory and Mathematics (214 citations) and Molecular Biology (909 citations). David Rouquié has collaborated with scholars based in France, Germany and United States. Frequent co-authors include Eva Benková, Ikram Blilou, Ben Scheres, Justyna Wiśniewska, Philip B. Brewer, Daniela Seifertová, Kamil Růžička, Jian Xu, Jiřı́ Friml and Joerg Wichard. Their work appears in journals such as Science, Nature Communications and PLoS ONE.
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.