Valère Lounnas

1.9k citations
21 papers · 1.6k indexed · h-index 16
Topics
Protein Structure and Dynamics (6 papers)Computational Drug Discovery Methods (6 papers)Pharmacogenetics and Drug Metabolism (6 papers)

In The Last Decade

Valère Lounnas

21 papers receiving 1.6k citations

Peers

Valère Lounnas
Comparison fields: 5 of 124
  • Molecular Biology 1.1k
  • Materials Chemistry 320
  • Computational Theory and Mathematics 301
  • Pharmacology 268
  • Atomic and Molecular Physics, and Optics 236
Replace K. Anton Feenstra with:
K. Anton Feenstra Netherlands
Peter J. Winn United Kingdom
Chaya S. Rapp United States
Joseph W. Kaus United States
Hwangseo Park South Korea
Lada Biedermannová Czechia
Paul D. Lyne United States
Kara E. Ranaghan United Kingdom
Devleena Shivakumar United States
Valère Lounnas relative to K. Anton Feenstra Netherlands K. Anton Feenstra's profile →
Citations per field
00.5×1.5×
K. Anton Feenstra · 1×
Citations per year

Countries citing papers authored by Valère Lounnas

Since Specialization
Citations

This map shows the geographic impact of Valère Lounnas'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 Valère Lounnas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Valère Lounnas more than expected).

Fields of papers citing papers by Valère Lounnas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Valère Lounnas. 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 Valère Lounnas. The network helps show where Valère Lounnas may publish in the future.

Co-authorship network of co-authors of Valère Lounnas

This figure shows the co-authorship network connecting the top 25 collaborators of Valère Lounnas. A scholar is included among the top collaborators of Valère Lounnas 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 Valère Lounnas. Valère Lounnas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 3
2 2
3 9
4 149
5 30
6 5
7 153
8 122
9 18
10 272
11 50
12 46
13 108
14 157
15 54
16 86
17 141
18 66
19 96
20 27

About Valère Lounnas

Valère Lounnas is a scholar working on Pharmacology, Molecular Medicine and Computational Theory and Mathematics, having authored 21 papers that have together received 1.6k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (6 papers), Computational Drug Discovery Methods (6 papers) and Pharmacogenetics and Drug Metabolism (6 papers). The work is most often cited by research in Pharmacology (268 citations), Computational Theory and Mathematics (301 citations) and Molecular Biology (1.1k citations). Valère Lounnas has collaborated with scholars based in Germany, United States and Netherlands. Frequent co-authors include Rebecca C. Wade, Susanna K. Lüdemann, B. Montgomery Pettitt, G.N. Phillips, Razif R. Gabdoulline, Peter J. Winn, Ralph Gauges, Ross McGuire, Robert P. Bywater and Tina Ritschel. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Molecular Biology and Biochemistry.

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.

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