Francois Berenger

511 citations
26 papers · 312 indexed · h-index 12
Topics
Computational Drug Discovery Methods (13 papers)Protein Structure and Dynamics (9 papers)Machine Learning in Materials Science (7 papers)
Partner nations
JapanUnited StatesChina

In The Last Decade

Francois Berenger

25 papers receiving 308 citations

Peers

Francois Berenger
Comparison fields: 5 of 68
  • Molecular Biology 239
  • Computational Theory and Mathematics 158
  • Materials Chemistry 124
  • Spectroscopy 24
  • Pharmacology 20
Replace Arkadii Lin with:
Arkadii Lin France
Yana Rose United States
Eric Allison Philot Brazil
Rick Oerlemans Netherlands
Oleksii Prykhodko Sweden
Gerhard Klebe Germany
Justas Dapkūnas Lithuania
A. Beatriz Garmendia-Doval United Kingdom
Ken Borrelli United States
Jens A. Fuchs Switzerland
Francois Berenger relative to Arkadii Lin France Arkadii Lin's profile →
Citations per field
00.5×6.5×
Arkadii Lin · 1×
Citations per year

Countries citing papers authored by Francois Berenger

Since Specialization
Citations

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

Fields of papers citing papers by Francois Berenger

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Francois Berenger

This figure shows the co-authorship network connecting the top 25 collaborators of Francois Berenger. A scholar is included among the top collaborators of Francois Berenger 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 Francois Berenger. Francois Berenger 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 5
2 1
3 0
4 3
5 14
6 47
7 16
8 2
9 6
10 3
11 17
12 11
13 4
14 20
15 23
16 16
17 34
18 2
19 16
20 13

About Francois Berenger

Francois Berenger is a scholar working on Computational Theory and Mathematics, Information Systems and Management and Molecular Biology, having authored 26 papers that have together received 312 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (13 papers), Protein Structure and Dynamics (9 papers) and Machine Learning in Materials Science (7 papers). The work is most often cited by research in Computational Theory and Mathematics (158 citations), Molecular Biology (239 citations) and Computational Mathematics (2 citations). Francois Berenger has collaborated with scholars based in Japan, United States and China. Frequent co-authors include Kam Y. J. Zhang, Yoshihiro Yamanishi, Ashutosh Kumar, Arnout Voet, Koji Tsuda, David Simoncini, Yong Zhou, Jens Meiler, M Iwata and Camille Coti. Their work appears in journals such as Bioinformatics, PLoS ONE and Journal of Computational Chemistry.

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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