Yann Gaston‐Mathé

591 total citations
13 papers, 259 citations indexed

About

Yann Gaston‐Mathé is a scholar working on Computational Theory and Mathematics, Materials Chemistry and Molecular Biology. According to data from OpenAlex, Yann Gaston‐Mathé has authored 13 papers receiving a total of 259 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computational Theory and Mathematics, 6 papers in Materials Chemistry and 5 papers in Molecular Biology. Recurrent topics in Yann Gaston‐Mathé's work include Machine Learning in Materials Science (6 papers), Computational Drug Discovery Methods (6 papers) and Colorectal Cancer Treatments and Studies (4 papers). Yann Gaston‐Mathé is often cited by papers focused on Machine Learning in Materials Science (6 papers), Computational Drug Discovery Methods (6 papers) and Colorectal Cancer Treatments and Studies (4 papers). Yann Gaston‐Mathé collaborates with scholars based in France, United States and Austria. Yann Gaston‐Mathé's co-authors include Brice Hoffmann, Nicholas G. Martin, Didier Rognan, Raphaële Thiébaut, Andreas Jung, Pierre Laurent‐Puig, D. Machover, Patricia Sansilvestri‐Morel, Christophe Desterke and Pierre Ducrot and has published in prestigious journals such as Scientific Reports, Clinical Cancer Research and Journal of Medicinal Chemistry.

In The Last Decade

Yann Gaston‐Mathé

13 papers receiving 256 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Yann Gaston‐Mathé France 7 160 147 73 31 29 13 259
Jieyu Lü China 11 193 1.2× 67 0.5× 73 1.0× 31 1.0× 129 4.4× 26 449
Yoshiaki Washio United Kingdom 8 192 1.2× 51 0.3× 20 0.3× 50 1.6× 12 0.4× 11 373
Eric Gonzalez United States 10 108 0.7× 36 0.2× 19 0.3× 65 2.1× 32 1.1× 12 307
Nathan O. Fuller United States 10 161 1.0× 55 0.4× 11 0.2× 45 1.5× 36 1.2× 18 330
Adriana Stroba Germany 6 342 2.1× 52 0.4× 29 0.4× 34 1.1× 19 0.7× 6 407
Prabha Karnachi United States 10 163 1.0× 90 0.6× 39 0.5× 123 4.0× 65 2.2× 12 310
Lan Shen United States 12 241 1.5× 34 0.2× 12 0.2× 68 2.2× 46 1.6× 23 532
Dušan Ružić Serbia 11 235 1.5× 85 0.6× 56 0.8× 56 1.8× 12 0.4× 24 366
Rebecca A. Gallego United States 4 157 1.0× 59 0.4× 13 0.2× 46 1.5× 13 0.4× 5 267
Rémy Morgentin United Kingdom 10 167 1.0× 53 0.4× 11 0.2× 21 0.7× 13 0.4× 14 298

Countries citing papers authored by Yann Gaston‐Mathé

Since Specialization
Citations

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

Fields of papers citing papers by Yann Gaston‐Mathé

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yann Gaston‐Mathé. 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 Yann Gaston‐Mathé. The network helps show where Yann Gaston‐Mathé may publish in the future.

Co-authorship network of co-authors of Yann Gaston‐Mathé

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

All Works

13 of 13 papers shown
1.
Gaston‐Mathé, Yann, et al.. (2023). Exploring isofunctional molecules: Design of a benchmark and evaluation of prediction performance. Molecular Informatics. 42(4). e2200216–e2200216. 2 indexed citations
2.
Gaston‐Mathé, Yann, et al.. (2023). Integrating synthetic accessibility with AI-based generative drug design. Journal of Cheminformatics. 15(1). 83–83. 27 indexed citations
3.
Gaston‐Mathé, Yann, et al.. (2023). Molecular Assays Simulator to Unravel Predictors Hacking in Goal-Directed Molecular Generations. Journal of Chemical Information and Modeling. 63(13). 3983–3998. 4 indexed citations
4.
Gaston‐Mathé, Yann, et al.. (2022). Key points to succeed in Artificial Intelligence drug discovery projects. Chemistry International. 44(1). 19–21. 2 indexed citations
5.
Martin, Nicholas G., et al.. (2022). On the Frustration to Predict Binding Affinities from Protein–Ligand Structures with Deep Neural Networks. Journal of Medicinal Chemistry. 65(11). 7946–7958. 108 indexed citations
6.
Mirguet, Olivier, Arnaud Gohier, Pierre Ducrot, et al.. (2022). Deep generative models for ligand‐based de novo design applied to multi‐parametric optimization. Journal of Computational Chemistry. 43(10). 692–703. 36 indexed citations
7.
Machover, D., Emma Goldschmidt, Vincent Castagné, et al.. (2022). Pharmacologic modulation of 5-fluorouracil by folinic acid and pyridoxine for treatment of patients with advanced breast carcinoma. Scientific Reports. 12(1). 9079–9079. 3 indexed citations
8.
Machover, D., Vincent Castagné, Christophe Desterke, et al.. (2021). Pharmacologic modulation of 5-fluorouracil by folinic acid and high-dose pyridoxine for treatment of patients with digestive tract carcinomas. Scientific Reports. 11(1). 12668–12668. 4 indexed citations
9.
Machover, D., Luigia Rossi, J. HAMELIN, et al.. (2019). Effects in Cancer Cells of the Recombinant L-Methionine Gamma-Lyase from Brevibacterium aurantiacum. Encapsulation in Human Erythrocytes for Sustained L-Methionine Elimination. Journal of Pharmacology and Experimental Therapeutics. 369(3). 489–502. 23 indexed citations
10.
Laurent‐Puig, Pierre, Volker Heinemann, Daniel Neureiter, et al.. (2018). Validation of miR-31-3p Expression to Predict Cetuximab Efficacy When Used as First-Line Treatment in RAS Wild-Type Metastatic Colorectal Cancer. Clinical Cancer Research. 25(1). 134–141. 31 indexed citations
11.
Machover, D., Emma Goldschmidt, Rosella Mollicone, et al.. (2018). Enhancement of 5-Fluorouracil Cytotoxicity by Pyridoxal 5′-Phosphate and Folinic Acid in Tandem. Journal of Pharmacology and Experimental Therapeutics. 366(2). 238–243. 6 indexed citations
12.
13.
Fogel, Paul, et al.. (2016). Applications of a Novel Clustering Approach Using Non-Negative Matrix Factorization to Environmental Research in Public Health. International Journal of Environmental Research and Public Health. 13(5). 509–509. 3 indexed citations

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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Jieyu Lü Breakdown of academic impact, for papers by Yoshiaki Washio Breakdown of academic impact, for papers by Eric Gonzalez Breakdown of academic impact, for papers by Nathan O. Fuller Breakdown of academic impact, for papers by Adriana Stroba Breakdown of academic impact, for papers by Prabha Karnachi Breakdown of academic impact, for papers by Lan Shen Breakdown of academic impact, for papers by Dušan Ružić Breakdown of academic impact, for papers by Rebecca A. Gallego Breakdown of academic impact, for papers by Rémy Morgentin
Rankless by CCL
2026