Michaël Moret

1.8k total citations
17 papers, 1.0k citations indexed

About

Michaël Moret is a scholar working on Molecular Biology, Computational Theory and Mathematics and Materials Chemistry. According to data from OpenAlex, Michaël Moret has authored 17 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 7 papers in Computational Theory and Mathematics and 5 papers in Materials Chemistry. Recurrent topics in Michaël Moret's work include Computational Drug Discovery Methods (7 papers), Machine Learning in Materials Science (4 papers) and Chemical Synthesis and Analysis (3 papers). Michaël Moret is often cited by papers focused on Computational Drug Discovery Methods (7 papers), Machine Learning in Materials Science (4 papers) and Chemical Synthesis and Analysis (3 papers). Michaël Moret collaborates with scholars based in Switzerland, Netherlands and Germany. Michaël Moret's co-authors include Gisbert Schneider, Francesca Grisoni, Daniel Merk, Lukas Friedrich, Peter J. Wild, Niels J. Rupp, Eirini Arvaniti, Thomas Hermanns, Christian D. Fankhauser and Manfred Claassen and has published in prestigious journals such as Angewandte Chemie International Edition, Nature Communications and Nature Biotechnology.

In The Last Decade

Michaël Moret

15 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Michaël Moret Switzerland	12	418	398	290	260	170	17	1.0k
Neel S. Madhukar United States	11	255 0.6×	523 1.3×	103 0.4×	185 0.7×	232 1.4×	28	1.2k
Coryandar Gilvary United States	5	211 0.5×	264 0.7×	107 0.4×	183 0.7×	210 1.2×	5	757
Isidro Cortés‐Ciriano United Kingdom	26	874 2.1×	1.3k 3.3×	329 1.1×	126 0.5×	73 0.4×	63	2.3k
Michael P. Menden Germany	15	489 1.2×	677 1.7×	68 0.2×	86 0.3×	67 0.4×	41	1.2k
Xiaozhe Wan China	10	681 1.6×	575 1.4×	458 1.6×	89 0.3×	25 0.1×	14	1.2k
Samson Fong United States	7	230 0.6×	510 1.3×	67 0.2×	109 0.4×	56 0.3×	11	790
Somayah Albaradei Saudi Arabia	11	263 0.6×	361 0.9×	85 0.3×	69 0.3×	60 0.4×	28	604
Jiahua Rao China	10	256 0.6×	434 1.1×	158 0.5×	131 0.5×	40 0.2×	24	641
Petr Smirnov Canada	14	353 0.8×	636 1.6×	61 0.2×	65 0.3×	52 0.3×	25	969
Santosh Putta United States	17	388 0.9×	437 1.1×	147 0.5×	72 0.3×	42 0.2×	38	858

Countries citing papers authored by Michaël Moret

Since Specialization

Citations

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

Fields of papers citing papers by Michaël Moret

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michaël Moret

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

All Works

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17 of 17 papers shown

Ferreira, Raphaël, et al.. (2025). Engineered base editors with reduced bystander editing through directed evolution. Nature Biotechnology.

Appleton, Evan, Noushin Mehdipour, Iman Haghighi, et al.. (2024). Algorithms for Autonomous Formation of Multicellular Shapes from Single Cells. ACS Synthetic Biology. 13(9). 2753–2763.

Moret, Michaël, et al.. (2024). Generative machine learning produces kinetic models that accurately characterize intracellular metabolic states. Nature Catalysis. 7(10). 1086–1098. 16 indexed citations

Moret, Michaël, Leandro Cotos, Kenneth Atz, et al.. (2023). Leveraging molecular structure and bioactivity with chemical language models for de novo drug design. Nature Communications. 14(1). 114–114. 95 indexed citations

Moret, Michaël, et al.. (2022). Reconstructing Kinetic Models for Dynamical Studies of Metabolism using Generative Adversarial Networks. Nature Machine Intelligence. 4(8). 710–719. 41 indexed citations

Moret, Michaël, et al.. (2022). Perplexity-Based Molecule Ranking and Bias Estimation of Chemical Language Models. Journal of Chemical Information and Modeling. 62(5). 1199–1206. 15 indexed citations

Grisoni, Francesca, Alexander L. Button, Michaël Moret, et al.. (2021). Combining generative artificial intelligence and on-chip synthesis for de novo drug design. Science Advances. 7(24). 103 indexed citations

Moret, Michaël, et al.. (2021). Beam Search for Automated Design and Scoring of Novel ROR Ligands with Machine Intelligence**. Angewandte Chemie International Edition. 60(35). 19477–19482. 56 indexed citations

Moret, Michaël, et al.. (2021). Beam‐Search zum automatisierten Entwurf und Scoring neuer ROR‐Liganden mithilfe maschineller Intelligenz**. Angewandte Chemie. 133(35). 19626–19632. 1 indexed citations

10.

Moret, Michaël, Lukas Friedrich, Francesca Grisoni, Daniel Merk, & Gisbert Schneider. (2020). Generative molecular design in low data regimes. Nature Machine Intelligence. 2(3). 171–180. 142 indexed citations

11.

Grisoni, Francesca, et al.. (2020). Bidirectional Molecule Generation with Recurrent Neural Networks. Journal of Chemical Information and Modeling. 60(3). 1175–1183. 147 indexed citations

12.

Mišković, Ljubiša, et al.. (2019). Uncertainty reduction in biochemical kinetic models: Enforcing desired model properties. PLoS Computational Biology. 15(8). e1007242–e1007242. 18 indexed citations

13.

Arvaniti, Eirini, Michaël Moret, Niels J. Rupp, et al.. (2018). Automated Gleason grading of prostate cancer tissue microarrays via deep learning. Scientific Reports. 8(1). 12054–12054. 269 indexed citations

14.

Arvaniti, Eirini, Michaël Moret, Niels J. Rupp, et al.. (2018). Automated Gleason grading of prostate cancer via deep learning. European Urology Supplements. 17(14). e3020–e3021. 3 indexed citations

15.

Soekarman, D, J van Denderen, L. H. Hoefsloot, et al.. (1990). A novel variant of the bcr-abl fusion product in Philadelphia chromosome-positive acute lymphoblastic leukemia.. PubMed. 4(6). 397–403. 45 indexed citations

16.

Hagemeijer, A, et al.. (1990). Cytogenetic analysis of malignant mesothelioma. Cancer Genetics and Cytogenetics. 47(1). 1–28. 79 indexed citations

17.

Hagemeijer, A., et al.. (1989). 124 Cytogenetic analysis of malignant mesotheliomas. Cancer Genetics and Cytogenetics. 38(2). 200–200. 1 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.

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