Michaël Moret

1.8k citations
17 papers · 1.0k · h-index 12

Impact in

Papers in

Michaël Moret

15 papers receiving 1.0k citations

Peers

Michaël Moret
Comparison fields: 5 of 103
  • Health Informatics 39
  • Computational Theory and Mathematics 418
  • Artificial Intelligence 260
  • Radiology, Nuclear Medicine and Imaging 170
  • Biophysics 40
Replace Neel S. Madhukar with:
Neel S. Madhukar United States
Isidro Cortés‐Ciriano United Kingdom
Michael P. Menden Germany
Samson Fong United States
Petr Smirnov Canada
Coryandar Gilvary United States
Artur Kadurin Russia
Ladislav Rampášek Canada
Jiasheng Cao China
Zhaleh Safikhani Canada
Michaël Moret relative to Neel S. Madhukar United States Neel S. Madhukar's profile →
Citations per field
00.5×1.6×
Neel S. Madhukar · 1×
Citations per year

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-authors

The 25 scholars most cited alongside Michaël Moret, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Michaël Moret Line = papers co-authored together Michaël Moret links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1 2018269
2 2020147
3 2020142
4 2021103
5 202395
6 199079
7 202156
8
A novel variant of the bcr-abl fusion product in Philadelphia chromosome-positive acute lymphoblastic leukemia.
199045
9 202241
10 201918
11 202416
12 202215
13 20183
14 20211
15 19891
16 20250
17 20240

About Michaël Moret

Michaël Moret is a scholar working on Molecular Biology, Computational Theory and Mathematics, Materials Chemistry, Organic Chemistry and Artificial Intelligence, having authored 17 papers that have together received 1.0k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (7 papers), Machine Learning in Materials Science (4 papers), Microbial Metabolic Engineering and Bioproduction (3 papers), Chemical Synthesis and Analysis (3 papers), AI in cancer detection (2 papers), Receptor Mechanisms and Signaling (2 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Gene Regulatory Network Analysis (2 papers). The work is most often cited by research in Health Informatics (39 citations), Computational Theory and Mathematics (418 citations), Artificial Intelligence (260 citations), Radiology, Nuclear Medicine and Imaging (170 citations) and Biophysics (40 citations). Michaël Moret has collaborated with scholars based in Switzerland, Netherlands and Germany. Frequent co-authors include Gisbert Schneider, Francesca Grisoni, Daniel Merk, Lukas Friedrich, Manfred Claassen, Jan H. Rüschoff, Norbert Wey, Peter J. Wild, Thomas Hermanns and Niels J. Rupp. Their work appears in journals such as Journal of Chemical Information and Modeling, Nature Machine Intelligence, Scientific Reports, PLoS Computational Biology and Nature Communications.

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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