Marwin Segler
Impact in
- Computational Theory and Mathematics top 0.1%
- Computational Drug Discovery Methods
- Materials Chemistry top 2%
- Machine Learning in Materials Science
Papers in
-
- Machine Learning in Materials Science 20
-
- Computational Drug Discovery Methods 16
- Co-authors
- Mark P. Waller (3 shared papers)Mike Preuß (1 shared paper)Christian Tyrchan (1 shared paper)Thierry Kogej (1 shared paper)Frank Glorius (1 shared paper)Frederik Sandfort (1 shared paper)Felix Strieth‐Kalthoff (1 shared paper)Mohamed A. Ahmed (2 shared papers)
- Journals
- Journal of Chemical Information and Modeling (3 papers)ACS Central Science (2 papers)Chemistry - A European Journal (2 papers)Nature Communications (1 paper)Information Sciences (1 paper)
- Partner nations
- United KingdomGermanyUnited States
In The Last Decade
Marwin Segler
22 papers receiving 3.2k citations
Marwin Segler's Hit Papers
Peers
Comparison fields: 5 of 149
- Computational Theory and Mathematics 2.0k
- Materials Chemistry 1.9k
- Health Informatics 50
- Molecular Biology 1.3k
- Biophysics 83
Countries citing papers authored by Marwin Segler
This map shows the geographic impact of Marwin Segler'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 Marwin Segler with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marwin Segler more than expected).
Fields of papers citing papers by Marwin Segler
This network shows the impact of papers produced by Marwin Segler. 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 Marwin Segler. The network helps show where Marwin Segler may publish in the future.
Co-authors
The 25 scholars most cited alongside Marwin Segler, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Planning chemical syntheses with deep neural networks and symbolic AI Hit paper breakdown → | 2018 | 1250 |
| 2 | Generating Focused Molecule Libraries for Drug Discovery with Recurrent Neural Networks Hit paper breakdown → | 2017 | 992 |
| 3 | Neural‐Symbolic Machine Learning for Retrosynthesis and Reaction Prediction Hit paper breakdown → | 2017 | 377 |
| 4 | 2020 | 216 | |
| 5 | 2022 | 98 | |
| 6 | 2018 | 86 | |
| 7 | 2022 | 49 | |
| 8 | Exploring Deep Recurrent Models with Reinforcement Learning for Molecule Design | 2018 | 35 |
| 9 | 2022 | 30 | |
| 10 | 2011 | 28 | |
| 11 | 2023 | 28 | |
| 12 | 2019 | 26 | |
| 13 | 2024 | 22 | |
| 14 | 2015 | 21 | |
| 15 | 2023 | 19 | |
| 16 | 2023 | 10 | |
| 17 | 2020 | 8 | |
| 18 | 2025 | 6 | |
| 19 | FS-Mol: A Few-Shot Learning Dataset of Molecules | 2021 | 5 |
| 20 | Generating molecules via chemical reactions | 2019 | 1 |
About Marwin Segler
Marwin Segler is a scholar working on Materials Chemistry, Computational Theory and Mathematics, Molecular Biology, Artificial Intelligence and Biomedical Engineering, having authored 22 papers that have together received 3.3k indexed citations. Recurring topics across this work include Machine Learning in Materials Science (20 papers), Computational Drug Discovery Methods (16 papers), Chemical Synthesis and Analysis (4 papers), Innovative Microfluidic and Catalytic Techniques Innovation (3 papers), Machine Learning and Data Classification (2 papers), Metabolomics and Mass Spectrometry Studies (2 papers), Catalytic C–H Functionalization Methods (2 papers) and Domain Adaptation and Few-Shot Learning (1 paper). The work is most often cited by research in Computational Theory and Mathematics (2.0k citations), Materials Chemistry (1.9k citations), Health Informatics (50 citations), Molecular Biology (1.3k citations) and Biophysics (83 citations). Marwin Segler has collaborated with scholars based in United Kingdom, Germany and United States. Frequent co-authors include Mark P. Waller, Mike Preuß, Christian Tyrchan, Thierry Kogej, Frank Glorius, Frederik Sandfort, Felix Strieth‐Kalthoff, Mohamed A. Ahmed, Nathan Brown and Nadine Schneider. Their work appears in journals such as Journal of Chemical Information and Modeling, ACS Central Science, Chemistry - A European Journal, Nature Communications and Information Sciences.
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.