Pascal Notin
Impact in
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
- Genetics top 10%
- Genomics and Rare Diseases
- Evolution and Genetic Dynamics
Papers in
-
- Protein Structure and Dynamics 6
- Machine Learning in Bioinformatics 2
- Enzyme Catalysis and Immobilization 1
- CRISPR and Genetic Engineering 1
-
- SARS-CoV-2 and COVID-19 Research 2
- Co-authors
- Debora S. Marks (6 shared papers)Yarin Gal (7 shared papers)Jonathan Frazer (2 shared papers)Mafalda Dias (2 shared papers)Joseph Min (1 shared paper)Aidan N. Gomez (1 shared paper)Kelly P. Brock (1 shared paper)Chris Sander (2 shared papers)
- Journals
- Nature (4 papers)Nature Biotechnology (2 papers)NeuroImage (1 paper)Science (1 paper)Immunity (1 paper)
- Partner nations
- United StatesUnited KingdomJapan
In The Last Decade
Pascal Notin
11 papers receiving 856 citations
Pascal Notin's Hit Papers
Peers
Comparison fields: 5 of 78
- Health Informatics 36
- Genetics 267
- Molecular Biology 399
- Infectious Diseases 77
- Computational Theory and Mathematics 28
Countries citing papers authored by Pascal Notin
This map shows the geographic impact of Pascal Notin'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 Pascal Notin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pascal Notin more than expected).
Fields of papers citing papers by Pascal Notin
This network shows the impact of papers produced by Pascal Notin. 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 Pascal Notin. The network helps show where Pascal Notin may publish in the future.
Co-authors
The 25 scholars most cited alongside Pascal Notin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Disease variant prediction with deep generative models of evolutionary data Hit paper breakdown → | 2021 | 480 |
| 2 | Machine learning for functional protein design Hit paper breakdown → | 2024 | 171 |
| 3 | Learning from prepandemic data to forecast viral escape Hit paper breakdown → | 2023 | 133 |
| 4 | 2022 | 25 | |
| 5 | 2025 | 16 | |
| 6 | 2025 | 13 | |
| 7 | 2023 | 12 | |
| 8 | 2025 | 11 | |
| 9 | 2023 | 6 | |
| 10 | 2026 | 5 | |
| 11 | 2025 | 1 | |
| 12 | 2026 | 0 |
About Pascal Notin
Pascal Notin is a scholar working on Molecular Biology, Infectious Diseases, Cognitive Neuroscience, Genetics and Materials Chemistry, having authored 12 papers that have together received 873 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (6 papers), Machine Learning in Bioinformatics (2 papers), SARS-CoV-2 and COVID-19 Research (2 papers), Functional Brain Connectivity Studies (1 paper), Enzyme Catalysis and Immobilization (1 paper), Enzyme Structure and Function (1 paper), CRISPR and Genetic Engineering (1 paper) and Genomics and Rare Diseases (1 paper). The work is most often cited by research in Health Informatics (36 citations), Genetics (267 citations), Molecular Biology (399 citations), Infectious Diseases (77 citations) and Computational Theory and Mathematics (28 citations). Pascal Notin has collaborated with scholars based in United States, United Kingdom and Japan. Frequent co-authors include Debora S. Marks, Yarin Gal, Jonathan Frazer, Mafalda Dias, Joseph Min, Aidan N. Gomez, Kelly P. Brock, Chris Sander, Nathan J. Rollins and Nicole N. Thadani. Their work appears in journals such as Nature, Nature Biotechnology, NeuroImage, Science and Immunity.
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.