Pascal Notin

2.0k citations
7 papers · 677 · 3 hit papers · h-index 5

Impact in

Papers in

    • Protein Structure and Dynamics 2
    • Genomics and Phylogenetic Studies 2
    • RNA and protein synthesis mechanisms 2
    • Machine Learning in Bioinformatics 1
    • Genomics and Rare Diseases 1
    • Evolution and Genetic Dynamics 1

Pascal Notin

7 papers receiving 665 citations

Pascal Notin's Hit Papers

Machine learning for functional protein design 2024 · 145 citations
1450+1+3Years since publication100200300

Peers

Pascal Notin
Comparison fields: 5 of 85
  • Health Informatics 11
  • Genetics 176
  • Molecular Biology 380
  • Infectious Diseases 58
  • Cancer Research 45
Replace Noam Auslander with:
Noam Auslander United States
Joseph Min United States
James Diggans United States
Muxue Tang China
Chenyu Zhu China
Ahmad Rusdan Handoyo Utomo Indonesia
Juexiao Zhou Saudi Arabia
Karin Schwarzbauer Austria
Giovanni Birolo Italy
Andrew Yongky United States
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Citations per field
00.5×6.1×
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Citations per year

Countries citing papers authored by Pascal Notin

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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 19 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.

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

All Works

7 of 7 papers shown
#Work
1
Disease variant prediction with deep generative models of evolutionary data
Hit paper breakdown →
2021398
2
Machine learning for functional protein design
Hit paper breakdown →
2024145
3
Learning from prepandemic data to forecast viral escape
Hit paper breakdown →
202398
4 202222
5 202510
6 20232
7 20252

About Pascal Notin

Pascal Notin is a scholar working on Molecular Biology, Genetics, Infectious Diseases, Cognitive Neuroscience and Business and International Management, having authored 7 papers that have together received 677 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (2 papers), Genomics and Phylogenetic Studies (2 papers), RNA and protein synthesis mechanisms (2 papers), Genomics and Rare Diseases (1 paper), Neural dynamics and brain function (1 paper), Genetics, Aging, and Longevity in Model Organisms (1 paper), Machine Learning in Bioinformatics (1 paper) and Evolution and Genetic Dynamics (1 paper). The work is most often cited by research in Health Informatics (11 citations), Genetics (176 citations), Molecular Biology (380 citations), Infectious Diseases (58 citations) and Cancer Research (45 citations). Pascal Notin has collaborated with scholars based in United States, United Kingdom and Switzerland. Frequent co-authors include Yarin Gal, Debora S. Marks, Kelly P. Brock, Jonathan Frazer, Aidan N. Gomez, Mafalda Dias, Joseph Min, Chris Sander, Nathan Rollins and Daniel P. Ritter. Their work appears in journals such as Nature, Nature Biotechnology, Science and NeuroImage.

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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