Tom Sercu
Impact in
- Molecular Biology top 2%
- Machine Learning in Bioinformatics
- Protein Structure and Dynamics
- RNA and protein synthesis mechanisms
- Genomics and Phylogenetic Studies
- vaccines and immunoinformatics approaches
- Bioinformatics and Genomic Networks
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- Computational Drug Discovery Methods
Papers in
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- Speech Recognition and Synthesis 6
- Domain Adaptation and Few-Shot Learning 2
- Natural Language Processing Techniques 2
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- Speech and Audio Processing 4
- Music and Audio Processing 4
- Co-authors
- Zeming Lin (2 shared papers)Alexander W. Rives (2 shared papers)Halil Akin (1 shared paper)Roshan Rao (1 shared paper)Zhongkai Zhu (1 shared paper)Nikita Smetanin (1 shared paper)Brian Hie (1 shared paper)Robert Verkuil (1 shared paper)
- Journals
- Science (2 papers)Proceedings of the National Academy of Sciences (1 paper)Neural Information Processing Systems (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)arXiv (Cornell University) (3 papers)
- Partner nations
- United States
In The Last Decade
Tom Sercu
14 papers receiving 4.9k citations
Tom Sercu's Hit Papers
Peers
Comparison fields: 5 of 157
- Molecular Biology 3.3k
- Computational Theory and Mathematics 639
- Microbiology 146
- Signal Processing 197
- Structural Biology 21
Countries citing papers authored by Tom Sercu
This map shows the geographic impact of Tom Sercu'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 Tom Sercu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tom Sercu more than expected).
Fields of papers citing papers by Tom Sercu
This network shows the impact of papers produced by Tom Sercu. 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 Tom Sercu. The network helps show where Tom Sercu may publish in the future.
Co-authors
The 25 scholars most cited alongside Tom Sercu, 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 | Evolutionary-scale prediction of atomic-level protein structure with a language model Hit paper breakdown → | 2023 | 2669 |
| 2 | Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences Hit paper breakdown → | 2021 | 1724 |
| 3 | Simulating 500 million years of evolution with a language model Hit paper breakdown → | 2025 | 301 |
| 4 | 2016 | 157 | |
| 5 | 2016 | 78 | |
| 6 | 2017 | 39 | |
| 7 | 2017 | 29 | |
| 8 | 2017 | 16 | |
| 9 | Fisher GAN | 2017 | 14 |
| 10 | 2019 | 7 | |
| 11 | 2021 | 7 | |
| 12 | 2016 | 4 | |
| 13 | Interactive Visual Exploration of Latent Space (IVELS) for Peptide Auto-Encoder Model Selection | 2019 | 3 |
| 14 | Improved Adversarial Image Captioning | 2019 | 1 |
About Tom Sercu
Tom Sercu is a scholar working on Artificial Intelligence, Signal Processing, Computer Vision and Pattern Recognition, Cultural Studies and Molecular Biology, having authored 14 papers that have together received 5.0k indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (6 papers), Speech and Audio Processing (4 papers), Music and Audio Processing (4 papers), Machine Learning in Bioinformatics (3 papers), RNA and protein synthesis mechanisms (3 papers), Genomics and Phylogenetic Studies (2 papers), Domain Adaptation and Few-Shot Learning (2 papers) and Natural Language Processing Techniques (2 papers). The work is most often cited by research in Molecular Biology (3.3k citations), Computational Theory and Mathematics (639 citations), Microbiology (146 citations), Signal Processing (197 citations) and Structural Biology (21 citations). Tom Sercu has collaborated with scholars based in United States. Frequent co-authors include Zeming Lin, Alexander W. Rives, Halil Akin, Roshan Rao, Zhongkai Zhu, Nikita Smetanin, Brian Hie, Robert Verkuil, Ori Kabeli and Allan dos Santos Costa. Their work appears in journals such as Science, Proceedings of the National Academy of Sciences, Neural Information Processing Systems, Proceedings of the AAAI Conference on Artificial Intelligence and arXiv (Cornell University).
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.