Tom Sercu

Biochemistry, Genetics and Molecular Biology · Life Sciences

22h-index11.3kcitations53works312.02yr avg
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Research Topics

Machine Learning in Bioinformatics(16), Genomics and Phylogenetic Studies(12), Speech Recognition and Synthesis(11), RNA and protein synthesis mechanisms(10), Speech and Audio Processing(10)

Publications53 total

Simulating 500 million years of evolution with a language model
Science·2025· 439 cited
Simulating 500 million years of evolution with a language model
2024· 185 citedOpen Access
Evolutionary-scale prediction of atomic-level protein structure with a language model
Science·2023· 4.2k citedOpen Access
Language models generalize beyond natural proteins
2022· 188 citedOpen Access
A high-level programming language for generative protein design
2022· 59 citedOpen Access
ESM Atlas v0 random sample of high confidence predicted protein structures
Zenodo (CERN European Organization for Nuclear Research)·2022Open Access
ESM Atlas v0 representative random sample of predicted protein structures
Zenodo (CERN European Organization for Nuclear Research)·2022Open Access
ESM Atlas v0 representative random sample of predicted protein structures
Zenodo (CERN European Organization for Nuclear Research)·2022Open Access
ESM Atlas v0 random sample of high confidence predicted protein structures
2022Open Access
Evolutionary-scale prediction of atomic level protein structure with a language model
2022· 522 citedOpen Access
Learning inverse folding from millions of predicted structures
2022· 393 citedOpen Access
MSA Transformer
2021· 9 cited
Language models enable zero-shot prediction of the effects of mutations on protein function
2021· 636 citedOpen Access
Author Correction: Accelerated antimicrobial discovery via deep generative models and molecular dynamics simulations
Nature Biomedical Engineering·2021· 9 citedOpen Access
Improved Mutual Information Estimation
Proceedings of the AAAI Conference on Artificial Intelligence·2021· 9 citedOpen Access
Transformer protein language models are unsupervised structure learners
2021· 10 cited
Neural Potts Model
2021· 8 citedOpen Access
Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences
Proceedings of the National Academy of Sciences·2021· 2.8k citedOpen Access
MSA Transformer
2021· 329 citedOpen Access
Transformer protein language models are unsupervised structure learners
2020· 335 citedOpen Access
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Frequent Co-authors

Alexander Rives(18), Youssef Mroueh(16), Roshan Rao(13), Robert Verkuil(13), Zeming Lin(12), Salvatore Candido(8), Joshua Meier(8), Halil Akin(7), Brian Hie(7), Ori Kabeli(7), Jason Liu(7), Nikita Smetanin(6), Zhongkai Zhu(5), Wenting Lu(5), Yaniv Shmueli(5), Allan dos Santos Costa(5), Maryam Fazel-Zarandi(5), George Saon(5), Anant Raj(5), Pierre Dognin(5)