Tom Sercu
New York Consortium in Evolutionary Primatology(US)
Publications by Year
Research Areas
Machine Learning in Bioinformatics, Genomics and Phylogenetic Studies, Speech Recognition and Synthesis, RNA and protein synthesis mechanisms, Protein Structure and Dynamics
Most-Cited Works
- → Evolutionary-scale prediction of atomic-level protein structure with a language model(2023)4,355 cited
- → Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences(2021)2,898 cited
- → Language models enable zero-shot prediction of the effects of mutations on protein function(2021)641 cited
- → Evolutionary-scale prediction of atomic level protein structure with a language model(2022)527 cited
- → Simulating 500 million years of evolution with a language model(2025)480 cited
- → Learning inverse folding from millions of predicted structures(2022)400 cited
- → Transformer protein language models are unsupervised structure learners(2020)337 cited
- → MSA Transformer(2021)336 cited
- → Very deep multilingual convolutional neural networks for LVCSR(2016)214 cited