Scientific discovery in the age of artificial intelligence
Artificial intelligence (AI) is being increasingly integrated into scientific discovery to augment
and accelerate research, helping scientists to generate hypotheses, design experiments …
and accelerate research, helping scientists to generate hypotheses, design experiments …
Machine learning-guided protein engineering
Recent progress in engineering highly promising biocatalysts has increasingly involved
machine learning methods. These methods leverage existing experimental and simulation …
machine learning methods. These methods leverage existing experimental and simulation …
Accurate proteome-wide missense variant effect prediction with AlphaMissense
The vast majority of missense variants observed in the human genome are of unknown
clinical significance. We present AlphaMissense, an adaptation of AlphaFold fine-tuned on …
clinical significance. We present AlphaMissense, an adaptation of AlphaFold fine-tuned on …
Evolutionary-scale prediction of atomic-level protein structure with a language model
Recent advances in machine learning have leveraged evolutionary information in multiple
sequence alignments to predict protein structure. We demonstrate direct inference of full …
sequence alignments to predict protein structure. We demonstrate direct inference of full …
Hyenadna: Long-range genomic sequence modeling at single nucleotide resolution
Genomic (DNA) sequences encode an enormous amount of information for gene regulation
and protein synthesis. Similar to natural language models, researchers have proposed …
and protein synthesis. Similar to natural language models, researchers have proposed …
Learning inverse folding from millions of predicted structures
We consider the problem of predicting a protein sequence from its backbone atom
coordinates. Machine learning approaches to this problem to date have been limited by the …
coordinates. Machine learning approaches to this problem to date have been limited by the …
[PDF][PDF] Language models of protein sequences at the scale of evolution enable accurate structure prediction
Large language models have recently been shown to develop emergent capabilities with
scale, going beyond simple pattern matching to perform higher level reasoning and …
scale, going beyond simple pattern matching to perform higher level reasoning and …
Genome-wide prediction of disease variant effects with a deep protein language model
Predicting the effects of coding variants is a major challenge. While recent deep-learning
models have improved variant effect prediction accuracy, they cannot analyze all coding …
models have improved variant effect prediction accuracy, they cannot analyze all coding …
Efficient evolution of human antibodies from general protein language models
Natural evolution must explore a vast landscape of possible sequences for desirable yet
rare mutations, suggesting that learning from natural evolutionary strategies could guide …
rare mutations, suggesting that learning from natural evolutionary strategies could guide …
High-resolution de novo structure prediction from primary sequence
Recent breakthroughs have used deep learning to exploit evolutionary information in
multiple sequence alignments (MSAs) to accurately predict protein structures. However …
multiple sequence alignments (MSAs) to accurately predict protein structures. However …