Diffusion Protein Language Models (DPLM) are introduced as a novel approach to protein language modeling, showcasing strong generative and predictive capabilities. The paper highlights the importance of understanding and designing proteins through data-driven deep learning methods, emphasizing the need for a versatile protein LM. DPLM is pre-trained on evolutionary-scale protein sequences, demonstrating its ability to generate structurally plausible and diverse protein sequences. The model can be fine-tuned for various predictive tasks, making it superior to existing models like ESM2. Additionally, DPLM offers conditional generation options, such as scaffolding for functional motifs and structure-conditioned generation.
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by Xinyou Wang,... at arxiv.org 02-29-2024
https://arxiv.org/pdf/2402.18567.pdfDeeper Inquiries