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Fine-tuning Protein Language Models with Deep Mutational Scanning improves Variant Effect Prediction
Protein Language Models (PLMs) have emerged as performant and scalable tools for predicting the functional impact and clinical significance of protein-coding variants, but they still lag experimental accuracy.
Generalising sequence models for epigenome predictions with tissue and assay embeddings
Sequence modelling approaches for epigenetic profile prediction have recently expanded in terms of sequence length, model size, and profile diversity.
Epigenomic language models powered by Cerebras
Learning effective representations of DNA sequences using large genomic sequence corpuses may accelerate the development of models of gene regulation and function through transfer learning.
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