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Learn about Protein Language Models (PLMs) and their applications in synthetic biology through this 48-minute workshop that explores how these Transformer-like models are trained on protein sequences to understand biological 'grammar'. Discover the key differences between PLMs and traditional NLP models while exploring various open-source models and datasets. Through hands-on exercises in Google Colab, develop a protein function multi-label classifier using pre-trained models, implement retrieval-augmented classification techniques, and create a Streamlit application for real-time protein function prediction. Master practical skills in working with popular PLMs like ProBERT, ProtTrans, and Ankh, while learning to set up environments, manipulate protein datasets, and perform model fine-tuning for improved classification performance.
