Protein Sequence

Protein sequence analysis focuses on understanding the linear order of amino acids in proteins and its relationship to protein structure, function, and evolution. Current research heavily utilizes deep learning models, including transformer-based architectures like BERT and GPT variants, and diffusion models, to analyze protein sequences, predict properties (e.g., binding sites, post-translational modifications), and even design novel proteins. These advancements are significantly impacting various fields, including drug discovery, disease diagnosis, and biotechnology, by enabling faster and more accurate prediction and design of proteins with desired characteristics. Furthermore, research is actively addressing challenges like data leakage in benchmarks and developing more efficient methods for handling large datasets.