While artificial intelligence (AI) is transforming biological science, its full potential in immunology has yet to be realized due to limited data and the need for extensive experimental validation. This review provides a practical guide for experimental immunologists to actively contribute to AI development, with a focus on applications for B- and T-cell receptors. It not only gives an overview of common AI techniques in immunology but also highlights the important role of high-throughput experimental methodologies. Overall, we believe that the synergy between AI and experimental innovation will be a crucial catalyst for advancing the field of immunology.
Wang et al. (Sun,) studied this question.