Shumin Li

xDecoder unlocks the potential of genomic foundation models for few-shot personal gene expression prediction.

Large-scale genomic language models (gLMs) hold promise for modeling gene regulation, yet their ability to capture personal gene expression variations remains unresolved. We developed xDecoder, a unified decoding framework that utilizes gLMs and sequence-to-function (S2F) embeddings to learn how personal genetic variat...