摘要
The advent of high-throughput technologies in genomics,proteomics,transcriptomics,and imaging has led to an explosion of biomedical data,which presents both opportunities and challenges for researchers and clinicians.On one hand,the sheer volume and complexity of these data pose significant challenges for data analysis and interpretation.On the other hand,these data hold great promise for uncovering new insights into cellular functions,disease etiology,and personalized therapeutic development.In particular,the development of Large Language Models(LLM)is critical for extracting meaningful information from large-scale biomedical datasets and translating these findings into clinical applications.
