Large Language Models in Bioinformatics: A Survey
It provides a comprehensive overview for researchers in bioinformatics and AI, but is incremental as a survey paper.
This survey reviews how Large Language Models (LLMs) are applied in bioinformatics to analyze DNA, RNA, proteins, and single-cell data, highlighting their potential to drive innovations in precision medicine.
Large Language Models (LLMs) are revolutionizing bioinformatics, enabling advanced analysis of DNA, RNA, proteins, and single-cell data. This survey provides a systematic review of recent advancements, focusing on genomic sequence modeling, RNA structure prediction, protein function inference, and single-cell transcriptomics. Meanwhile, we also discuss several key challenges, including data scarcity, computational complexity, and cross-omics integration, and explore future directions such as multimodal learning, hybrid AI models, and clinical applications. By offering a comprehensive perspective, this paper underscores the transformative potential of LLMs in driving innovations in bioinformatics and precision medicine.