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q-bio.GN2025
scSiameseClu: A Siamese Clustering Framework for Interpreting single-cell RNA Sequencing Data
Ping Xu, Zhiyuan Ning, Pengjiang Li +5
Single-cell RNA sequencing (scRNA-seq) reveals cell heterogeneity, with cell clustering playing a key role in identifying cell types and marker genes. Recent advances, especially g…
q-bio.GN2024
scInterpreter: Training Large Language Models to Interpret scRNA-seq Data for Cell Type Annotation
Cong Li, Meng Xiao, Pengfei Wang +3
Despite the inherent limitations of existing Large Language Models in directly reading and interpreting single-cell omics data, they demonstrate significant potential and flexibili…