Cell Type

Cell type identification is crucial for understanding biological systems and disease, focusing on accurately classifying and segmenting individual cells within complex tissues and samples. Current research employs diverse approaches, including deep learning frameworks like U-Nets and graph autoencoders, along with methods leveraging multimodal data integration and mixture modeling for instance learning to overcome challenges posed by limited labeled data and high dimensionality. These advancements are significantly impacting fields like diagnostics, drug discovery, and basic biological research by enabling more precise and efficient analysis of cellular heterogeneity and function.