Amanda Gonçalves

The paper constructs a pan-cancer single-cell atlas to improve tumor identity inference and identify genetic vulnerabilities by integrating high-quality malignant cells across multiple cancers.

This paper uses single-cell Raman spectroscopy and machine learning to predict therapeutic response in melanoma, achieving >96% accuracy in cell line classification and 91% accuracy in patient drug resistance inference.