Publications

Publications from the IMPROVE project:

Zhang et al., Topological regression as an interpretable and efficient tool for quantitative structure-activity relationship modeling. Nature Communications, 2024.

Vasanthakumari et al., Comprehensive investigation of active learning strategies for predicting drug response. Cancers (Basel), 2024.

Partin et al., Deep learning methods for drug response prediction in cancer: predominant and emerging trends. Front. Med., Sec. Precision Medicine, 2023.

Partin et al., Data augmentation and multimodal learning for predicting drug response in patient-derived xenografts from gene expressions and histology images. Front. Med., Sec. Precision Medicine, 2023.

Partin et al., Drug response prediction in patient-derived xenografts with data augmentation and multimodal deep learning. Journal of Clinical Oncology, 2022.

Zhu et al., Multifactorial drug response modeling based on cancer organoid data. Journal of Clinical Oncology, 2022.

Partin et al., Learning curves for drug response prediction in cancer cell lines. BMC Bioinformatics, 2021.