2018/07/06 · In this paper, we proposed DeepPredictor, a deep learning model, to predict drug sensitivity of cancer cell lines. The model was trained on CCLE ...

In this study, we have developed a deep learning architecture to improve the performance of drug sensitivity prediction based on these data.

2023/02/15 · A wave of recent papers demonstrates promising results in predicting cancer response to drug treatments while utilizing deep learning methods.

2024/04/27 · This section develops the architecture of CANDELA, a cancer drug sensitivity estimation modular graph neural network, visualized in Figure 1.

2021/03/19 · The results revealed the landscape of molecular features in association with drug response in 33 cancer types that were beyond the information ...

2024/05/09 · This study proposes a new and interpretable deep learning model, DrugGene, which integrates gene expression, gene mutation, gene copy number ...

2020/10/22 · We address these challenges by developing DrugCell, an interpretable deep learning model of human cancer cells trained on the responses of 1,235 ...

2020/11/09 · We address these challenges by developing DrugCell, an interpretable deep learning model of human cancer cells trained on the responses of 1,235 ...

2023/06/13 · To predict the drug sensitivity on unseen cancer cell lines, a deep learning neural network named NeuPD is proposed. As an input, gene ...

2021/04/01 · Abstract—High-throughput screening technologies have provided a large amount of drug sensitivity data for a panel of cancer cell lines and ...