Deep learning methods for drug response prediction in cancer: predominant and emerging trends
Cancer claims millions of lives yearly worldwide. While many therapies have been made
available in recent years, by in large cancer remains unsolved. Exploiting computational …
available in recent years, by in large cancer remains unsolved. Exploiting computational …
Trends and potential of machine learning and deep learning in drug study at single-cell level
Cancer treatments always face challenging problems, particularly drug resistance due to
tumor cell heterogeneity. The existing datasets include the relationship between gene …
tumor cell heterogeneity. The existing datasets include the relationship between gene …
GraphCDR: a graph neural network method with contrastive learning for cancer drug response prediction
Auto-HMM-LMF: feature selection based method for prediction of drug response via autoencoder and hidden Markov model
Background Predicting the response of cancer cell lines to specific drugs is an essential
problem in personalized medicine. Since drug response is closely associated with genomic …
problem in personalized medicine. Since drug response is closely associated with genomic …