4 papers
Large-scale AI-Ready Data for Anti-Cancer Drug Response Modeling
Vincent Lavelle, Yitan Zhu, Kaitlyn Marlor +2
Drug response prediction (DRP) models are an active area of research in pharmacogenomics, with growing potential to accelerate the identification of effective anticancer drugs. How…
Benchmarking community drug response prediction models: datasets, models, tools, and metrics for cross-dataset generalization analysis
Alexander Partin, Priyanka Vasanthakumari, Oleksandr Narykov +17
Deep learning (DL) and machine learning (ML) models have shown promise in drug response prediction (DRP), yet their ability to generalize across datasets remains an open question,…
Assessing Reusability of Deep Learning-Based Monotherapy Drug Response Prediction Models Trained with Omics Data
Jamie C. Overbeek, Alexander Partin, Thomas S. Brettin +21
Cancer drug response prediction (DRP) models present a promising approach towards precision oncology, tailoring treatments to individual patient profiles. While deep learning (DL)…
Variational and Explanatory Neural Networks for Encoding Cancer Profiles and Predicting Drug Responses
Tianshu Feng, Rohan Gnanaolivu, Abolfazl Safikhani +7
Human cancers present a significant public health challenge and require the discovery of novel drugs through translational research. Transcriptomics profiling data that describes m…