A cross-study analysis of drug response prediction in cancer cell lines
To enable personalized cancer treatment, machine learning models have been developed
to predict drug response as a function of tumor and drug features. However, most algorithm …
to predict drug response as a function of tumor and drug features. However, most algorithm …
[HTML][HTML] Multitask learning improves prediction of cancer drug sensitivity
Precision oncology seeks to predict the best therapeutic option for individual patients based
on the molecular characteristics of their tumors. To assess the preclinical feasibility of drug …
on the molecular characteristics of their tumors. To assess the preclinical feasibility of drug …
[HTML][HTML] A deep learning framework for predicting response to therapy in cancer
A major challenge in cancer treatment is predicting clinical response to anti-cancer drugs on
a personalized basis. Using a pharmacogenomics database of 1,001 cancer cell lines, we …
a personalized basis. Using a pharmacogenomics database of 1,001 cancer cell lines, we …
Deep learning for drug response prediction in cancer
Predicting the sensitivity of tumors to specific anti-cancer treatments is a challenge of
paramount importance for precision medicine. Machine learning (ML) algorithms can be …
paramount importance for precision medicine. Machine learning (ML) algorithms can be …
A survey and systematic assessment of computational methods for drug response prediction
J Chen, L Zhang - Briefings in bioinformatics, 2021 - academic.oup.com
Drug response prediction arises from both basic and clinical research of personalized
therapy, as well as drug discovery for cancers. With gene expression profiles and other …
therapy, as well as drug discovery for cancers. With gene expression profiles and other …
A systematic assessment of deep learning methods for drug response prediction: from in vitro to clinical applications
B Shen, F Feng, K Li, P Lin, L Ma… - Briefings in …, 2023 - academic.oup.com
Drug response prediction is an important problem in personalized cancer therapy. Among
various newly developed models, significant improvement in prediction performance has …
various newly developed models, significant improvement in prediction performance has …
[HTML][HTML] Machine learning approaches to drug response prediction: challenges and recent progress
Cancer is a leading cause of death worldwide. Identifying the best treatment using
computational models to personalize drug response prediction holds great promise to …
computational models to personalize drug response prediction holds great promise to …
[HTML][HTML] Assessment of modelling strategies for drug response prediction in cell lines and xenografts
Data from several large high-throughput drug response screens have become available to
the scientific community recently. Although many efforts have been made to use this …
the scientific community recently. Although many efforts have been made to use this …
How much can deep learning improve prediction of the responses to drugs in cancer cell lines?
The drug response prediction problem arises from personalized medicine and drug
discovery. Deep neural networks have been applied to the multi-omics data being available …
discovery. Deep neural networks have been applied to the multi-omics data being available …
[HTML][HTML] Anticancer drug sensitivity prediction in cell lines from baseline gene expression through recursive feature selection
Z Dong, N Zhang, C Li, H Wang, Y Fang, J Wang… - BMC cancer, 2015 - Springer
Background An enduring challenge in personalized medicine is to select right drug for
individual patients. Testing drugs on patients in large clinical trials is one way to assess their …
individual patients. Testing drugs on patients in large clinical trials is one way to assess their …