An ensemble based top performing approach for NCI-DREAM drug sensitivity prediction challenge
We consider the problem of predicting sensitivity of cancer cell lines to new drugs based on
supervised learning on genomic profiles. The genetic and epigenetic characterization of a …
supervised learning on genomic profiles. The genetic and epigenetic characterization of a …
A new approach for prediction of tumor sensitivity to targeted drugs based on functional data
Background The success of targeted anti-cancer drugs are frequently hindered by the lack of
knowledge of the individual pathway of the patient and the extreme data requirements on …
knowledge of the individual pathway of the patient and the extreme data requirements on …
An integrated approach to anti-cancer drug sensitivity prediction
A framework for design of personalized cancer therapy requires the ability to predict the
sensitivity of a tumor to anticancer drugs. The predictive modeling of tumor sensitivity to anti …
sensitivity of a tumor to anticancer drugs. The predictive modeling of tumor sensitivity to anti …
Iterative sure independent ranking and screening for drug response prediction
B An, Q Zhang, Y Fang, M Chen, Y Qin - BMC Medical Informatics and …, 2020 - Springer
Background Prediction of drug response based on multi-omics data is a crucial task in the
research of personalized cancer therapy. Results We proposed an iterative sure …
research of personalized cancer therapy. Results We proposed an iterative sure …
Machine learning model for breast anticancer drug sensitivity prediction from gene expression
Therapeutic action of drugs and their potential mechanisms provide an important basis for
precision medicine. Cancer cell lines and drug sensitivities associated with different …
precision medicine. Cancer cell lines and drug sensitivities associated with different …
Bayesian matrix factorisation: inference, priors, and data integration
TA Brouwer - 2017 - repository.cam.ac.uk
In recent years the amount of biological data has increased exponentially. Most of these
data can be represented as matrices relating two different entity types, such as drug-target …
data can be represented as matrices relating two different entity types, such as drug-target …
Anti-cancer drug sensitivity modeling using genomic characterization and functional data
SMJ Haider - 2015 - ttu-ir.tdl.org
A framework for design of personalized cancer therapy requires the ability to predict the
sensitivity of a tumor to anti-cancer drugs. The predictive modeling of tumor sensitivity to anti …
sensitivity of a tumor to anti-cancer drugs. The predictive modeling of tumor sensitivity to anti …
Computational approaches to drug sensitivity prediction and personalized cancer therapy
NE Berlow - 2015 - ttu-ir.tdl.org
This dissertation represents the accumulated research in the field of Personalized Cancer
Therapy performed as a Graduate Student at Texas Tech University. This research has …
Therapy performed as a Graduate Student at Texas Tech University. This research has …