We proposed an ensemble learning method simultaneously integrating a low-rank matrix completion (MC) model and a ridge regression model (RR) to predict anticancer drug response on cancer cell lines. Our combination model achieves both high prediction accuracy and good biological interpretability
open access journalThe development of reliable predictive models for individual cancer cell lines to...
Machine learning methods trained on cancer cell line panels are intensively studied for the predicti...
Current breast cancer predictive signatures are not unique. Can we use this fact to our advantage to...
<p>We proposed an ensemble learning method simultaneously integrating a low-rank matrix completion (...
8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Manag...
Motivation: Chemotherapy or targeted therapy are two of the main treatment options for many types of...
Drug sensitivity prediction to a panel of cancer cell lines using computational approaches has been ...
In order to improve anti-cancer treatment, we need to better understand why some patients respond to...
Motivation: A key goal of computational personalized medicine is to systematically utilize genomic a...
Publisher Copyright: © 2021 The Author(s). Published by Oxford University Press.Motivation: Combinat...
Motivation: A prime challenge in precision cancer medicine is to identify genomic and molecular feat...
Abstract One of the prominent challenges in precision medicine is to select the most appropriate tre...
Predicting the response of cancer cell lines to specific drugs is one of the central problems in per...
Abstract Background The National Cancer Institute drug pair screening effort against 60 well-charact...
Personalizing medicine, by choosing therapies that maximize effectiveness and minimize side effects ...
open access journalThe development of reliable predictive models for individual cancer cell lines to...
Machine learning methods trained on cancer cell line panels are intensively studied for the predicti...
Current breast cancer predictive signatures are not unique. Can we use this fact to our advantage to...
<p>We proposed an ensemble learning method simultaneously integrating a low-rank matrix completion (...
8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Manag...
Motivation: Chemotherapy or targeted therapy are two of the main treatment options for many types of...
Drug sensitivity prediction to a panel of cancer cell lines using computational approaches has been ...
In order to improve anti-cancer treatment, we need to better understand why some patients respond to...
Motivation: A key goal of computational personalized medicine is to systematically utilize genomic a...
Publisher Copyright: © 2021 The Author(s). Published by Oxford University Press.Motivation: Combinat...
Motivation: A prime challenge in precision cancer medicine is to identify genomic and molecular feat...
Abstract One of the prominent challenges in precision medicine is to select the most appropriate tre...
Predicting the response of cancer cell lines to specific drugs is one of the central problems in per...
Abstract Background The National Cancer Institute drug pair screening effort against 60 well-charact...
Personalizing medicine, by choosing therapies that maximize effectiveness and minimize side effects ...
open access journalThe development of reliable predictive models for individual cancer cell lines to...
Machine learning methods trained on cancer cell line panels are intensively studied for the predicti...
Current breast cancer predictive signatures are not unique. Can we use this fact to our advantage to...
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