Predicting in vitro drug sensitivity using Random Forests
نویسندگان
چکیده
منابع مشابه
Predicting in vitro drug sensitivity using Random Forests
MOTIVATION Panels of cell lines such as the NCI-60 have long been used to test drug candidates for their ability to inhibit proliferation. Predictive models of in vitro drug sensitivity have previously been constructed using gene expression signatures generated from gene expression microarrays. These statistical models allow the prediction of drug response for cell lines not in the original NCI...
متن کاملDifferentially Private Random Decision Forests using Smooth Sensitivity
We propose a new differentially-private decision forest algorithm that minimizes both the number of queries required, and the sensitivity of those queries. To do so, we build an ensemble of random decision trees that avoids querying the private data except to find the majority class label in the leaf nodes. Rather than using a count query to return the class counts like the current state-ofthe-...
متن کاملPredicting customer retention and profitability by using random forests and regression forests techniques
In an era of strong customer relationship management (CRM) emphasis, firms strive to build valuable relationships with their existing customer base. In this study we attempt to better understand three important measures of customer outcome: next buy, partial defection and customers’ profitability evolution. By means of random forests techniques we investigate a broad set of explanatory variable...
متن کاملDiversified Random Forests Using Random Subspaces
Random Forest is an ensemble learning method used for classification and regression. In such an ensemble, multiple classifiers are used where each classifier casts one vote for its predicted class label. Majority voting is then used to determine the class label for unlabelled instances. Since it has been proven empirically that ensembles tend to yield better results when there is a significant ...
متن کاملA Copula Based Approach for Design of Multivariate Random Forests for Drug Sensitivity Prediction
Modeling sensitivity to drugs based on genetic characterizations is a significant challenge in the area of systems medicine. Ensemble based approaches such as Random Forests have been shown to perform well in both individual sensitivity prediction studies and team science based prediction challenges. However, Random Forests generate a deterministic predictive model for each drug based on the ge...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Bioinformatics
سال: 2010
ISSN: 1460-2059,1367-4803
DOI: 10.1093/bioinformatics/btq628