Instruct: Given a scientific paper title, retrieve paper titles that are cited by the given paper.
Query: A multivariate random forest based framework for drug sensitivity prediction
Predicting in vitro drug sensitivity using Random Forests
Multivariate random forests
Predicting disease risks from highly imbalanced data using random forest
PaccMann: Prediction of anticancer compound sensitivity with multi-modal attention-based neural networks
Gene selection and classification of microarray data using random forest
DeepARG: A deep learning approach for predicting antibiotic resistance genes from metagenomic data
Netpredictor: R and Shiny package to perform drug-target network analysis and prediction of missing links
Overview of random forest methodology and practical guidance with emphasis on computational biology and bioinformatics
DrugE-Rank: improving drug–target interaction prediction of new candidate drugs or targets by ensemble learning to rank
application of breiman ' s random forest to modeling structure - activity relationships of pharmaceutical molecules .
deep - learning - based drug - target interaction prediction .
A framework for sensitivity analysis of decision trees
Random Survival Forests for High-Dimensional Data
An Efficient Algorithm for Disease Prediction with Multi Dimensional Data
Data-Driven Prediction of Drug Effects and Interactions
A comprehensive comparison of random forests and support vector machines for microarray-based cancer classification
PADME: A Deep Learning-based Framework for Drug-Target Interaction Prediction
ggRandomForests: Exploring Random Forest Survival
the cancer cell line encyclopedia enables predictive modeling of anticancer drug sensitivity .
Collaborative matrix factorization with multiple similarities for predicting drug-target interactions
chapter 5 cognitive analytics : going beyond big data analytics and machine learning .
MemexQA: Visual Memex Question Answering
Classification and Regression by randomForest
MAFIA: a maximal frequent itemset algorithm for transactional databases
The Science Behind Biosimilars Entering a New Era of Biologic Therapy