@inbook{bc83bc80cb874f29b6e54f3d9651fd0d,
title = "DrugE-rank: Predicting drug-target interactions by learning to rank",
abstract = "Identifying drug-target interactions is crucial for the success of drug discovery. Approaches based on machine learning for this problem can be divided into two types: feature-based and similarity-based methods. By utilizing the “Learning to rank” framework, we propose a new method, DrugE-Rank, to combine these two different types of methods for improving the prediction performance of new candidate drugs and targets. DrugE-Rank is available at http://datamining-iip.fudan.edu.cn/service/DrugE-Rank/.",
keywords = "Drug discovery, DrugE-rank, Learning to rank",
author = "Jieyao Deng and Qingjun Yuan and Hiroshi Mamitsuka and Shanfeng Zhu",
year = "2018",
month = jan,
day = "1",
doi = "10.1007/978-1-4939-8561-6_14",
language = "English",
isbn = "978-1-4939-8560-9",
series = "Methods in Molecular Biology",
publisher = "Springer",
pages = "195--202",
booktitle = "Methods in Molecular Biology",
address = "Germany",
}