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Positive-Unlabeled Learning for inferring drug interactions based on heterogeneous attributes

Hameed, Pathima Nusrath; Verspoor, Karin; Kusljic, Snezana; Halgamuge, Saman

Description

Background Investigating and understanding drug-drug interactions (DDIs) is important in improving the effectiveness of clinical care. DDIs can occur when two or more drugs are administered together. Experimentally based DDI detection methods require a large cost and time. Hence, there is a great interest in developing efficient and useful computational methods for inferring potential DDIs. Standard binary classifiers require both positives and negatives for training. In a DDI context, drug...[Show more]

CollectionsANU Research Publications
Date published: 2017-03-01
Type: Journal article
URI: http://hdl.handle.net/1885/235235
Source: BMC Bioinformatics
DOI: 10.1186/s12859-017-1546-7
Access Rights: Open Access

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