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Exploring the associations between drug side-effects and therapeutic indications.

Abstract：

:Drug therapeutic indications and side-effects are both measurable patient phenotype changes in response to the treatment. Inferring potential drug therapeutic indications and identifying clinically interesting drug side-effects are both important and challenging tasks. Previous studies have utilized either chemical structures or protein targets to predict indications and side-effects. In this study, we compared drug therapeutic indication prediction using various information including chemical structures, protein targets and side-effects. We also compared drug side-effect prediction with various information sources including chemical structures, protein targets and therapeutic indication. Prediction performance based on 10-fold cross-validation demonstrates that drug side-effects and therapeutic indications are the most predictive information source for each other. In addition, we extracted 6706 statistically significant indication-side-effect associations from all known drug-disease and drug-side-effect relationships. We further developed a novel user interface that allows the user to interactively explore these associations in the form of a dynamic bipartitie graph. Many relationship pairs provide explicit repositioning hypotheses (e.g., drugs causing postural hypotension are potential candidates for hypertension) and clear adverse-reaction watch lists (e.g., drugs for heart failure possibly cause impotence). All data sets and highly correlated disease-side-effect relationships are available at http://astro.temple.edu/∼tua87106/druganalysis.html.

journal_name

J Biomed Inform

journal_title

Journal of biomedical informatics

authors

Wang F,Zhang P,Cao N,Hu J,Sorrentino R

doi

10.1016/j.jbi.2014.03.014

subject

Has Abstract

pub_date

2014-10-01 00:00:00

pages

15-23

eissn

1532-0464

issn

1532-0480

pii

S1532-0464(14)00081-1

journal_volume

51

pub_type

杂志文章

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