DocumentCode :
3195785
Title :
An ensemble approach for drug side effect prediction
Author :
Jahid, Md Jamiul ; Ruan, Jiayang
Author_Institution :
Dept. of Comput. Sci., Univ. of Texas at San Antonio, San Antonio, TX, USA
fYear :
2013
fDate :
18-21 Dec. 2013
Firstpage :
440
Lastpage :
445
Abstract :
In silico prediction of drug side-effects in early stage of drug development is becoming more popular now days, which not only reduces the time for drug design but also reduces the drug development costs. In this article we propose an ensemble approach to predict drug side-effects of drug molecules based on their chemical structure. Our idea originates from the observation that similar drugs have similar side-effects. Based on this observation we design an ensemble approach that combine the results from different classification models where each model is generated by a different set of similar drugs. We applied our approach to 1385 side-effects in the SIDER database for 888 drugs. Results show that our approach outperformed previously published approaches and standard classifiers. Furthermore, we applied our method to a number of uncharacterized drug molecules in DrugBank database and predict their side-effect profiles for future usage. Results from various sources confirm that our method is able to predict the side-effects for uncharacterized drugs and more importantly able to predict rare side-effects which are often ignored by other approaches. The method described in this article can be useful to predict side-effects in drug design in an early stage to reduce experimental cost and time.
Keywords :
drugs; medical computing; pattern classification; DrugBank database; SIDER database; classification models; drug design; drug side effect prediction; ensemble approach; side-effect profiles; Chemicals; Databases; Drugs; Predictive models; Probability; Proteins; Support vector machines; adverse side-effect; chemical substructure; drug development; uncharacterized drug;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Bioinformatics and Biomedicine (BIBM), 2013 IEEE International Conference on
Conference_Location :
Shanghai
Type :
conf
DOI :
10.1109/BIBM.2013.6732532
Filename :
6732532
Link To Document :
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