Proceedings of the 2016 International Forum on Mechanical, Control and Automation (IFMCA 2016)

Drug Side-effect Prediction based on Comprehensive Drug Similarity

Authors
Chengcheng Sun, Yi Zheng, Yan Jia, Liang Gan
Corresponding Author
Chengcheng Sun
Available Online March 2017.
DOI
https://doi.org/10.2991/ifmca-16.2017.28How to use a DOI?
Keywords
drug side-effect prediction; comprehensive drug similarity; drug chemical structure; drug target protein.
Abstract
Drug side-effects have gained attention from the whole society because of significant morbidities and mortalities they caused. Therefore, the early detection of side-effects, before reaching the clinical stages, is important yet challenging. In this paper, we proposed a comprehensive similarity framework to measure the similarity between drugs and developed a side-effect prediction approach based on it. The new comprehensive similarity integrates drug formula similarity, drug chemical structure similarity, drug substituent similarity, drug target similarity and drug side-effect similarity in a unified framework to capture drug features from different perspectives. Extensive comparison experiments on real drug side-effect prediction demonstrate that our proposed approach is competent to drug side-effect prediction and outperforms other state-of-the-art approaches.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Volume Title
Proceedings of the 2016 International Forum on Mechanical, Control and Automation (IFMCA 2016)
Series
Advances in Engineering Research
Publication Date
March 2017
ISBN
978-94-6252-307-4
ISSN
2352-5401
DOI
https://doi.org/10.2991/ifmca-16.2017.28How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Chengcheng Sun
AU  - Yi Zheng
AU  - Yan Jia
AU  - Liang Gan
PY  - 2017/03
DA  - 2017/03
TI  - Drug Side-effect Prediction based on Comprehensive Drug Similarity
BT  - Proceedings of the 2016 International Forum on Mechanical, Control and Automation (IFMCA 2016)
PB  - Atlantis Press
SP  - 171
EP  - 178
SN  - 2352-5401
UR  - https://doi.org/10.2991/ifmca-16.2017.28
DO  - https://doi.org/10.2991/ifmca-16.2017.28
ID  - Sun2017/03
ER  -