Prediction of Drug–Drug Interactions by Using Profile Fingerprint Vectors and Protein Similarities-Reference-Cited by-同舟云学术

Prediction of Drug–Drug Interactions by Using Profile Fingerprint Vectors and Protein Similarities

Published:2020 Issue:1 Volume:26 Page:42
ISSN:2093-3681
Container-title:Healthcare Informatics Research
language:en
Short-container-title:Healthc Inform Res

Author:

Dere Selma¹^ORCID,Ayvaz Serkan²^ORCID

Affiliation:

1. Department of Computer Engineering, Bahcesehir University, Besiktas, Istanbul, Turkey.

2. Department of Software Engineering, Bahcesehir University, Besiktas, Istanbul, Turkey.

Publisher

The Korean Society of Medical Informatics

Subject

Health Information Management,Health Informatics,Biomedical Engineering

Link

https://synapse.koreamed.org/pdf/10.4258/hir.2020.26.1.42

Reference24 articles.

2. US Food and Drug Administration [Internet]. White Oak (MD). Food and Drug Administration. c2019. cited at 2020 Jan 19. Available from: http://www.fda.gov/

3. Machine learning-based prediction of drug–drug interactions by integrating drug phenotypic, therapeutic, chemical, and genomic properties

4. In Vitro Evaluation of Reversible and Irreversible Cytochrome P450 Inhibition: Current Status on Methodologies and their Utility for Predicting Drug–Drug Interactions

5. Towards a mechanism-based analysis of pharmacodynamic drug?drug interactions in vivo

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