Document Type
Article
Publication Date
2017
Digital Object Identifier (DOI)
https://doi.org/10.1371/journal.pone.0173548
Abstract
Identifying drug-drug interaction (DDI) is an important topic for the development of safe pharmaceutical drugs and for the optimization of multidrug regimens for complex diseases such as cancer and HIV. There have been about 150,000 publications on DDIs in PubMed, which is a great resource for DDI studies. In this paper, we introduced an automatic computational method for the systematic analysis of the mechanism of DDIs using MeSH (Medical Subject Headings) terms from PubMed literature. MeSH term is a controlled vocabulary thesaurus developed by the National Library of Medicine for indexing and annotating articles. Our method can effectively identify DDI-relevant MeSH terms such as drugs, proteins and phenomena with high accuracy. The connections among these MeSH terms were investigated by using co-occurrence heatmaps and social network analysis. Our approach can be used to visualize relationships of DDI terms, which has the potential to help users better understand DDIs. As the volume of PubMed records increases, our method for automatic analysis of DDIs from the PubMed database will become more accurate.
Rights Information
This work is licensed under a Creative Commons Attribution 4.0 License.
Was this content written or created while at USF?
Yes
Citation / Publisher Attribution
PLoS ONE, v. 12, issue 4, art. e0173548
Scholar Commons Citation
Lu, Yin; Figler, Bryan; Huang, Hong; Tu, Yi-Cheng; Wang, Ju; and Cheng, Feng, "Characterization of the Mechanism of Drug-Drug Interactions from Pubmed Using Mesh Terms" (2017). School of Information Faculty Publications. 345.
https://digitalcommons.usf.edu/si_facpub/345
