Drug repurposing through joint learning on knowledge graphs and literature
Type
PreprintAuthors
AlShahrani, Mona
Hoehndorf, Robert

KAUST Department
Bio-Ontology Research Group (BORG)Computational Bioscience Research Center (CBRC)
Computer Science Program
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
KAUST Grant Number
URF/1/3454-01-01FCC/1/1976-08-01
FCS/1/3657-02-01
Date
2018-08-06Permanent link to this record
http://hdl.handle.net/10754/628436
Metadata
Show full item recordAbstract
Drug repurposing is the problem of finding new uses for known drugs, and may either involve finding a new protein target or a new indication for a known mechanism. Several computational methods for drug repurposing exist, and many of these methods rely on combinations of different sources of information, extract hand-crafted features and use a computational model to predict targets or indications for a drug. One of the distinguishing features between different drug repurposing systems is the selection of features. Recently, a set of novel machine learning methods have become available that can efficiently learn features from datasets, and these methods can be applied, among others, to text and structured data in knowledge graphs. We developed a novel method that combines information in literature and structured databases, and applies feature learning to generate vector space embeddings. We apply our method to the identification of drug targets and indications for known drugs based on heterogeneous information about drugs, target proteins, and diseases. We demonstrate that our method is able to combine complementary information from both structured databases and from literature, and we show that our method can compete with well-established methods for drug repurposing. Our approach is generic and can be applied to other areas in which multi-modal information is used to build predictive models.Citation
Alshahrani M, Hoehndorf R (2018) Drug repurposing through joint learning on knowledge graphs and literature. Available: http://dx.doi.org/10.1101/385617.Sponsors
This work was supported by funding from King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award No. URF/1/3454-01-01, FCC/1/1976-08-01, and FCS/1/3657-02-01.Publisher
Cold Spring Harbor LaboratoryDOI
10.1101/385617Additional Links
https://www.biorxiv.org/content/early/2018/08/06/385617Relations
Is Supplemented By:- [Software]
Title: bio-ontology-research-group/multi-drug-embedding: Method for drug repurposing from knowledge graphs and literature. Publication Date: 2018-05-01. github: bio-ontology-research-group/multi-drug-embedding Handle: 10754/668244
ae974a485f413a2113503eed53cd6c53
10.1101/385617
Scopus Count
Except where otherwise noted, this item's license is described as The copyright holder for this preprint is the author/funder. It is made available under a CC-BY-NC-ND 4.0 International license.