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Predicting Drug-Target Interactions via Within-Score and Between-Score
Joint Authors
Shi, Jian-Yu
Liu, Zun
Yu, Hui
Li, Yong-Jun
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-10-12
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Network inference and local classification models have been shown to be useful in predicting newly potential drug-target interactions (DTIs) for assisting in drug discovery or drug repositioning.
The idea is to represent drugs, targets, and their interactions as a bipartite network or an adjacent matrix.
However, existing methods have not yet addressed appropriately several issues, such as the powerless inference in the case of isolated subnetworks, the biased classifiers derived from insufficient positive samples, the need of training a number of local classifiers, and the unavailable relationship between known DTIs and unapproved drug-target pairs (DTPs).
Designing more effective approaches to address those issues is always desirable.
In this paper, after presenting better drug similarities and target similarities, we characterize each DTP as a feature vector of within-scores and between-scores so as to hold the following superiorities: (1) a uniform vector of all types of DTPs, (2) only one global classifier with less bias benefiting from adequate positive samples, and (3) more importantly, the visualized relationship between known DTIs and unapproved DTPs.
The effectiveness of our approach is finally demonstrated via comparing with other popular methods under cross validation and predicting potential interactions for DTPs under the validation in existing databases.
American Psychological Association (APA)
Shi, Jian-Yu& Liu, Zun& Yu, Hui& Li, Yong-Jun. 2015. Predicting Drug-Target Interactions via Within-Score and Between-Score. BioMed Research International،Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1055151
Modern Language Association (MLA)
Shi, Jian-Yu…[et al.]. Predicting Drug-Target Interactions via Within-Score and Between-Score. BioMed Research International No. 2015 (2015), pp.1-9.
https://search.emarefa.net/detail/BIM-1055151
American Medical Association (AMA)
Shi, Jian-Yu& Liu, Zun& Yu, Hui& Li, Yong-Jun. Predicting Drug-Target Interactions via Within-Score and Between-Score. BioMed Research International. 2015. Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1055151
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1055151