Predicting Metabolite-Disease Associations Based on Linear Neighborhood Similarity with Improved Bipartite Network Projection Algorithm
Joint Authors
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-05-23
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
A large number of clinical observations have showed that metabolites are involved in a variety of important human diseases in the recent years.
Nonetheless, the inherent noise and incompleteness in the existing biological datasets are tough factors which limit the prediction accuracy of current computational methods.
To solve this problem, in this paper, a prediction method, IBNPLNSMDA, is proposed which uses the improved bipartite network projection method to predict latent metabolite-disease associations based on linear neighborhood similarity.
Specifically, liner neighborhood similarity matrix about metabolites (diseases) is reconstructed according to the new feature which is gained by the known metabolite-disease associations and relevant integrated similarities.
The improved bipartite network projection method is adopted to infer the potential associations between metabolites and diseases.
At last, IBNPLNSMDA achieves a reliable performance in LOOCV (AUC of 0.9634) outperforming the compared methods.
In addition, in case studies of four common human diseases, simulation results confirm the utility of our method in discovering latent metabolite-disease pairs.
Thus, we believe that IBNPLNSMDA could serve as a reliable computational tool for metabolite-disease associations prediction.
American Psychological Association (APA)
Lei, Xiujuan& Zhang, Cheng. 2020. Predicting Metabolite-Disease Associations Based on Linear Neighborhood Similarity with Improved Bipartite Network Projection Algorithm. Complexity،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1145536
Modern Language Association (MLA)
Lei, Xiujuan& Zhang, Cheng. Predicting Metabolite-Disease Associations Based on Linear Neighborhood Similarity with Improved Bipartite Network Projection Algorithm. Complexity No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1145536
American Medical Association (AMA)
Lei, Xiujuan& Zhang, Cheng. Predicting Metabolite-Disease Associations Based on Linear Neighborhood Similarity with Improved Bipartite Network Projection Algorithm. Complexity. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1145536
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1145536