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RecRWR: A Recursive Random Walk Method for Improved Identification of Diseases
Joint Authors
Arrais, Joel P.
Oliveira, José Luís
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-03-22
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
High-throughput methods such as next-generation sequencing or DNA microarrays lack precision, as they return hundreds of genes for a single disease profile.
Several computational methods applied to physical interaction of protein networks have been successfully used in identification of the best disease candidates for each expression profile.
An open problem for these methods is the ability to combine and take advantage of the wealth of biomedical data publicly available.
We propose an enhanced method to improve selection of the best disease targets for a multilayer biomedical network that integrates PPI data annotated with stable knowledge from OMIM diseases and GO biological processes.
We present a comprehensive validation that demonstrates the advantage of the proposed approach, Recursive Random Walk with Restarts (RecRWR).
The obtained results outline the superiority of the proposed approach, RecRWR, in identifying disease candidates, especially with high levels of biological noise and benefiting from all data available.
American Psychological Association (APA)
Arrais, Joel P.& Oliveira, José Luís. 2015. RecRWR: A Recursive Random Walk Method for Improved Identification of Diseases. BioMed Research International،Vol. 2015, no. 2015, pp.1-7.
https://search.emarefa.net/detail/BIM-1056604
Modern Language Association (MLA)
Arrais, Joel P.& Oliveira, José Luís. RecRWR: A Recursive Random Walk Method for Improved Identification of Diseases. BioMed Research International No. 2015 (2015), pp.1-7.
https://search.emarefa.net/detail/BIM-1056604
American Medical Association (AMA)
Arrais, Joel P.& Oliveira, José Luís. RecRWR: A Recursive Random Walk Method for Improved Identification of Diseases. BioMed Research International. 2015. Vol. 2015, no. 2015, pp.1-7.
https://search.emarefa.net/detail/BIM-1056604
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1056604