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Reverse Nearest Neighbor Search on a Protein-Protein Interaction Network to Infer Protein-Disease Associations
The associations between proteins and diseases are crucial information for investigating pathological mechanisms. However, the number of known and reliable protein-disease associations is quite small. In this study, an analysis framework to infer associations between proteins and diseases was develo...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5513527/ https://www.ncbi.nlm.nih.gov/pubmed/28757797 http://dx.doi.org/10.1177/1177932217720405 |
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author | Suratanee, Apichat Plaimas, Kitiporn |
author_facet | Suratanee, Apichat Plaimas, Kitiporn |
author_sort | Suratanee, Apichat |
collection | PubMed |
description | The associations between proteins and diseases are crucial information for investigating pathological mechanisms. However, the number of known and reliable protein-disease associations is quite small. In this study, an analysis framework to infer associations between proteins and diseases was developed based on a large data set of a human protein-protein interaction network integrating an effective network search, namely, the reverse k-nearest neighbor (RkNN) search. The RkNN search was used to identify an impact of a protein on other proteins. Then, associations between proteins and diseases were inferred statistically. The method using the RkNN search yielded a much higher precision than a random selection, standard nearest neighbor search, or when applying the method to a random protein-protein interaction network. All protein-disease pair candidates were verified by a literature search. Supporting evidence for 596 pairs was identified. In addition, cluster analysis of these candidates revealed 10 promising groups of diseases to be further investigated experimentally. This method can be used to identify novel associations to better understand complex relationships between proteins and diseases. |
format | Online Article Text |
id | pubmed-5513527 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-55135272017-07-28 Reverse Nearest Neighbor Search on a Protein-Protein Interaction Network to Infer Protein-Disease Associations Suratanee, Apichat Plaimas, Kitiporn Bioinform Biol Insights Original Research The associations between proteins and diseases are crucial information for investigating pathological mechanisms. However, the number of known and reliable protein-disease associations is quite small. In this study, an analysis framework to infer associations between proteins and diseases was developed based on a large data set of a human protein-protein interaction network integrating an effective network search, namely, the reverse k-nearest neighbor (RkNN) search. The RkNN search was used to identify an impact of a protein on other proteins. Then, associations between proteins and diseases were inferred statistically. The method using the RkNN search yielded a much higher precision than a random selection, standard nearest neighbor search, or when applying the method to a random protein-protein interaction network. All protein-disease pair candidates were verified by a literature search. Supporting evidence for 596 pairs was identified. In addition, cluster analysis of these candidates revealed 10 promising groups of diseases to be further investigated experimentally. This method can be used to identify novel associations to better understand complex relationships between proteins and diseases. SAGE Publications 2017-07-13 /pmc/articles/PMC5513527/ /pubmed/28757797 http://dx.doi.org/10.1177/1177932217720405 Text en © The Author(s) 2017 http://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page(https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Original Research Suratanee, Apichat Plaimas, Kitiporn Reverse Nearest Neighbor Search on a Protein-Protein Interaction Network to Infer Protein-Disease Associations |
title | Reverse Nearest Neighbor Search on a Protein-Protein Interaction Network to Infer Protein-Disease Associations |
title_full | Reverse Nearest Neighbor Search on a Protein-Protein Interaction Network to Infer Protein-Disease Associations |
title_fullStr | Reverse Nearest Neighbor Search on a Protein-Protein Interaction Network to Infer Protein-Disease Associations |
title_full_unstemmed | Reverse Nearest Neighbor Search on a Protein-Protein Interaction Network to Infer Protein-Disease Associations |
title_short | Reverse Nearest Neighbor Search on a Protein-Protein Interaction Network to Infer Protein-Disease Associations |
title_sort | reverse nearest neighbor search on a protein-protein interaction network to infer protein-disease associations |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5513527/ https://www.ncbi.nlm.nih.gov/pubmed/28757797 http://dx.doi.org/10.1177/1177932217720405 |
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