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Regularized Multi-View Subspace Clustering for Common Modules Across Cancer Stages
Discovering the common modules that are co-expressed across various stages can lead to an improved understanding of the underlying molecular mechanisms of cancers. There is a shortage of efficient tools for integrative analysis of gene expression and protein interaction networks for discovering comm...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6102576/ https://www.ncbi.nlm.nih.gov/pubmed/29701681 http://dx.doi.org/10.3390/molecules23051016 |
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author | Zhang, Enli Ma, Xiaoke |
author_facet | Zhang, Enli Ma, Xiaoke |
author_sort | Zhang, Enli |
collection | PubMed |
description | Discovering the common modules that are co-expressed across various stages can lead to an improved understanding of the underlying molecular mechanisms of cancers. There is a shortage of efficient tools for integrative analysis of gene expression and protein interaction networks for discovering common modules associated with cancer progression. To address this issue, we propose a novel regularized multi-view subspace clustering (rMV-spc) algorithm to obtain a representation matrix for each stage and a joint representation matrix that balances the agreement across various stages. To avoid the heterogeneity of data, the protein interaction network is incorporated into the objective of rMV-spc via regularization. Based on the interior point algorithm, we solve the optimization problem to obtain the common modules. By using artificial networks, we demonstrate that the proposed algorithm outperforms state-of-the-art methods in terms of accuracy. Furthermore, the rMV-spc discovers common modules in breast cancer networks based on the breast data, and these modules serve as biomarkers to predict stages of breast cancer. The proposed model and algorithm effectively integrate heterogeneous data for dynamic modules. |
format | Online Article Text |
id | pubmed-6102576 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-61025762018-11-13 Regularized Multi-View Subspace Clustering for Common Modules Across Cancer Stages Zhang, Enli Ma, Xiaoke Molecules Article Discovering the common modules that are co-expressed across various stages can lead to an improved understanding of the underlying molecular mechanisms of cancers. There is a shortage of efficient tools for integrative analysis of gene expression and protein interaction networks for discovering common modules associated with cancer progression. To address this issue, we propose a novel regularized multi-view subspace clustering (rMV-spc) algorithm to obtain a representation matrix for each stage and a joint representation matrix that balances the agreement across various stages. To avoid the heterogeneity of data, the protein interaction network is incorporated into the objective of rMV-spc via regularization. Based on the interior point algorithm, we solve the optimization problem to obtain the common modules. By using artificial networks, we demonstrate that the proposed algorithm outperforms state-of-the-art methods in terms of accuracy. Furthermore, the rMV-spc discovers common modules in breast cancer networks based on the breast data, and these modules serve as biomarkers to predict stages of breast cancer. The proposed model and algorithm effectively integrate heterogeneous data for dynamic modules. MDPI 2018-04-26 /pmc/articles/PMC6102576/ /pubmed/29701681 http://dx.doi.org/10.3390/molecules23051016 Text en © 2018 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Zhang, Enli Ma, Xiaoke Regularized Multi-View Subspace Clustering for Common Modules Across Cancer Stages |
title | Regularized Multi-View Subspace Clustering for Common Modules Across Cancer Stages |
title_full | Regularized Multi-View Subspace Clustering for Common Modules Across Cancer Stages |
title_fullStr | Regularized Multi-View Subspace Clustering for Common Modules Across Cancer Stages |
title_full_unstemmed | Regularized Multi-View Subspace Clustering for Common Modules Across Cancer Stages |
title_short | Regularized Multi-View Subspace Clustering for Common Modules Across Cancer Stages |
title_sort | regularized multi-view subspace clustering for common modules across cancer stages |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6102576/ https://www.ncbi.nlm.nih.gov/pubmed/29701681 http://dx.doi.org/10.3390/molecules23051016 |
work_keys_str_mv | AT zhangenli regularizedmultiviewsubspaceclusteringforcommonmodulesacrosscancerstages AT maxiaoke regularizedmultiviewsubspaceclusteringforcommonmodulesacrosscancerstages |