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Biomarker Identification for Prostate Cancer and Lymph Node Metastasis from Microarray Data and Protein Interaction Network Using Gene Prioritization Method

Finding a genetic disease-related gene is not a trivial task. Therefore, computational methods are needed to present clues to the biomedical community to explore genes that are more likely to be related to a specific disease as biomarker. We present biomarker identification problem using gene priori...

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Detalles Bibliográficos
Autores principales: Arias, Carlos Roberto, Yeh, Hsiang-Yuan, Soo, Von-Wun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Scientific World Journal 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3354662/
https://www.ncbi.nlm.nih.gov/pubmed/22654636
http://dx.doi.org/10.1100/2012/842727
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author Arias, Carlos Roberto
Yeh, Hsiang-Yuan
Soo, Von-Wun
author_facet Arias, Carlos Roberto
Yeh, Hsiang-Yuan
Soo, Von-Wun
author_sort Arias, Carlos Roberto
collection PubMed
description Finding a genetic disease-related gene is not a trivial task. Therefore, computational methods are needed to present clues to the biomedical community to explore genes that are more likely to be related to a specific disease as biomarker. We present biomarker identification problem using gene prioritization method called gene prioritization from microarray data based on shortest paths, extended with structural and biological properties and edge flux using voting scheme (GP-MIDAS-VXEF). The method is based on finding relevant interactions on protein interaction networks, then scoring the genes using shortest paths and topological analysis, integrating the results using a voting scheme and a biological boosting. We applied two experiments, one is prostate primary and normal samples and the other is prostate primary tumor with and without lymph nodes metastasis. We used 137 truly prostate cancer genes as benchmark. In the first experiment, GP-MIDAS-VXEF outperforms all the other state-of-the-art methods in the benchmark by retrieving the truest related genes from the candidate set in the top 50 scores found. We applied the same technique to infer the significant biomarkers in prostate cancer with lymph nodes metastasis which is not established well.
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spelling pubmed-33546622012-05-31 Biomarker Identification for Prostate Cancer and Lymph Node Metastasis from Microarray Data and Protein Interaction Network Using Gene Prioritization Method Arias, Carlos Roberto Yeh, Hsiang-Yuan Soo, Von-Wun ScientificWorldJournal Research Article Finding a genetic disease-related gene is not a trivial task. Therefore, computational methods are needed to present clues to the biomedical community to explore genes that are more likely to be related to a specific disease as biomarker. We present biomarker identification problem using gene prioritization method called gene prioritization from microarray data based on shortest paths, extended with structural and biological properties and edge flux using voting scheme (GP-MIDAS-VXEF). The method is based on finding relevant interactions on protein interaction networks, then scoring the genes using shortest paths and topological analysis, integrating the results using a voting scheme and a biological boosting. We applied two experiments, one is prostate primary and normal samples and the other is prostate primary tumor with and without lymph nodes metastasis. We used 137 truly prostate cancer genes as benchmark. In the first experiment, GP-MIDAS-VXEF outperforms all the other state-of-the-art methods in the benchmark by retrieving the truest related genes from the candidate set in the top 50 scores found. We applied the same technique to infer the significant biomarkers in prostate cancer with lymph nodes metastasis which is not established well. The Scientific World Journal 2012-05-02 /pmc/articles/PMC3354662/ /pubmed/22654636 http://dx.doi.org/10.1100/2012/842727 Text en Copyright © 2012 Carlos Roberto Arias et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Arias, Carlos Roberto
Yeh, Hsiang-Yuan
Soo, Von-Wun
Biomarker Identification for Prostate Cancer and Lymph Node Metastasis from Microarray Data and Protein Interaction Network Using Gene Prioritization Method
title Biomarker Identification for Prostate Cancer and Lymph Node Metastasis from Microarray Data and Protein Interaction Network Using Gene Prioritization Method
title_full Biomarker Identification for Prostate Cancer and Lymph Node Metastasis from Microarray Data and Protein Interaction Network Using Gene Prioritization Method
title_fullStr Biomarker Identification for Prostate Cancer and Lymph Node Metastasis from Microarray Data and Protein Interaction Network Using Gene Prioritization Method
title_full_unstemmed Biomarker Identification for Prostate Cancer and Lymph Node Metastasis from Microarray Data and Protein Interaction Network Using Gene Prioritization Method
title_short Biomarker Identification for Prostate Cancer and Lymph Node Metastasis from Microarray Data and Protein Interaction Network Using Gene Prioritization Method
title_sort biomarker identification for prostate cancer and lymph node metastasis from microarray data and protein interaction network using gene prioritization method
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3354662/
https://www.ncbi.nlm.nih.gov/pubmed/22654636
http://dx.doi.org/10.1100/2012/842727
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