Cargando…
Identifying Gastric Cancer Related Genes Using the Shortest Path Algorithm and Protein-Protein Interaction Network
Gastric cancer, as one of the leading causes of cancer related deaths worldwide, causes about 800,000 deaths per year. Up to now, the mechanism underlying this disease is still not totally uncovered. Identification of related genes of this disease is an important step which can help to understand th...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3963223/ https://www.ncbi.nlm.nih.gov/pubmed/24729971 http://dx.doi.org/10.1155/2014/371397 |
_version_ | 1782308487151222784 |
---|---|
author | Jiang, Yang Shu, Yang Shi, Ying Li, Li-Peng Yuan, Fei Ren, Hui |
author_facet | Jiang, Yang Shu, Yang Shi, Ying Li, Li-Peng Yuan, Fei Ren, Hui |
author_sort | Jiang, Yang |
collection | PubMed |
description | Gastric cancer, as one of the leading causes of cancer related deaths worldwide, causes about 800,000 deaths per year. Up to now, the mechanism underlying this disease is still not totally uncovered. Identification of related genes of this disease is an important step which can help to understand the mechanism underlying this disease, thereby designing effective treatments. In this study, some novel gastric cancer related genes were discovered based on the knowledge of known gastric cancer related ones. These genes were searched by applying the shortest path algorithm in protein-protein interaction network. The analysis results suggest that some of them are indeed involved in the biological process of gastric cancer, which indicates that they are the actual gastric cancer related genes with high probability. It is hopeful that the findings in this study may help promote the study of this disease and the methods can provide new insights to study various diseases. |
format | Online Article Text |
id | pubmed-3963223 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-39632232014-04-13 Identifying Gastric Cancer Related Genes Using the Shortest Path Algorithm and Protein-Protein Interaction Network Jiang, Yang Shu, Yang Shi, Ying Li, Li-Peng Yuan, Fei Ren, Hui Biomed Res Int Research Article Gastric cancer, as one of the leading causes of cancer related deaths worldwide, causes about 800,000 deaths per year. Up to now, the mechanism underlying this disease is still not totally uncovered. Identification of related genes of this disease is an important step which can help to understand the mechanism underlying this disease, thereby designing effective treatments. In this study, some novel gastric cancer related genes were discovered based on the knowledge of known gastric cancer related ones. These genes were searched by applying the shortest path algorithm in protein-protein interaction network. The analysis results suggest that some of them are indeed involved in the biological process of gastric cancer, which indicates that they are the actual gastric cancer related genes with high probability. It is hopeful that the findings in this study may help promote the study of this disease and the methods can provide new insights to study various diseases. Hindawi Publishing Corporation 2014 2014-03-05 /pmc/articles/PMC3963223/ /pubmed/24729971 http://dx.doi.org/10.1155/2014/371397 Text en Copyright © 2014 Yang Jiang 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 Jiang, Yang Shu, Yang Shi, Ying Li, Li-Peng Yuan, Fei Ren, Hui Identifying Gastric Cancer Related Genes Using the Shortest Path Algorithm and Protein-Protein Interaction Network |
title | Identifying Gastric Cancer Related Genes Using the Shortest Path Algorithm and Protein-Protein Interaction Network |
title_full | Identifying Gastric Cancer Related Genes Using the Shortest Path Algorithm and Protein-Protein Interaction Network |
title_fullStr | Identifying Gastric Cancer Related Genes Using the Shortest Path Algorithm and Protein-Protein Interaction Network |
title_full_unstemmed | Identifying Gastric Cancer Related Genes Using the Shortest Path Algorithm and Protein-Protein Interaction Network |
title_short | Identifying Gastric Cancer Related Genes Using the Shortest Path Algorithm and Protein-Protein Interaction Network |
title_sort | identifying gastric cancer related genes using the shortest path algorithm and protein-protein interaction network |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3963223/ https://www.ncbi.nlm.nih.gov/pubmed/24729971 http://dx.doi.org/10.1155/2014/371397 |
work_keys_str_mv | AT jiangyang identifyinggastriccancerrelatedgenesusingtheshortestpathalgorithmandproteinproteininteractionnetwork AT shuyang identifyinggastriccancerrelatedgenesusingtheshortestpathalgorithmandproteinproteininteractionnetwork AT shiying identifyinggastriccancerrelatedgenesusingtheshortestpathalgorithmandproteinproteininteractionnetwork AT lilipeng identifyinggastriccancerrelatedgenesusingtheshortestpathalgorithmandproteinproteininteractionnetwork AT yuanfei identifyinggastriccancerrelatedgenesusingtheshortestpathalgorithmandproteinproteininteractionnetwork AT renhui identifyinggastriccancerrelatedgenesusingtheshortestpathalgorithmandproteinproteininteractionnetwork |