ArticleBioMed research international2014
Identifying gastric cancer related genes using the shortest path algorithm and protein-protein interaction network.
Article in BioMed research international, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Systems Medicine Design for Triple-Negative Breast Cancer and Non-Triple-Negative Breast Cancer Based on Systems Identification and Carcinogenic Mechanisms.International journal of molecular sciences · 2021Article
- Matrix metalloproteinase expression and molecular interaction network analysis in gastric cancer.Oncology letters · 2016Article
- Identification of novel candidate drivers connecting different dysfunctional levels for lung adenocarcinoma using protein-protein interactions and a shortest path approach.Scientific reports · 2016Article
- PPI network analysis of mRNA expression profile of ezrin knockdown in esophageal squamous cell carcinoma.BioMed research international · 2014Article
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Authors and funding
6 authors.
Funding
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Abstract
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.
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