Identifying Gastric Cancer Related Genes Using the Shortest Path Algorithm and Protein-Protein Interaction Network
Author(s) -
Yang Jiang,
Yang Shu,
Ying Shi,
Lipeng Li,
Fei Yuan,
Hui Ren
Publication year - 2014
Publication title -
biomed research international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.772
H-Index - 126
eISSN - 2314-6141
pISSN - 2314-6133
DOI - 10.1155/2014/371397
Subject(s) - cancer , mechanism (biology) , disease , gene , identification (biology) , biology , bioinformatics , computational biology , medicine , genetics , pathology , philosophy , botany , epistemology
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.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom