title: A graphic method for identification of novel glioma related genes.
abstract: Glioma, as the most common and lethal intracranial tumor, is a serious disease that causes many deaths every year. Good comprehension of the mechanism underlying this disease is very helpful to design effective treatments. However, up to now, the knowledge of this disease is still limited. It is an important step to understand the mechanism underlying this disease by uncovering its related genes. In this study, a graphic method was proposed to identify novel glioma related genes based on known glioma related genes. A weighted graph was constructed according to the protein-protein interaction information retrieved from STRING and the well-known shortest path algorithm was employed to discover novel genes. The following analysis suggests that some of them are related to the biological process of glioma, proving that our method was effective in identifying novel glioma related genes. We hope that the proposed method would be applied to study other diseases and provide useful information to medical workers, thereby designing effective treatments of different diseases.
authors: Department of Surgery, China-Japan Union Hospital of Jilin University, Changchun 130033, China.
authors: Yu-Fei
authors: YF
authors: Gao
authors: State Key Laboratory of Medical Genomics, Institute of Health Sciences, Shanghai Jiaotong University School of Medicine and Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200025, China.
authors: Yang
authors: 0000-0002-8304-1531
authors: Y
authors: Shu
authors: Endoscopy Center, China-Japan Union Hospital of Jilin University, Changchun 130033, China.
authors: Lei
authors: L
authors: Yang
authors: Department of Surgery, China-Japan Union Hospital of Jilin University, Changchun 130033, China.
authors: Yi-Chun
authors: YC
authors: He
authors: Department of Surgery, China-Japan Union Hospital of Jilin University, Changchun 130033, China.
authors: Li-Peng
authors: LP
authors: Li
authors: Institute of Systems Biology, Shanghai University, Shanghai 200444, China.
authors: GuaHua
authors: G
authors: Huang
authors: CAS-MPG Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
authors: Hai-Peng
authors: HP
authors: Li
authors: Department of Surgery, China-Japan Union Hospital of Jilin University, Changchun 130033, China.
authors: Yang
authors: 0000-0002-1901-9778
authors: Y
authors: Jiang
mesh_terms: D000465:Algorithms; D001932:Brain Neoplasms / Q000235:genetics*; D063990:Gene Ontology; D052138:Genes, Neoplasm; D056726:Genetic Association Studies / Q000379:methods*; D005910:Glioma / Q000235:genetics*; D006801:Humans; D015398:Signal Transduction / Q000235:genetics