Identification of New Candidate Genes and Chemicals Related to Esophageal Cancer Using a Hybrid Interaction Network of Chemicals and Proteins |
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Authors: | Yu-Fei Gao Fei Yuan Junbao Liu Li-Peng Li Yi-Chun He Ru-Jian Gao Yu-Dong Cai Yang Jiang |
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Institution: | 1. Department of Surgery, China-Japan Union Hospital of Jilin University, Changchun 130033, People’s Republic of China.; 2. Institute of Health Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, People’s Republic of China.; 3. College of Life Science, Shanghai University, Shanghai 200444, People’s Republic of China.; University of Georgia, UNITED STATES, |
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Abstract: | Cancer is a serious disease responsible for many deaths every year in both developed and developing countries. One reason is that the mechanisms underlying most types of cancer are still mysterious, creating a great block for the design of effective treatments. In this study, we attempted to clarify the mechanism underlying esophageal cancer by searching for novel genes and chemicals. To this end, we constructed a hybrid network containing both proteins and chemicals, and generalized an existing computational method previously used to identify disease genes to identify new candidate genes and chemicals simultaneously. Based on jackknife test, our generalized method outperforms or at least performs at the same level as those obtained by a widely used method - the Random Walk with Restart (RWR). The analysis results of the final obtained genes and chemicals demonstrated that they highly shared gene ontology (GO) terms and KEGG pathways with direct and indirect associations with esophageal cancer. In addition, we also discussed the likelihood of selected candidate genes and chemicals being novel genes and chemicals related to esophageal cancer. |
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