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| Content Provider | IET Digital Library |
|---|---|
| Author | Fu, Changhe Deng, Su Song, Qiqing Jing, Ling |
| Abstract | Identification of oncogenic genes from a large sample number of genomic data is a challenge. In this study, a well-established latent factor model, Bayesian factor and regression model, are applied to predict unknown colon cancer related genes from colon adenocarcinoma genomic data. Four important latent factors were addressed by the latent factor model, focusing on characterisation of heterogeneity of expression patterns of specific oncogenic genes by using microarray data of 174 colon cancer patients. Based on the fact that variables included in the same latent factor have some common characteristics and known cancer related genes in Online Mendelian Inheritance in Man, the authors found that the four latent factors can be employed to predict unknown colon cancer related genes that were never reported in the literature. The authors validated 15 identified genes by checking their somatic mutations of the same patients from DNA sequencing data. |
| Starting Page | 165 |
| Ending Page | 169 |
| Page Count | 5 |
| ISSN | 17518849 |
| Volume Number | 7 |
| e-ISSN | 17518857 |
| Issue Number | Issue 5, Oct (2013) |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/iet-syb/7/5 |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/iet-syb.2012.0057 |
| Journal | IET Systems Biology |
| Access Restriction | Open |
| Rights Holder | © The Institution of Engineering and Technology |
| Subject Keyword | Bayes Method Bayesian Factor Biological Organs Biology And Medical Computing Biomedical Engineering Cancer Colon Adenocarcinoma Colon Cancer Related Genes DNA DNA Microarray Data DNA Sequencing Data Expression Pattern Genetics Genomic Data Genomic Technique Genomics Heterogeneity Lab-on-a-chip Latent Factor Analysis Medical Diagnostic Computing Molecular Biophysics Oncogenic Genes Online Mendelian Inheritance in Man Physiological Model Regression Analysis Somatic Mutations |
| Content Type | Text |
| Resource Type | Article |
| Subject | Cell Biology Genetics Molecular Biology Modeling and Simulation Biotechnology |
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