A Computational Method of Defining Potential Biomarkers based on Differential Sub-Networks
文献类型：期刊论文
| 作者 | Yao, Weihong2; Lin, Xiaohui2; Zeng, Jun1; Huang, Xin2; Wang, Lichao1; Yin, Peiyuan1; Zhou, Lina1; Hu, Chunxiu1 |
| 刊名 | SCIENTIFIC REPORTS
 |
| 出版日期 | 2017-10-30 |
| 卷号 | 7 |
| 英文摘要 | Analyzing omics data from a network-based perspective can facilitate biomarker discovery. To improve disease diagnosis and identify prospective information indicating the onset of complex disease, a computational method for identifying potential biomarkers based on differential sub-networks (PBDSN) is developed. In PB-DSN, Pearson correlation coefficient (PCC) is used to measure the relationship between feature ratios and to infer potential networks. A differential sub-network is extracted to identify crucial information for discriminating different groups and indicating the emergence of complex diseases. Subsequently, PB-DSN defines potential biomarkers based on the topological analysis of these differential sub-networks. In this study, PB-DSN is applied to handle a static genomics dataset of small, round blue cell tumors and a time-series metabolomics dataset of hepatocellular carcinoma. PB-DSN is compared with support vector machine-recursive feature elimination, multivariate empirical Bayes statistics, analyzing time-series data based on dynamic networks, molecular networks based on PCC, PinnacleZ, graph-based iterative group analysis, KeyPathwayMiner and BioNet. The better performance of PB-DSN not only demonstrates its effectiveness for the identification of discriminative features that facilitate disease classification, but also shows its potential for the identification of warning signals. |
| WOS标题词 | Science & Technology |
| 类目[WOS] | Multidisciplinary Sciences |
| 研究领域[WOS] | Science & Technology - Other Topics |
| 关键词[WOS] | CARDIOVASCULAR-DISEASE ; METABOLOMICS DATA ; GENE-EXPRESSION ; CANCER ; CLASSIFICATION ; IDENTIFICATION ; CARCINOMA ; SELECTION ; MODULES ; MARKERS |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000414131700032 |
| 源URL | [http://cas-ir.dicp.ac.cn/handle/321008/149719]  |
| 专题 | 大连化学物理研究所_中国科学院大连化学物理研究所 |
| 作者单位 | 1.Chinese Acad Sci, Dalian Inst Chem Phys, Key Lab Separat Sci Analyt Chem, Dalian 116023, Peoples R China 2.Dalian Univ Technol, Sch Comp Sci & Technol, Dalian 116024, Peoples R China |
| 推荐引用方式 GB/T 7714 | Yao, Weihong,Lin, Xiaohui,Zeng, Jun,et al. A Computational Method of Defining Potential Biomarkers based on Differential Sub-Networks[J]. SCIENTIFIC REPORTS,2017,7. |
| APA | Yao, Weihong.,Lin, Xiaohui.,Zeng, Jun.,Huang, Xin.,Wang, Lichao.,...&Hu, Chunxiu.(2017).A Computational Method of Defining Potential Biomarkers based on Differential Sub-Networks.SCIENTIFIC REPORTS,7. |
| MLA | Yao, Weihong,et al."A Computational Method of Defining Potential Biomarkers based on Differential Sub-Networks".SCIENTIFIC REPORTS 7(2017). |
入库方式： OAI收割
来源：大连化学物理研究所
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