Application of L-EDA in metabonomics data handling: global metabolite profiling and potential biomarker discovery of epithelial ovarian cancer prognosis
文献类型：期刊论文
| 作者 | Chen, Jing1; Zhang, Yang2; Zhang, Xiaoyan3; Cao, Rui4,7; Chen, Shili1; Huang, Qiang1; Lu, Xin1; Wan, Xiaoping5; Wu, Xiaohua6; Xu, Congjian3 |
| 刊名 | metabolomics
 |
| 出版日期 | 2011-12-01 |
| 卷号 | 7期号:4页码:614-622 |
| 关键词 | Metabonomics Ovarian cancer Prognosis biomarker Solution capacity limited EDA Estimation of distribution algorithms |
| ISSN号 | 待补充 |
| 产权排序 | 1,1 |
| 通讯作者 | 许国旺 |
| 中文摘要 | application of l-eda in metabonomics data handling: global metabolite profiling and potential biomarker discovery of epithelial ovarian cancer prognosis |
| 英文摘要 | solution capacity limited estimation of distribution algorithm (l-eda) is proposed and applied to ovarian cancer prognosis biomarker discovery to expatiate on its potential in metabonomics studies. sera from healthy women, epithelial ovarian cancer (eoc), recurrent eoc and non-recurrent eoc patients were analyzed by liquid chromatography-mass spectrometry. the metabolite data were processed by l-eda to discover potential eoc prognosis biomarkers. after l-eda filtration, 78 out of 714 variables were selected, and the relationships among four groups were visualized by principle component analysis, it was observed that with the l-eda filtered variables, non-recurrent eoc and recurrent eoc groups could be separated, which was not possible with the initial data. five metabolites (six variables) with p < 0.05 in wilcoxon test were discovered as potential eoc prognosis biomarkers, and their classification accuracy rates were 86.9% for recurrent eoc and non-recurrent eoc, and 88.7% for healthy + non-recurrent eoc and eoc + recurrent eoc. the results show that l-eda is a powerful tool for potential biomarker discovery in metabonomics study. |
| WOS标题词 | science & technology ; life sciences & biomedicine |
| 学科主题 | 物理化学 |
| 类目[WOS] | endocrinology & metabolism |
| 研究领域[WOS] | endocrinology & metabolism |
| 关键词[WOS] | research-and-development ; support vector machines ; distribution algorithms ; spectrometry data ; feature-selection ; neural-networks ; nmr-spectra ; classification ; metabolomics ; models |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000295991900015 |
| 公开日期 | 2012-07-09 |
| 源URL | [http://159.226.238.44/handle/321008/115667]  |
| 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, CAS Key Lab Separat Sci Analyt Chem, Dalian 116023, Peoples R China 2.Dalian Univ Technol, Sch Comp Sci & Technol, Dalian 116024, Peoples R China 3.Fudan Univ, Inst Biomed Sci, Shanghai Key Lab Female Reprod Endocrine Related, Obstet & Gynecol Hosp,Shanghai Med Sch, Shanghai 200011, Peoples R China 4.Dalian Med Univ, Dept Obstet, Dalian 116033, Peoples R China 5.Shanghai Jiao Tong Univ, Sch Med, Int Peace Matern & Child Hlth Hosp, Shanghai 200030, Peoples R China 6.Fudan Univ, Dept Gynecol Oncol, Canc Hosp, Shanghai 200032, Peoples R China 7.Dalian Med Univ, Gynecol Hosp, Dalian 116033, Peoples R China |
| 推荐引用方式 GB/T 7714 | Chen, Jing,Zhang, Yang,Zhang, Xiaoyan,et al. Application of L-EDA in metabonomics data handling: global metabolite profiling and potential biomarker discovery of epithelial ovarian cancer prognosis[J]. metabolomics,2011,7(4):614-622. |
| APA | Chen, Jing.,Zhang, Yang.,Zhang, Xiaoyan.,Cao, Rui.,Chen, Shili.,...&Lin, Xiaohui.(2011).Application of L-EDA in metabonomics data handling: global metabolite profiling and potential biomarker discovery of epithelial ovarian cancer prognosis.metabolomics,7(4),614-622. |
| MLA | Chen, Jing,et al."Application of L-EDA in metabonomics data handling: global metabolite profiling and potential biomarker discovery of epithelial ovarian cancer prognosis".metabolomics 7.4(2011):614-622. |
入库方式： OAI收割
来源：大连化学物理研究所
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