Revealing alzheimer’s disease genes spectrum in the whole-genome by machine learning
文献类型：期刊论文
| 作者 | Huang,Xiaoyan1,2,3; Liu,Hankui2,3; Li,Xinming4; Guan,Liping2,3; Li,Jiankang2,3; Tellier,Laurent Christian Asker M.2,3,5; Yang,Huanming2,6; Wang,Jian2,6; Zhang,Jianguo2,3,7 |
| 刊名 | Bmc neurology
 |
| 出版日期 | 2018-01-10 |
| 卷号 | 18期号:1 |
| ISSN号 | 1471-2377 |
| 关键词 | Alzheimer’s disease Gene Machine learning |
| DOI | 10.1186/s12883-017-1010-3 |
| 通讯作者 | Zhang,jianguo(zhangjg@genomics.cn) |
| 英文摘要 | Abstractbackgroundalzheimer’s disease (ad) is an important, progressive neurodegenerative disease, with a complex genetic architecture. a key goal of biomedical research is to seek out disease risk genes, and to elucidate the function of these risk genes in the development of disease. for this purpose, expanding the ad-associated gene set is necessary. in past research, the prediction methods for ad related genes has been limited in their exploration of the target genome regions. we here present a genome-wide method for ad candidate genes predictions.methodswe present a machine learning approach (svm), based upon integrating gene expression data with human brain-specific gene network data, to discover the full spectrum of ad genes across the whole genome.resultswe classified ad candidate genes with an accuracy and the area under the receiver operating characteristic (roc) curve of 84.56% and 94%. our approach provides a supplement for the spectrum of ad-associated genes extracted from more than 20,000 genes in a genome wide scale.conclusionsin this study, we have elucidated the whole-genome spectrum of ad, using a machine learning approach. through this method, we expect for the candidate gene catalogue to provide a more comprehensive annotation of ad for researchers. |
| 语种 | 英语 |
| 出版者 | BioMed Central |
| WOS记录号 | BMC:10.1186/S12883-017-1010-3 |
| URI标识 | http://www.irgrid.ac.cn/handle/1471x/2374353 |
| 专题 | 中国科学院大学 |
| 通讯作者 | Zhang,Jianguo |
| 作者单位 | 1.University of Chinese Academy of Sciences; BGI Education Center 2. 3. 4. 5. 6.James D. Watson Institute of Genome Sciences 7. |
| 推荐引用方式 GB/T 7714 | Huang,Xiaoyan,Liu,Hankui,Li,Xinming,et al. Revealing alzheimer’s disease genes spectrum in the whole-genome by machine learning[J]. Bmc neurology,2018,18(1). |
| APA | Huang,Xiaoyan.,Liu,Hankui.,Li,Xinming.,Guan,Liping.,Li,Jiankang.,...&Zhang,Jianguo.(2018).Revealing alzheimer’s disease genes spectrum in the whole-genome by machine learning.Bmc neurology,18(1). |
| MLA | Huang,Xiaoyan,et al."Revealing alzheimer’s disease genes spectrum in the whole-genome by machine learning".Bmc neurology 18.1(2018). |
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来源：中国科学院大学
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