Inferring novel genes related to oral cancer with a network embedding method and one-class learning algorithms
文献类型：期刊论文
| 作者 | Chen, Lei2,3,4; Cai, Yu-Dong4; Zhang, Yu-Hang1; Huang, Tao1; Huang, Guohua6; Pan, Xiaoyong5; , |
| 刊名 | GENE THERAPY
 |
| 出版日期 | 2019 |
| 卷号 | 26期号:12页码:465-478 |
| 关键词 | drug delivery microneedle exosome keratin hair regrowth transdermal drug delivery |
| ISSN号 | 0969-7128 |
| DOI | 10.1038/s41434-019-0099-y |
| 文献子类 | Article |
| 英文摘要 | Oral cancer (OC) is one of the most common cancers threatening human lives. However, OC pathogenesis has yet to be fully uncovered, and thus designing effective treatments remains difficult. Identifying genes related to OC is an important way for achieving this purpose. In this study, we proposed three computational models for inferring novel OC-related genes. In contrast to previously proposed computational methods, which lacked the learning procedures, each proposed model adopted a one-class learning algorithm, which can provide a deep insight into features of validated OC-related genes. A network embedding algorithm (i.e., node2vec) was applied to the protein-protein interaction network to produce the representation of genes. The features of the OC-related genes were used in the training of the one-class algorithm, and the performance of the final inferring model was improved through a feature selection procedure. Then, candidate genes were produced by applying the trained inferring model to other genes. Three tests were performed to screen out the important candidate genes. Accordingly, we obtained three inferred gene sets, any two of which were different. The inferred genes were also different from previous reported genes and some of them have been included in the public Oral Cancer Gene Database. Finally, we analyzed several inferred genes to confirm whether they are novel OC-related genes. |
| 学科主题 | Research & Experimental Medicine |
| WOS关键词 | PROTEIN INTERACTION NETWORK ; SQUAMOUS-CELL CARCINOMA ; WNT PATHWAY ; EXPRESSION ; IDENTIFICATION ; INVASION ; INFLAMMATION ; POLYMORPHISM ; INTERACTOME ; METASTASIS |
| 语种 | 英语 |
| CSCD记录号 | CSCD:31455874 |
| WOS记录号 | WOS:000510690000002 |
| 出版者 | SPRINGERNATURE |
| 版本 | 出版稿 |
| 源URL | [http://202.127.25.144/handle/331004/1135]  |
| 专题 | 中国科学院上海生命科学研究院营养科学研究所 |
| 作者单位 | 1.Chinese Acad Sci, Shanghai Inst Nutr & Hlth, Shanghai Inst Biol Sci, Shanghai 200031, Peoples R China; 2.East China Normal Univ, Shanghai Key Lab, PMMP, Shanghai 200241, Peoples R China; 3.Shanghai Maritime Univ, Coll Informat Engn, Shanghai 201306, Peoples R China; 4.Shanghai Univ, Sch Life Sci, Shanghai 200444, Peoples R China; 5.Erasmus MC, Dept Med Informat, Rotterdam, Netherlands, 6.Shaoyang Univ, Coll Informat Engn, Shaoyang 422000, Hunan, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Chen, Lei,Cai, Yu-Dong,Zhang, Yu-Hang,et al. Inferring novel genes related to oral cancer with a network embedding method and one-class learning algorithms[J]. GENE THERAPY,2019,26(12):465-478. |
| APA | Chen, Lei.,Cai, Yu-Dong.,Zhang, Yu-Hang.,Huang, Tao.,Huang, Guohua.,...&,.(2019).Inferring novel genes related to oral cancer with a network embedding method and one-class learning algorithms.GENE THERAPY,26(12),465-478. |
| MLA | Chen, Lei,et al."Inferring novel genes related to oral cancer with a network embedding method and one-class learning algorithms".GENE THERAPY 26.12(2019):465-478. |
入库方式： OAI收割
来源：上海营养与健康研究所
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