Data mining of the cancer-related lncRNAs GO terms and KEGG pathways by using mRMR method
文献类型：期刊论文
| 作者 | Yuan, Fei1; Lu, Lin2; Zhang, YuHang3; Wang, ShaoPeng4; Cai, Yu-Dong4; , |
| 刊名 | MATHEMATICAL BIOSCIENCES
 |
| 出版日期 | 2018 |
| 卷号 | 304期号:-页码:1-8 |
| 关键词 | LncRNA Cancer-related lncRNA GO term KEGG pathway Max-relevance Min-redundancy |
| ISSN号 | 0025-5564 |
| DOI | 10.1016/j.mbs.2018.08.001 |
| 文献子类 | Article |
| 英文摘要 | LncRNAs plays an important role in the regulation of gene expression. Identification of cancer-related lncRNAs GO terms and KEGG pathways is great helpful for revealing cancer-related functional biological processes. Therefore, in this study, we proposed a computational method to identify novel cancer-related IncRNAs GO terms and KEGG pathways. By using existing lncRNA database and Max-relevance MM-redundancy (mRMR) method, GO terms and KEGG pathways were evaluated based on their importance on distinguishing cancerrelated and non-cancer-related lncRNAs. Finally, GO terms and KEGG pathways with high importance were presented and analyzed. Our literature reviewing showed that the top 10 ranked GO terms and pathways were really related to interpretable tumorigenesis according to recent publications. |
| 学科主题 | Life Sciences & Biomedicine - Other Topics ; Mathematical & Computational Biology |
| WOS关键词 | LONG NONCODING RNA ; CELL-CYCLE PROGRESSION ; MESENCHYMAL STEM-CELLS ; FEATURE-SELECTION ; OSTEOGENIC DIFFERENTIATION ; MOLECULAR FRAGMENTS ; MUTUAL INFORMATION ; COLORECTAL-CANCER ; ANALYSIS REVEALS ; DOWN-REGULATION |
| 语种 | 英语 |
| WOS记录号 | WOS:000444929000001 |
| 出版者 | ELSEVIER SCIENCE INC |
| 版本 | 出版稿 |
| 源URL | [http://202.127.25.144/handle/331004/1034]  |
| 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.Binzhou Med Univ Hosp, Dept Sci & Technol, Binzhou 256603, Shandong, Peoples R China; 2.Columbia Univ, Med Ctr, Dept Radiol, New York, NY 10032 USA; 3.Chinese Acad Sci, Shanghai Inst Biol Sci, Inst Hlth Sci, Shanghai 200031, Peoples R China; 4.Shanghai Univ, Sch Life Sci, Shanghai 200444, Peoples R China, |
| 推荐引用方式 GB/T 7714 | Yuan, Fei,Lu, Lin,Zhang, YuHang,et al. Data mining of the cancer-related lncRNAs GO terms and KEGG pathways by using mRMR method[J]. MATHEMATICAL BIOSCIENCES,2018,304(-):1-8. |
| APA | Yuan, Fei,Lu, Lin,Zhang, YuHang,Wang, ShaoPeng,Cai, Yu-Dong,&,.(2018).Data mining of the cancer-related lncRNAs GO terms and KEGG pathways by using mRMR method.MATHEMATICAL BIOSCIENCES,304(-),1-8. |
| MLA | Yuan, Fei,et al."Data mining of the cancer-related lncRNAs GO terms and KEGG pathways by using mRMR method".MATHEMATICAL BIOSCIENCES 304.-(2018):1-8. |
入库方式： OAI收割
来源：上海营养与健康研究所
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