Identification of Cell Cycle-Regulated Genes by Convolutional Neural Network
文献类型：期刊论文
| 作者 | Liu, Chenglin2; Cui, Peng2; Huang, Tao1; Cui, Peng3; , |
| 刊名 | COMBINATORIAL CHEMISTRY & HIGH THROUGHPUT SCREENING
 |
| 出版日期 | 2017 |
| 卷号 | 20期号:7页码:603-611 |
| ISSN号 | 1386-2073 |
| 关键词 | Cell cycle cell cycle-regulated genes deep learning convolutional neural network machine learning classification |
| DOI | 10.2174/1386207320666170417144937 |
| 文献子类 | Article |
| 英文摘要 | Background: The cell cycle-regulated genes express periodically with the cell cycle stages, and the identification and study of these genes can provide a deep understanding of the cell cycle process. Large false positives and low overlaps are big problems in cell cycle-regulated gene detection. Methods: Here, a computational framework called DLGene was proposed for cell cycle-regulated gene detection. It is based on the convolutional neural network, a deep learning algorithm representing raw form of data pattern without assumption of their distribution. First, the expression data was transformed to categorical state data to denote the changing state of gene expression, and four different expression patterns were revealed for the reported cell cycle-regulated genes. Then, DLGene was applied to discriminate the non-cell cycle gene and the four subtypes of cell cycle genes. Its performances were compared with six traditional machine learning methods. At last, the biological functions of representative cell cycle genes for each subtype are analyzed. Results: Our method showed better and more balanced performance of sensitivity and specificity comparing to other machine learning algorithms. The cell cycle genes had very different expression pattern with non-cell cycle genes and among the cell-cycle genes, there were four subtypes. Our method not only detects the cell cycle genes, but also describes its expression pattern, such as when its highest expression level is reached and how it changes with time. For each type, we analyzed the biological functions of the representative genes and such results provided novel insight to the cell cycle mechanisms. |
| 学科主题 | Biochemistry & Molecular Biology ; Chemistry ; Pharmacology & Pharmacy |
| WOS关键词 | PERIODICALLY EXPRESSED GENES ; SACCHAROMYCES-CEREVISIAE ; TRANSCRIPTIONAL CIRCUITRY ; CHROMOSOME SEGREGATION ; DEPENDENT KINASES ; YEAST ; GENOME ; MODEL |
| 语种 | 英语 |
| 出版者 | BENTHAM SCIENCE PUBL LTD |
| WOS记录号 | WOS:000413458200004 |
| 版本 | 出版稿 |
| 源URL | [http://202.127.25.144/handle/331004/671]  |
| 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 Biol Sci, Inst Hlth Sci, Shanghai 200031, Peoples R China; 2.Shanghai Jiao Tong Univ, Sch Life Sci & Biotechnol, 800 Dongchuan Rd, Shanghai 200240, Peoples R China; 3.Shanghai Jiao Tong Univ, SJTU Yale Joint Ctr Biostat, Dept Bioinformat, 800 Dongchuan Rd, Shanghai 200240, Peoples R China, |
| 推荐引用方式 GB/T 7714 | Liu, Chenglin,Cui, Peng,Huang, Tao,et al. Identification of Cell Cycle-Regulated Genes by Convolutional Neural Network[J]. COMBINATORIAL CHEMISTRY & HIGH THROUGHPUT SCREENING,2017,20(7):603-611. |
| APA | Liu, Chenglin,Cui, Peng,Huang, Tao,Cui, Peng,&,.(2017).Identification of Cell Cycle-Regulated Genes by Convolutional Neural Network.COMBINATORIAL CHEMISTRY & HIGH THROUGHPUT SCREENING,20(7),603-611. |
| MLA | Liu, Chenglin,et al."Identification of Cell Cycle-Regulated Genes by Convolutional Neural Network".COMBINATORIAL CHEMISTRY & HIGH THROUGHPUT SCREENING 20.7(2017):603-611. |
入库方式： OAI收割
来源：上海营养与健康研究所
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