Integrated entropy-based approach for analyzing exons and introns in DNA sequences
文献类型：期刊论文
| 作者 | Li, Junyi2; Zhang, Li2; Li, Huinian2; Ping, Yuan2; Xu, Qingzhe2; Wang, Yadong2,3; Wang, Rongjie3; Tan, Renjie3; Liu, Bo3; Wang, Zhen1 |
| 刊名 | BMC BIOINFORMATICS
 |
| 出版日期 | 2019 |
| 卷号 | 20期号:-页码:283 |
| 关键词 | Information entropy Generalized topological entropy DNA sequences Exon and intron prediction Genomic signal processing |
| ISSN号 | 1471-2105 |
| DOI | 10.1186/s12859-019-2772-y |
| 文献子类 | Article; Proceedings Paper |
| 英文摘要 | BackgroundNumerous essential algorithms and methods, including entropy-based quantitative methods, have been developed to analyze complex DNA sequences since the last decade. Exons and introns are the most notable components of DNA and their identification and prediction are always the focus of state-of-the-art research.ResultsIn this study, we designed an integrated entropy-based analysis approach, which involves modified topological entropy calculation, genomic signal processing (GSP) method and singular value decomposition (SVD), to investigate exons and introns in DNA sequences. We optimized and implemented the topological entropy and the generalized topological entropy to calculate the complexity of DNA sequences, highlighting the characteristics of repetition sequences. By comparing digitalizing entropy values of exons and introns, we observed that they are significantly different. After we converted DNA data to numerical topological entropy value, we applied SVD method to effectively investigate exon and intron regions on a single gene sequence. Additionally, several genes across five species are used for exon predictions.ConclusionsOur approach not only helps to explore the complexity of DNA sequence and its functional elements, but also provides an entropy-based GSP method to analyze exon and intron regions. Our work is feasible across different species and extendable to analyze other components in both coding and noncoding region of DNA sequences. |
| 学科主题 | Biochemistry & Molecular Biology ; Biotechnology & Applied Microbiology ; Mathematical & Computational Biology |
| WOS关键词 | GENE-FUNCTION PREDICTION |
| 语种 | 英语 |
| WOS记录号 | WOS:000470984700008 |
| 出版者 | BMC |
| 版本 | 出版稿 |
| 源URL | [http://202.127.25.144/handle/331004/560]  |
| 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, CAS MPG Partner Inst Computat Biol, Univ Chinese Acad Sci,CAS Key Lab Computat Biol, Shanghai Inst Nutr & Hlth,Shanghai Inst Biol Sci, Shanghai 200031, Peoples R China, 2.Harbin Inst Technol Shenzhen, Sch Comp Sci & Technol, Shenzhen 518055, Guangdong, Peoples R China; 3.Harbin Inst Technol, Sch Comp Sci & Technol, Harbin 150001, Heilongjiang, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Li, Junyi,Zhang, Li,Li, Huinian,et al. Integrated entropy-based approach for analyzing exons and introns in DNA sequences[J]. BMC BIOINFORMATICS,2019,20(-):283. |
| APA | Li, Junyi.,Zhang, Li.,Li, Huinian.,Ping, Yuan.,Xu, Qingzhe.,...&,.(2019).Integrated entropy-based approach for analyzing exons and introns in DNA sequences.BMC BIOINFORMATICS,20(-),283. |
| MLA | Li, Junyi,et al."Integrated entropy-based approach for analyzing exons and introns in DNA sequences".BMC BIOINFORMATICS 20.-(2019):283. |
入库方式： OAI收割
来源：上海营养与健康研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。