Knowledge Management System of Hefei Institute of Physical Science,CAS
A novel conjoint triad auto covariance (CTAC) coding method for predicting protein-protein interaction based on amino acid sequence. | |
Wang X(王雪) | |
2019-04-18 | |
发表期刊 | Mathematical Biosciences |
ISSN | 0025-5564 |
摘要 | Protein-protein interactions (PPIs) play a crucial role in the life-sustaining activities of organisms. Although various methods for the prediction of PPIs have been developed in the past decades, their robustness and predic
tion accuracy need to be improved. Therefore, it is necessary to develop an effective and accurate method to predict PPIs. Aiming at making sure that PPIs can be predicted effectively, in this paper, we propose a new sequence-based approach based on deep neural network (DNN) and conjoint triad auto covariance (CTAC) to improve the effectiveness of predicting PPIs. The coding method of CTAC combines the advantages of conjoint triad and auto covariance. Therefore, the CTAC can obtain more PPIs information from the amino acid sequence. The model of DNN-CTAC achieved an accuracy of 98.37%, recall of 99.41%, area under the curve (AUC) of 99.24% and loss of 22.7%, respectively, on human dataset. These results indicate that DNNCTAC can enhance the predictive power of PPIs and can significantly enhance the accuracy of the prediction. And, it has proved to be a useful complement to future proteomics research. The source codes and all datasets are available at https: //github.com/smalltalkman/hppi-tensorflow.
|
关键词 | Deep neural networks Protein-protein interaction Conjoint triad auto covariance |
学科门类 | 工学::计算机科学与技术(可授工学、理学学位) |
DOI | doi.org/10.1016/j.mbs.2019.04.002 |
URL | 查看原文 |
收录类别 | SCI |
语种 | 英语 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.hfcas.ac.cn:8080/handle/334002/126102 |
专题 | 中国科学院合肥物质科学研究院 |
作者单位 | Institute of Technical Biology & Agriculture Engineering, Chinese Academy of Sciences |
推荐引用方式 GB/T 7714 | Wang X. A novel conjoint triad auto covariance (CTAC) coding method for predicting protein-protein interaction based on amino acid sequence.[J]. Mathematical Biosciences,2019. |
APA | Wang X.(2019).A novel conjoint triad auto covariance (CTAC) coding method for predicting protein-protein interaction based on amino acid sequence..Mathematical Biosciences. |
MLA | Wang X."A novel conjoint triad auto covariance (CTAC) coding method for predicting protein-protein interaction based on amino acid sequence.".Mathematical Biosciences (2019). |
条目包含的文件 | 条目无相关文件。 |
个性服务 |
推荐该条目 |
保存到收藏夹 |
查看访问统计 |
导出为Endnote文件 |
谷歌学术 |
谷歌学术中相似的文章 |
[Wang X(王雪)]的文章 |
百度学术 |
百度学术中相似的文章 |
[Wang X(王雪)]的文章 |
必应学术 |
必应学术中相似的文章 |
[Wang X(王雪)]的文章 |
相关权益政策 |
暂无数据 |
收藏/分享 |
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。
修改评论