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Combining sequence and Gene Ontology for protein module detection in the Weighted Network
Yu, Yang; Liu, Jie; Feng, Nuan; Song, Bo; Zheng ZY(郑泽宇)
Department数字工厂研究室
Source PublicationJOURNAL OF THEORETICAL BIOLOGY
ISSN0022-5193
2017
Volume412Pages:107-112
Indexed BySCI
WOS IDWOS:000391081500012
Contribution Rank1
Funding OrganizationScience Research Project of Liaoning Province Education Department [L2015496, L201605] ; One-hundred Talent Program of the Chinese Academy of Sciences [Y5AA100A01]
KeywordProtein Complex Protein Interaction Gene Ontology The Weighted Network
AbstractStudies of protein modules in a Protein-Protein Interaction (PPI) network contribute greatly to the understanding of biological mechanisms. With the development of computing science, computational approaches have played an important role in locating protein modules. In this paper, a new approach combining Gene Ontology and amino acid background frequency is introduced to detect the protein modules in the weighted PPI networks. The proposed approach mainly consists of three parts: the feature extraction, the weighted graph construction and the protein complex detection. Firstly, the topology-sequence information is utilized to present the feature of protein complex. Secondly, six types of the weighed graph are constructed by combining PPI network and Gene Ontology information. Lastly, protein complex algorithm is applied to the weighted graph, which locates the clusters based on three conditions, including density, network diameter and the included angle cosine. Experiments have been conducted on two protein complex benchmark sets for yeast and the results show that the approach is more effective compared to five typical algorithms with the performance of f-measure and precision. The combination of protein interaction network with sequence and gene ontology data is helpful to improve the performance and provide a optional method for protein module detection.
Language英语
WOS HeadingsScience & Technology ; Life Sciences & Biomedicine
WOS SubjectBiology ; Mathematical & Computational Biology
WOS KeywordSEMANTIC SIMILARITY ; COMPLEXES ; INFORMATION ; ALGORITHM ; MODULARITY ; CASCADE ; CANCER ; TERMS ; YEAST
WOS Research AreaLife Sciences & Biomedicine - Other Topics ; Mathematical & Computational Biology
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/19823
Collection数字工厂研究室
Corresponding AuthorYu, Yang; Feng, Nuan
Affiliation1.Software College, Shenyang Normal University, Shenyang 110034, PR China
2.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, PR China
3.College of Information Technology, Shenyang Institute of Technology, Fushun 113122, PR China
Recommended Citation
GB/T 7714
Yu, Yang,Liu, Jie,Feng, Nuan,et al. Combining sequence and Gene Ontology for protein module detection in the Weighted Network[J]. JOURNAL OF THEORETICAL BIOLOGY,2017,412:107-112.
APA Yu, Yang,Liu, Jie,Feng, Nuan,Song, Bo,&Zheng ZY.(2017).Combining sequence and Gene Ontology for protein module detection in the Weighted Network.JOURNAL OF THEORETICAL BIOLOGY,412,107-112.
MLA Yu, Yang,et al."Combining sequence and Gene Ontology for protein module detection in the Weighted Network".JOURNAL OF THEORETICAL BIOLOGY 412(2017):107-112.
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