Similarity Analysis based on Sparse Representation for Protein Sequence Comparison
Lina Yang1,2; Yuan Yan Tang1; Yulong Wang1; Huiwu Luo1; Jianjia Pan1; Haoliang Yuan1; Xianwei Zheng1; Chunli Li1; Ting Shu1
Conference Name2015 IEEE 2nd International Conference on Cybernetics (CYBCONF)
Source PublicationProceedings - 2015 IEEE 2nd International Conference on Cybernetics, CYBCONF 2015
Conference Date24-26 June 2015
Conference PlaceGdynia, Poland

This paper propose a least square-based sparse representation algorithm to analyze similarity comparison of protein sequences in the area of bioinformatics and molecular biology, which helps the prediction and classification of protein structure and function. The protein sequences are represented into the 1-dimensional feature vectors by their biochemical quantities. Then using the least square method to form the feature vector. Through the similarity calculation, the distance matrix can be obtained, by which, the phylogenic tree can be constructed.We apply this approach by analyzing the ND5 (NADH dehydrogenase subunit 5) protein cluster dataset. The experimental results show that the proposed model is more accurate than the Su's model,and it is closer with some known biological facts.

KeywordFeature Extraction L1-regularized Least Squares Protein Sequence Analysis Sparse Representation
URLView the original
Indexed BySCI
WOS Research AreaComputer Science
WOS SubjectComputer Science, Cybernetics
WOS IDWOS:000373207200067
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Cited Times [WOS]:1   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
CollectionUniversity of Macau
Affiliation1.Department of Computer and Information Science, University of Macau, Macau, China
2.Guangxi Normal University for Nationalities, Chongzuo, China
First Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Lina Yang,Yuan Yan Tang,Yulong Wang,et al. Similarity Analysis based on Sparse Representation for Protein Sequence Comparison[C]:IEEE,2015:382-387.
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