ITP OpenIR  > SCI期刊论文
Zhang, HC; Gao, YJ; Deng, MH; Wang, C; Zhu, JW; Li, SC; Zheng, WM; Bu, DB; Bu, DB (reprint author), Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing, Peoples R China.; Zheng, WM (reprint author), Chinese Acad Sci, Inst Theoret Phys, Beijing 100080, Peoples R China.
Improving residue-residue contact prediction via low-rank and sparse decomposition of residue correlation matrix
Source PublicationBIOCHEMICAL AND BIOPHYSICAL RESEARCH COMMUNICATIONS
Language英语
KeywordProtein Contacts Prediction Correlation Analysis Background Correlation Removal Low-rank And Sparse Matrix Decomposition
AbstractStrategies for correlation analysis in protein contact prediction often encounter two challenges, namely, the indirect coupling among residues, and the background correlations mainly caused by phylogenetic biases. While various studies have been conducted on how to disentangle indirect coupling, the removal of background correlations still remains unresolved. Here, we present an approach for removing background correlations via low-rank and sparse decomposition (LRS) of a residue correlation matrix. The correlation matrix can be constructed using either local inference strategies (e.g., mutual information, or MI) or global inference strategies (e.g., direct coupling analysis, or DCA). In our approach, a correlation matrix was decomposed into two components, i.e., a low-rank component representing background correlations, and a sparse component representing true correlations. Finally the residue contacts were inferred from the sparse component of correlation matrix. We trained our LRS-based method on the PSICOV dataset, and tested it on both GREMLIN and CASP11 datasets. Our experimental results suggested that LRS significantly improves the contact prediction precision. For example, when equipped with the LRS technique, the prediction precision of MI and mfDCA increased from 0.25 to 0.67 and from 0.58 to 0.70, respectively (Top L/10 predicted contacts, sequence separation: 5 AA, dataset: GREMLIN). In addition, our LRS technique also consistently outperforms the popular denoising technique APC (average product correction), on both local (MI_LRS: 0.67 vs MI_APC: 0.34) and global measures (mfDCA_LRS: 0.70 vs mfDCA_APC: 0.67). Interestingly, we found out that when equipped with our LRS technique, local inference strategies performed in a comparable manner to that of global inference strategies, implying that the application of LRS technique narrowed down the performance gap between local and global inference strategies. Overall, our LRS technique greatly facilitates protein contact prediction by removing background correlations. An implementation of the approach called COLORS (improving COntact prediction using LOw-Rank and Sparse matrix decomposition) is available from http://proteinictac.cn/COLORS/. (C) 2016 Elsevier Inc. All rights reserved.
2016
Volume472Issue:1Pages:217-222
Subject AreaBiochemistry & Molecular Biology ; Biophysics
DOIhttp://dx.doi.org/10.1016/j.bbrc.2016.01.188
Indexed BySCI
Funding OrganizationNational Basic Research Program of China (973 Program) [2012CB316502, 2015CB910303] ; National Basic Research Program of China (973 Program) [2012CB316502, 2015CB910303] ; National Basic Research Program of China (973 Program) [2012CB316502, 2015CB910303] ; National Basic Research Program of China (973 Program) [2012CB316502, 2015CB910303] ; National Nature Science Foundation of China [11175224, 11121403, 31270834, 61272318, 31171262, 31428012, 31471246] ; National Nature Science Foundation of China [11175224, 11121403, 31270834, 61272318, 31171262, 31428012, 31471246] ; National Nature Science Foundation of China [11175224, 11121403, 31270834, 61272318, 31171262, 31428012, 31471246] ; National Nature Science Foundation of China [11175224, 11121403, 31270834, 61272318, 31171262, 31428012, 31471246] ; Open Project Program of State Key Laboratory of Theoretical Physics [Y4KF171CJ1] ; Open Project Program of State Key Laboratory of Theoretical Physics [Y4KF171CJ1] ; Open Project Program of State Key Laboratory of Theoretical Physics [Y4KF171CJ1] ; Open Project Program of State Key Laboratory of Theoretical Physics [Y4KF171CJ1] ; European Commission [306819] ; European Commission [306819] ; European Commission [306819] ; European Commission [306819]
Citation statistics
Document Type期刊论文
Identifierhttp://ir.itp.ac.cn/handle/311006/21722
CollectionSCI期刊论文
Corresponding AuthorBu, DB (reprint author), Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing, Peoples R China.; Zheng, WM (reprint author), Chinese Acad Sci, Inst Theoret Phys, Beijing 100080, Peoples R China.
Recommended Citation
GB/T 7714
Zhang, HC,Gao, YJ,Deng, MH,et al. Improving residue-residue contact prediction via low-rank and sparse decomposition of residue correlation matrix[J]. BIOCHEMICAL AND BIOPHYSICAL RESEARCH COMMUNICATIONS,2016,472(1):217-222.
APA Zhang, HC.,Gao, YJ.,Deng, MH.,Wang, C.,Zhu, JW.,...&Zheng, WM .(2016).Improving residue-residue contact prediction via low-rank and sparse decomposition of residue correlation matrix.BIOCHEMICAL AND BIOPHYSICAL RESEARCH COMMUNICATIONS,472(1),217-222.
MLA Zhang, HC,et al."Improving residue-residue contact prediction via low-rank and sparse decomposition of residue correlation matrix".BIOCHEMICAL AND BIOPHYSICAL RESEARCH COMMUNICATIONS 472.1(2016):217-222.
Files in This Item:
File Name/Size DocType Version Access License
Improving residue-re(1325KB) 开放获取--Application Full Text
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Zhang, HC]'s Articles
[Gao, YJ]'s Articles
[Deng, MH]'s Articles
Baidu academic
Similar articles in Baidu academic
[Zhang, HC]'s Articles
[Gao, YJ]'s Articles
[Deng, MH]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Zhang, HC]'s Articles
[Gao, YJ]'s Articles
[Deng, MH]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.