Title
Characterization and identification of lysine glutarylation based on intrinsic interdependence between positions in the substrate sites.
Abstract
The SVM model integrating MDD-identified substrate motifs performed well, with a sensitivity of 0.677, a specificity of 0.619, an accuracy of 0.638, and a Matthews Correlation Coefficient (MCC) value of 0.28. Using an independent testing dataset (46 glutarylated and 92 non-glutarylated sites) obtained from the literature, we demonstrated that the integrated SVM model could improve the predictive performance effectively, yielding a balanced sensitivity and specificity of 0.652 and 0.739, respectively. This integrated SVM model has been implemented as a web-based system (MDDGlutar), which is now freely available at http://csb.cse.yzu.edu.tw/MDDGlutar/ .
Year
DOI
Venue
2019
10.1186/s12859-018-2394-9
BMC Bioinformatics
Keywords
Field
DocType
Intrinsic interdependence,Maximal dependence decomposition,Protein glutarylation
Substrate (chemistry),Residue (complex analysis),Biology,Amino acid composition,Molecule,Biochemistry,Lysine,Genetics,DNA microarray
Journal
Volume
Issue
ISSN
19
13
1471-2105
Citations 
PageRank 
References 
0
0.34
19
Authors
5
Name
Order
Citations
PageRank
Kai-Yao Huang11157.91
Hui-Ju Kao2534.59
Justin Bo-Kai Hsu31086.69
Shun-Long Weng4303.72
Tzong-Yi Lee561737.18