Prediction and functional analysis of prokaryote lysine acetylation site by incorporating six types of features into Chou's general PseAAC
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Publication:1716885
DOI10.1016/j.jtbi.2018.10.047zbMath1406.92172OpenAlexW2896899595WikidataQ58575878 ScholiaQ58575878MaRDI QIDQ1716885
Jialin Yu, Guodong Chen, Xinyun Guo, Man Cao, Shao-Ping Shi
Publication date: 5 February 2019
Published in: Journal of Theoretical Biology (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jtbi.2018.10.047
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- Predicting protein submitochondrial locations by incorporating the pseudo-position specific scoring matrix into the general Chou's pseudo-amino acid composition
- IMem-2LSAAC: a two-level model for discrimination of membrane proteins and their types by extending the notion of SAAC into Chou's pseudo amino acid composition
- Some remarks on protein attribute prediction and pseudo amino acid composition
- iMethyl-STTNC: identification of N\(^6\)-methyladenosine sites by extending the idea of SAAC into Chou's PseAAC to formulate RNA sequences
- Lysine acetylation sites prediction using an ensemble of support vector machine classifiers
- A generalization of the Hermitian and skew-Hermitian splitting iteration method for solving Sylvester equations
- Achieving higher order of convergence for solving systems of nonlinear equations
- Regularization and Variable Selection Via the Elastic Net
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