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An Intelligent System for Identifying Acetylated Lysine on Histones and Nonhistone Proteins
Joint Authors
Chen, Yu-Ju
Lu, Cheng-Tsung
Lee, Tzong-Yi
Chen, Yi-Ju
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-07-23
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Lysine acetylation is an important and ubiquitous posttranslational modification conserved in prokaryotes and eukaryotes.
This process, which is dynamically and temporally regulated by histone acetyltransferases and deacetylases, is crucial for numerous essential biological processes such as transcriptional regulation, cellular signaling, and stress response.
Since the experimental identification of lysine acetylation sites within proteins is time-consuming and laboratory-intensive, several computational approaches have been developed to identify candidates for experimental validation.
In this work, acetylated protein data collected from UniProtKB were categorized into histone or nonhistone proteins.
Support vector machines (SVMs) were applied to build predictive models by using amino acid pair composition (AAPC) as a feature in a histone model.
We combined BLOSUM62 and AAPC features in a nonhistone model.
Furthermore, using maximal dependence decomposition (MDD) clustering can enhance the performance of the model on a fivefold cross-validation evaluation to yield a sensitivity of 0.863, specificity of 0.885, accuracy of 0.880, and MCC of 0.706.
Additionally, the proposed method is evaluated using independent test sets resulting in a predictive accuracy of 74%.
This indicates that the performance of our method is comparable with that of other acetylation prediction methods.
American Psychological Association (APA)
Lu, Cheng-Tsung& Lee, Tzong-Yi& Chen, Yu-Ju& Chen, Yi-Ju. 2014. An Intelligent System for Identifying Acetylated Lysine on Histones and Nonhistone Proteins. BioMed Research International،Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-478922
Modern Language Association (MLA)
Lu, Cheng-Tsung…[et al.]. An Intelligent System for Identifying Acetylated Lysine on Histones and Nonhistone Proteins. BioMed Research International No. 2014 (2014), pp.1-11.
https://search.emarefa.net/detail/BIM-478922
American Medical Association (AMA)
Lu, Cheng-Tsung& Lee, Tzong-Yi& Chen, Yu-Ju& Chen, Yi-Ju. An Intelligent System for Identifying Acetylated Lysine on Histones and Nonhistone Proteins. BioMed Research International. 2014. Vol. 2014, no. 2014, pp.1-11.
https://search.emarefa.net/detail/BIM-478922
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-478922