Improved Species-Specific Lysine Acetylation Site Prediction Based on a Large Variety of Features Set
Publication Date
May 16, 2016
Journal
PLOS ONE
Authors
Qiqige Wuyun, Wei Zheng, Yanping Zhang, Jishou Ruan, et al
Volume
11
Issue
5
Pages
e0155370
DOI
https://dx.plos.org/10.1371/journal.pone.0155370
Publisher URL
http://journals.plos.org/plosone/article?id=10.1371%2Fjournal.pone.0155370
Scopus
84969642561
Mendeley
http://www.mendeley.com/research/improved-speciesspecific-lysine-acetylation-site-prediction-based-large-variety-features-set
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Mendeley | Further Information

{"title"=>"Improved species-specific lysine acetylation site prediction based on a large variety of features set", "type"=>"journal", "authors"=>[{"first_name"=>"Qiqige", "last_name"=>"Wuyun", "scopus_author_id"=>"55320693500"}, {"first_name"=>"Wei", "last_name"=>"Zheng", "scopus_author_id"=>"56857031300"}, {"first_name"=>"Yanping", "last_name"=>"Zhang", "scopus_author_id"=>"55934269200"}, {"first_name"=>"Jishou", "last_name"=>"Ruan", "scopus_author_id"=>"56023743300"}, {"first_name"=>"Gang", "last_name"=>"Hu", "scopus_author_id"=>"55903159300"}], "year"=>2016, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "pui"=>"610397714", "doi"=>"10.1371/journal.pone.0155370", "sgr"=>"84969642561", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)", "pmid"=>"27183223", "scopus"=>"2-s2.0-84969642561"}, "id"=>"d483ce55-d15e-32c8-a474-853a04013e75", "abstract"=>"Lysine acetylation is a major post-translational modification. It plays a vital role in numerous essential biological processes, such as gene expression and metabolism, and is related to some human diseases. To fully understand the regulatory mechanism of acetylation, identification of acetylation sites is first and most important. However, experimental identification of protein acetylation sites is often time consuming and expensive. Therefore, the alternative computational methods are necessary. Here, we developed a novel tool, KA-predictor, to predict species-specific lysine acetylation sites based on support vector machine (SVM) classifier. We incorporated different types of features and employed an efficient feature selection on each type to form the final optimal feature set for model learning. And our predictor was highly competitive for the majority of species when compared with other methods. Feature contribution analysis indicated that HSE features, which were firstly introduced for lysine acetylation prediction, significantly improved the predictive performance. Particularly, we constructed a high-accurate structure dataset of H.sapiens from PDB to analyze the structural properties around lysine acetylation sites. Our datasets and a user-friendly local tool of KA-predictor can be freely available at http://sourceforge.net/p/ka-predictor.", "link"=>"http://www.mendeley.com/research/improved-speciesspecific-lysine-acetylation-site-prediction-based-large-variety-features-set", "reader_count"=>6, "reader_count_by_academic_status"=>{"Researcher"=>4, "Student > Ph. D. Student"=>1, "Student > Master"=>1}, "reader_count_by_user_role"=>{"Researcher"=>4, "Student > Ph. D. Student"=>1, "Student > Master"=>1}, "reader_count_by_subject_area"=>{"Biochemistry, Genetics and Molecular Biology"=>1, "Agricultural and Biological Sciences"=>2, "Medicine and Dentistry"=>1, "Computer Science"=>2}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>2}, "Computer Science"=>{"Computer Science"=>2}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}}, "group_count"=>0}

Scopus | Further Information

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