RF-GlutarySite: a random forest based predictor for glutarylation sites
Author:
Affiliation:
1. Department of Computational Science and Engineering
2. North Carolina Agricultural & Technical State University
3. Greensboro
4. USA
5. Department of Informatics
6. Kyushu University
7. Fukuoka 819-0395
8. Japan
9. Department of Biology
Abstract
Glutarylation, which is a newly identified posttranslational modification that occurs on lysine residues, has recently emerged as an important regulator of several metabolic and mitochondrial processes. Here, we describe the development of RF-GlutarySite, a random forest-based predictor designed to predict glutarylation sites based on protein primary amino acid sequence.
Funder
National Science Foundation
National Institutes of Health
Japan Society for the Promotion of Science
Publisher
Royal Society of Chemistry (RSC)
Subject
Genetics,Molecular Biology,Biochemistry
Link
http://pubs.rsc.org/en/content/articlepdf/2019/MO/C9MO00028C
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