Systematic inference of functional phosphorylation events in yeast metabolism
Author(s) -
Yu Chen,
Yonghong Wang,
Jens Nielsen
Publication year - 2017
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btx110
Subject(s) - phosphoproteomics , phosphorylation , protein phosphorylation , computational biology , biology , inference , flux (metallurgy) , saccharomyces cerevisiae , proteomics , biochemistry , flux balance analysis , metabolic pathway , systems biology , enzyme , bioinformatics , yeast , computer science , chemistry , gene , protein kinase a , artificial intelligence , organic chemistry
Protein phosphorylation is a post-translational modification that affects proteins by changing their structure and conformation in a rapid and reversible way, and it is an important mechanism for metabolic regulation in cells. Phosphoproteomics enables high-throughput identification of phosphorylation events on metabolic enzymes, but identifying functional phosphorylation events still requires more detailed biochemical characterization. Therefore, development of computational methods for investigating unknown functions of a large number of phosphorylation events identified by phosphoproteomics has received increased attention.
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