Abstract
Phosphorylation is one of the most essential post-translational modifications (PTMs) of proteins, regulates a variety of cellular signaling pathways, and at least partially determines the biological diversity. Recent progresses in phosphoproteomics have identified more than 100,000 phosphorylation sites, while this number will easily exceed one million in the next decade. In this regard, how to extract useful information from flood of phosphoproteomics data has emerged as a great challenge. In this review, we summarized the leading edges on computational analysis of phosphoproteomics, including discovery of phosphorylation motifs from phosphoproteomics data, systematic modeling of phosphorylation network, analysis of genetic variation that influences phosphorylation, and phosphorylation evolution. Based on existed knowledge, we also raised several perspectives for further studies. We believe that integration of experimental and computational analyses will propel the phosphoproteomics research into a new phase.
Keywords: Post-translational modification, phosphorylation, phosphorylation motif, phosphorylation network, phosGV, phosphorylation evolution, PTMs, PKs, HTP-MS, BRCT
Current Protein & Peptide Science
Title: Computational Analysis of Phosphoproteomics: Progresses and Perspectives
Volume: 12 Issue: 7
Author(s): Jian Ren, Xinjiao Gao, Zexian Liu, Jun Cao, Qian Ma and Yu Xue
Affiliation:
Keywords: Post-translational modification, phosphorylation, phosphorylation motif, phosphorylation network, phosGV, phosphorylation evolution, PTMs, PKs, HTP-MS, BRCT
Abstract: Phosphorylation is one of the most essential post-translational modifications (PTMs) of proteins, regulates a variety of cellular signaling pathways, and at least partially determines the biological diversity. Recent progresses in phosphoproteomics have identified more than 100,000 phosphorylation sites, while this number will easily exceed one million in the next decade. In this regard, how to extract useful information from flood of phosphoproteomics data has emerged as a great challenge. In this review, we summarized the leading edges on computational analysis of phosphoproteomics, including discovery of phosphorylation motifs from phosphoproteomics data, systematic modeling of phosphorylation network, analysis of genetic variation that influences phosphorylation, and phosphorylation evolution. Based on existed knowledge, we also raised several perspectives for further studies. We believe that integration of experimental and computational analyses will propel the phosphoproteomics research into a new phase.
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Cite this article as:
Ren Jian, Gao Xinjiao, Liu Zexian, Cao Jun, Ma Qian and Xue Yu, Computational Analysis of Phosphoproteomics: Progresses and Perspectives, Current Protein & Peptide Science 2011; 12(7) . https://dx.doi.org/10.2174/1389203711109070591
DOI https://dx.doi.org/10.2174/1389203711109070591 |
Print ISSN 1389-2037 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5550 |

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