Computational systems approach towards phosphoproteomics and their downstream regulation

被引:6
|
作者
Xiao, Di [1 ,2 ]
Chen, Carissa [1 ,2 ]
Yang, Pengyi [1 ,2 ,3 ]
机构
[1] Univ Sydney, Childrens Med Res Inst, Computat Syst Biol Grp, Westmead, NSW 2145, Australia
[2] Univ Sydney, Charles Perkins Ctr, Sydney, NSW, Australia
[3] Univ Sydney, Sch Math & Stat, Sydney, NSW, Australia
基金
英国医学研究理事会;
关键词
bioinformatics; cell biology; data processing and analysis; phosphoproteomics; signal transduction; systems biology; technology; PROTEIN-KINASE; POSTTRANSLATIONAL MODIFICATION; INTERACTION NETWORK; SIGNALING PATHWAYS; IN-VIVO; PHOSPHORYLATION; PREDICTION; SPECIFICITY; REVEALS; IDENTIFICATION;
D O I
10.1002/pmic.202200068
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Protein phosphorylation plays an essential role in modulating cell signalling and its downstream transcriptional and translational regulations. Until recently, protein phosphorylation has been studied mostly using low-throughput biochemical assays. The advancement of mass spectrometry (MS)-based phosphoproteomics transformed the field by enabling measurement of proteome-wide phosphorylation events, where tens of thousands of phosphosites are routinely identified and quantified in an experiment. This has brought a significant challenge in analysing large-scale phosphoproteomic data, making computational methods and systems approaches integral parts of phosphoproteomics. Previous works have primarily focused on reviewing the experimental techniques in MS-based phosphoproteomics, yet a systematic survey of the computational landscape in this field is still missing. Here, we review computational methods and tools, and systems approaches that have been developed for phosphoproteomics data analysis. We categorise them into four aspects including data processing, functional analysis, phosphoproteome annotation and their integration with other omics, and in each aspect, we discuss the key methods and example studies. Lastly, we highlight some of the potential research directions on which future work would make a significant contribution to this fast-growing field. We hope this review provides a useful snapshot of the field of computational systems phosphoproteomics and stimulates new research that drives future development.
引用
收藏
页数:13
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