From Phosphosites to Kinases

Publikation: Bidrag til bog/antologi/rapportBidrag til bog/antologiForskningfagfællebedømt

Standard

From Phosphosites to Kinases. / Munk, Stephanie; Refsgaard, Jan C; Olsen, Jesper V; Jensen, Lars J.

Phospho-Proteomics: Methods and Protocols. red. / Louise von Stechow. Bind 1355 Springer, 2016. s. 307-21.

Publikation: Bidrag til bog/antologi/rapportBidrag til bog/antologiForskningfagfællebedømt

Harvard

Munk, S, Refsgaard, JC, Olsen, JV & Jensen, LJ 2016, From Phosphosites to Kinases. i LV Stechow (red.), Phospho-Proteomics: Methods and Protocols. bind 1355, Springer, Methods in molecular biology (Clifton, N.J.), s. 307-21. https://doi.org/10.1007/978-1-4939-3049-4_21

APA

Munk, S., Refsgaard, J. C., Olsen, J. V., & Jensen, L. J. (2016). From Phosphosites to Kinases. I L. V. Stechow (red.), Phospho-Proteomics: Methods and Protocols (Bind 1355, s. 307-21). Springer. Methods in molecular biology (Clifton, N.J.) https://doi.org/10.1007/978-1-4939-3049-4_21

Vancouver

Munk S, Refsgaard JC, Olsen JV, Jensen LJ. From Phosphosites to Kinases. I Stechow LV, red., Phospho-Proteomics: Methods and Protocols. Bind 1355. Springer. 2016. s. 307-21. (Methods in molecular biology (Clifton, N.J.)). https://doi.org/10.1007/978-1-4939-3049-4_21

Author

Munk, Stephanie ; Refsgaard, Jan C ; Olsen, Jesper V ; Jensen, Lars J. / From Phosphosites to Kinases. Phospho-Proteomics: Methods and Protocols. red. / Louise von Stechow. Bind 1355 Springer, 2016. s. 307-21 (Methods in molecular biology (Clifton, N.J.)).

Bibtex

@inbook{d994a1f8d14945e49055ab519c566829,
title = "From Phosphosites to Kinases",
abstract = "Kinases play a pivotal role in propagating the phosphorylation-mediated signaling networks in living cells. With the overwhelming quantities of phosphoproteomics data being generated, the number of identified phosphorylation sites (phosphosites) is ever increasing. Often, proteomics investigations aim to understand the global signaling modulation that takes place in different biological conditions investigated. For phosphoproteomics data, identifying the kinases central to mediating this response is key. This has prompted several efforts to catalogue the immense amounts of phosphorylation data and known or predicted kinases responsible for the modifications. However, barely 20 {\%} of the known phosphosites are assigned to a kinase, initiating various bioinformatics efforts that attempt to predict the responsible kinases. These algorithms employ different approaches to predict kinase consensus sequence motifs, mostly based on large scale in vivo and in vitro experiments. The context of the kinase and the phosphorylated proteins in a biological system is equally important for predicting association between the enzymes and substrates, an aspect that is also being tackled with available bioinformatics tools. This chapter summarizes the use of the larger phosphorylation databases, and approaches that can be applied to predict kinases that phosphorylate individual sites or that are globally modulated in phosphoproteomics datasets.",
author = "Stephanie Munk and Refsgaard, {Jan C} and Olsen, {Jesper V} and Jensen, {Lars J}",
year = "2016",
doi = "10.1007/978-1-4939-3049-4_21",
language = "English",
isbn = "978-1-4939-3048-7",
volume = "1355",
pages = "307--21",
editor = "Stechow, {Louise von}",
booktitle = "Phospho-Proteomics",
publisher = "Springer",

}

RIS

TY - CHAP

T1 - From Phosphosites to Kinases

AU - Munk, Stephanie

AU - Refsgaard, Jan C

AU - Olsen, Jesper V

AU - Jensen, Lars J

PY - 2016

Y1 - 2016

N2 - Kinases play a pivotal role in propagating the phosphorylation-mediated signaling networks in living cells. With the overwhelming quantities of phosphoproteomics data being generated, the number of identified phosphorylation sites (phosphosites) is ever increasing. Often, proteomics investigations aim to understand the global signaling modulation that takes place in different biological conditions investigated. For phosphoproteomics data, identifying the kinases central to mediating this response is key. This has prompted several efforts to catalogue the immense amounts of phosphorylation data and known or predicted kinases responsible for the modifications. However, barely 20 % of the known phosphosites are assigned to a kinase, initiating various bioinformatics efforts that attempt to predict the responsible kinases. These algorithms employ different approaches to predict kinase consensus sequence motifs, mostly based on large scale in vivo and in vitro experiments. The context of the kinase and the phosphorylated proteins in a biological system is equally important for predicting association between the enzymes and substrates, an aspect that is also being tackled with available bioinformatics tools. This chapter summarizes the use of the larger phosphorylation databases, and approaches that can be applied to predict kinases that phosphorylate individual sites or that are globally modulated in phosphoproteomics datasets.

AB - Kinases play a pivotal role in propagating the phosphorylation-mediated signaling networks in living cells. With the overwhelming quantities of phosphoproteomics data being generated, the number of identified phosphorylation sites (phosphosites) is ever increasing. Often, proteomics investigations aim to understand the global signaling modulation that takes place in different biological conditions investigated. For phosphoproteomics data, identifying the kinases central to mediating this response is key. This has prompted several efforts to catalogue the immense amounts of phosphorylation data and known or predicted kinases responsible for the modifications. However, barely 20 % of the known phosphosites are assigned to a kinase, initiating various bioinformatics efforts that attempt to predict the responsible kinases. These algorithms employ different approaches to predict kinase consensus sequence motifs, mostly based on large scale in vivo and in vitro experiments. The context of the kinase and the phosphorylated proteins in a biological system is equally important for predicting association between the enzymes and substrates, an aspect that is also being tackled with available bioinformatics tools. This chapter summarizes the use of the larger phosphorylation databases, and approaches that can be applied to predict kinases that phosphorylate individual sites or that are globally modulated in phosphoproteomics datasets.

U2 - 10.1007/978-1-4939-3049-4_21

DO - 10.1007/978-1-4939-3049-4_21

M3 - Book chapter

SN - 978-1-4939-3048-7

VL - 1355

SP - 307

EP - 321

BT - Phospho-Proteomics

A2 - Stechow, Louise von

PB - Springer

ER -

ID: 179330041