Systems Analysis for Interpretation of Phosphoproteomics Data

Research output: Chapter in Book/Report/Conference proceedingBook chapterResearchpeer-review

Standard

Systems Analysis for Interpretation of Phosphoproteomics Data. / Munk, Stephanie; Refsgaard, Jan C; Olsen, Jesper V.

Phospho-Proteomics: Methods and Protocols. ed. / Louise von Stechow. Vol. 1355 Springer, 2016. p. 341-60 (Methods in molecular biology (Clifton, N.J.)).

Research output: Chapter in Book/Report/Conference proceedingBook chapterResearchpeer-review

Harvard

Munk, S, Refsgaard, JC & Olsen, JV 2016, Systems Analysis for Interpretation of Phosphoproteomics Data. in LV Stechow (ed.), Phospho-Proteomics: Methods and Protocols. vol. 1355, Springer, Methods in molecular biology (Clifton, N.J.), pp. 341-60. https://doi.org/10.1007/978-1-4939-3049-4_23

APA

Munk, S., Refsgaard, J. C., & Olsen, J. V. (2016). Systems Analysis for Interpretation of Phosphoproteomics Data. In L. V. Stechow (Ed.), Phospho-Proteomics: Methods and Protocols (Vol. 1355, pp. 341-60). Springer. Methods in molecular biology (Clifton, N.J.) https://doi.org/10.1007/978-1-4939-3049-4_23

Vancouver

Munk S, Refsgaard JC, Olsen JV. Systems Analysis for Interpretation of Phosphoproteomics Data. In Stechow LV, editor, Phospho-Proteomics: Methods and Protocols. Vol. 1355. Springer. 2016. p. 341-60. (Methods in molecular biology (Clifton, N.J.)). https://doi.org/10.1007/978-1-4939-3049-4_23

Author

Munk, Stephanie ; Refsgaard, Jan C ; Olsen, Jesper V. / Systems Analysis for Interpretation of Phosphoproteomics Data. Phospho-Proteomics: Methods and Protocols. editor / Louise von Stechow. Vol. 1355 Springer, 2016. pp. 341-60 (Methods in molecular biology (Clifton, N.J.)).

Bibtex

@inbook{edf5bf56f68b4f0ead93f9933635cebb,
title = "Systems Analysis for Interpretation of Phosphoproteomics Data",
abstract = "Global phosphoproteomics investigations yield overwhelming datasets with up to tens of thousands of quantified phosphosites. The main challenge after acquiring such large-scale data is to extract the biological meaning and relate this to the experimental question at hand. Systems level analysis provides the best means for extracting functional insights from such types of datasets, and this has primed a rapid development of bioinformatics tools and resources over the last decade. Many of these tools are specialized databases that can be mined for annotation and pathway enrichment, whereas others provide a platform to generate functional protein networks and explore the relations between proteins of interest. The use of these tools requires careful consideration with regard to the input data, and the interpretation demands a critical approach. This chapter provides a summary of the most appropriate tools for systems analysis of phosphoproteomics datasets, and the considerations that are critical for acquiring meaningful output.",
author = "Stephanie Munk and Refsgaard, {Jan C} and Olsen, {Jesper V}",
year = "2016",
doi = "10.1007/978-1-4939-3049-4_23",
language = "English",
isbn = "978-1-4939-3048-7",
volume = "1355",
series = "Methods in molecular biology (Clifton, N.J.)",
publisher = "Springer",
pages = "341--60",
editor = "Stechow, {Louise von}",
booktitle = "Phospho-Proteomics",
address = "Switzerland",

}

RIS

TY - CHAP

T1 - Systems Analysis for Interpretation of Phosphoproteomics Data

AU - Munk, Stephanie

AU - Refsgaard, Jan C

AU - Olsen, Jesper V

PY - 2016

Y1 - 2016

N2 - Global phosphoproteomics investigations yield overwhelming datasets with up to tens of thousands of quantified phosphosites. The main challenge after acquiring such large-scale data is to extract the biological meaning and relate this to the experimental question at hand. Systems level analysis provides the best means for extracting functional insights from such types of datasets, and this has primed a rapid development of bioinformatics tools and resources over the last decade. Many of these tools are specialized databases that can be mined for annotation and pathway enrichment, whereas others provide a platform to generate functional protein networks and explore the relations between proteins of interest. The use of these tools requires careful consideration with regard to the input data, and the interpretation demands a critical approach. This chapter provides a summary of the most appropriate tools for systems analysis of phosphoproteomics datasets, and the considerations that are critical for acquiring meaningful output.

AB - Global phosphoproteomics investigations yield overwhelming datasets with up to tens of thousands of quantified phosphosites. The main challenge after acquiring such large-scale data is to extract the biological meaning and relate this to the experimental question at hand. Systems level analysis provides the best means for extracting functional insights from such types of datasets, and this has primed a rapid development of bioinformatics tools and resources over the last decade. Many of these tools are specialized databases that can be mined for annotation and pathway enrichment, whereas others provide a platform to generate functional protein networks and explore the relations between proteins of interest. The use of these tools requires careful consideration with regard to the input data, and the interpretation demands a critical approach. This chapter provides a summary of the most appropriate tools for systems analysis of phosphoproteomics datasets, and the considerations that are critical for acquiring meaningful output.

U2 - 10.1007/978-1-4939-3049-4_23

DO - 10.1007/978-1-4939-3049-4_23

M3 - Book chapter

C2 - 26584937

SN - 978-1-4939-3048-7

VL - 1355

T3 - Methods in molecular biology (Clifton, N.J.)

SP - 341

EP - 360

BT - Phospho-Proteomics

A2 - Stechow, Louise von

PB - Springer

ER -

ID: 179330130