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Towards a Hierarchical Strategy to Explore Multi-Scale IP/MS Data for Protein Complexes

Protein interaction in cells can be described at different levels. At a low interaction level, proteins function together in small, stable complexes and at a higher level, in sets of interacting complexes. All interaction levels are crucial for the living organism, and one of the challenges in prote...

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Detalles Bibliográficos
Autores principales: Kutzera, Joachim, Smilde, Age K., Wilderjans, Tom F., Hoefsloot, Huub C. J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4598013/
https://www.ncbi.nlm.nih.gov/pubmed/26448546
http://dx.doi.org/10.1371/journal.pone.0139704
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author Kutzera, Joachim
Smilde, Age K.
Wilderjans, Tom F.
Hoefsloot, Huub C. J.
author_facet Kutzera, Joachim
Smilde, Age K.
Wilderjans, Tom F.
Hoefsloot, Huub C. J.
author_sort Kutzera, Joachim
collection PubMed
description Protein interaction in cells can be described at different levels. At a low interaction level, proteins function together in small, stable complexes and at a higher level, in sets of interacting complexes. All interaction levels are crucial for the living organism, and one of the challenges in proteomics is to measure the proteins at their different interaction levels. One common method for such measurements is immunoprecipitation followed by mass spectrometry (IP/MS), which has the potential to probe the different protein interaction forms. However, IP/MS data are complex because proteins, in their diverse interaction forms, manifest themselves in different ways in the data. Numerous bioinformatic tools for finding protein complexes in IP/MS data are currently available, but most tools do not provide information about the interaction level of the discovered complexes, and no tool is geared specifically to unraveling and visualizing these different levels. We present a new bioinformatic tool to explore IP/MS datasets for protein complexes at different interaction levels and show its performance on several real–life datasets. Our tool creates clusters that represent protein complexes, but unlike previous methods, it arranges them in a tree–shaped structure, reporting why specific proteins are predicted to build a complex and where it can be divided into smaller complexes. In every data analysis method, parameters have to be chosen. Our method can suggest values for its parameters and comes with adapted visualization tools that display the effect of the parameters on the result. The tools provide fast graphical feedback and allow the user to interact with the data by changing the parameters and examining the result. The tools also allow for exploring the different organizational levels of the protein complexes in a given dataset. Our method is available as GNU-R source code and includes examples at www.bdagroup.nl.
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spelling pubmed-45980132015-10-20 Towards a Hierarchical Strategy to Explore Multi-Scale IP/MS Data for Protein Complexes Kutzera, Joachim Smilde, Age K. Wilderjans, Tom F. Hoefsloot, Huub C. J. PLoS One Research Article Protein interaction in cells can be described at different levels. At a low interaction level, proteins function together in small, stable complexes and at a higher level, in sets of interacting complexes. All interaction levels are crucial for the living organism, and one of the challenges in proteomics is to measure the proteins at their different interaction levels. One common method for such measurements is immunoprecipitation followed by mass spectrometry (IP/MS), which has the potential to probe the different protein interaction forms. However, IP/MS data are complex because proteins, in their diverse interaction forms, manifest themselves in different ways in the data. Numerous bioinformatic tools for finding protein complexes in IP/MS data are currently available, but most tools do not provide information about the interaction level of the discovered complexes, and no tool is geared specifically to unraveling and visualizing these different levels. We present a new bioinformatic tool to explore IP/MS datasets for protein complexes at different interaction levels and show its performance on several real–life datasets. Our tool creates clusters that represent protein complexes, but unlike previous methods, it arranges them in a tree–shaped structure, reporting why specific proteins are predicted to build a complex and where it can be divided into smaller complexes. In every data analysis method, parameters have to be chosen. Our method can suggest values for its parameters and comes with adapted visualization tools that display the effect of the parameters on the result. The tools provide fast graphical feedback and allow the user to interact with the data by changing the parameters and examining the result. The tools also allow for exploring the different organizational levels of the protein complexes in a given dataset. Our method is available as GNU-R source code and includes examples at www.bdagroup.nl. Public Library of Science 2015-10-08 /pmc/articles/PMC4598013/ /pubmed/26448546 http://dx.doi.org/10.1371/journal.pone.0139704 Text en © 2015 Kutzera et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Kutzera, Joachim
Smilde, Age K.
Wilderjans, Tom F.
Hoefsloot, Huub C. J.
Towards a Hierarchical Strategy to Explore Multi-Scale IP/MS Data for Protein Complexes
title Towards a Hierarchical Strategy to Explore Multi-Scale IP/MS Data for Protein Complexes
title_full Towards a Hierarchical Strategy to Explore Multi-Scale IP/MS Data for Protein Complexes
title_fullStr Towards a Hierarchical Strategy to Explore Multi-Scale IP/MS Data for Protein Complexes
title_full_unstemmed Towards a Hierarchical Strategy to Explore Multi-Scale IP/MS Data for Protein Complexes
title_short Towards a Hierarchical Strategy to Explore Multi-Scale IP/MS Data for Protein Complexes
title_sort towards a hierarchical strategy to explore multi-scale ip/ms data for protein complexes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4598013/
https://www.ncbi.nlm.nih.gov/pubmed/26448546
http://dx.doi.org/10.1371/journal.pone.0139704
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