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Protter: interactive protein feature visualization and integration with experimental proteomic data

Omasits, Ulrich; Ahrens, Christian H; Müller, Sebastian; Wollscheid, Bernd (2014). Protter: interactive protein feature visualization and integration with experimental proteomic data. Bioinformatics, 30(6):884-886.

Abstract

Summary: The ability to integrate and visualize experimental proteomic evidence in the context of rich protein feature annotations represents an unmet need of the proteomics community. Here we present Protter, a web-based tool that supports interactive protein data analysis and hypothesis generation by visualizing both annotated sequence features and experimental proteomic data in the context of protein topology. Protter supports numerous proteomic file formats and automatically integrates a variety of reference protein annotation sources, which can be readily extended via modular plug-ins. A built-in export function produces publication-quality customized protein illustrations, also for large datasets. Visualizations of surfaceome datasets show the specific utility of Protter for the integrated visual analysis of membrane proteins and peptide selection for targeted proteomics. Availability and implementation:The Protter web application is available at http://wlab.ethz.ch/protter. Source code and installation instructions are available at http://ulo.github.io/Protter/. Contact: wbernd@ethz.ch Supplementary Information: Supplementary data are available at Bioinformatics online

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:National licences > 142-005
Dewey Decimal Classification:Unspecified
Scopus Subject Areas:Physical Sciences > Statistics and Probability
Life Sciences > Biochemistry
Life Sciences > Molecular Biology
Physical Sciences > Computer Science Applications
Physical Sciences > Computational Theory and Mathematics
Physical Sciences > Computational Mathematics
Language:English
Date:15 March 2014
Deposited On:31 Oct 2018 16:20
Last Modified:18 Mar 2025 02:41
Publisher:Oxford University Press
ISSN:1367-4803
OA Status:Hybrid
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1093/bioinformatics/btt607
PubMed ID:24162465
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  • Content: Published Version
  • Language: English
  • Description: Nationallizenz 142-005

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