Escher: A Web Application for Building, Sharing, and Embedding Data-Rich Visualizations of Biological Pathways
Abstract
Escher is a web application for visualizing data on biological pathways. Three key features make Escher a uniquely effective tool for pathway visualization. First, users can rapidly design new pathway maps. Escher provides pathway suggestions based on user data and genome-scale models, so users can draw pathways in a semi-automated way. Second, users can visualize data related to genes or proteins on the associated reactions and pathways, using rules that define which enzymes catalyze each reaction. Thus, users can identify trends in common genomic data types (e.g. RNA-Seq, proteomics, ChIP)—in conjunction with metabolite- and reaction-oriented data types (e.g. metabolomics, fluxomics). Third, Escher harnesses the strengths of web technologies (SVG, D3, developer tools) so that visualizations can be rapidly adapted, extended, shared, and embedded. This paper provides examples of each of these features and explains how the development approach used for Escher can be used to guide the development of future visualization tools.
- Authors:
-
- Univ. of California, San Diego, CA (United States). Dept. of Bioengineering
- Univ. of California, San Diego, CA (United States). Dept. of Bioengineering; Univ. of Tübingen (Germany). Center for Bioinformatics Tübingen (ZBIT)
- Technical Univ. of Denmark, Lyngby (Denmark). Novo Nordisk Foundation Center for Biosustainability
- Univ. of California, San Diego, CA (United States). Dept. of Pediatrics
- Univ. of California, San Diego, CA (United States). Dept. of Bioengineering. Dept. of Pediatrics
- Publication Date:
- Research Org.:
- Univ. of California, San Diego, CA (United States); Univ. of Tubingen (Germany); Technical Univ. of Denmark, Lyngby (Denmark)
- Sponsoring Org.:
- USDOE Office of Science (SC), Biological and Environmental Research (BER); National Science Foundation (NSF); National Inst. of Health (NIH) (United States); European Commission (EC); Novo Nordisk Foundation (Denmark)
- OSTI Identifier:
- 1455068
- Grant/Contract Number:
- SC0008701; DGE-1144086; R21 HD080682; 332020; NNF 132150-002
- Resource Type:
- Accepted Manuscript
- Journal Name:
- PLoS Computational Biology (Online)
- Additional Journal Information:
- Journal Name: PLoS Computational Biology (Online); Journal Volume: 11; Journal Issue: 8; Journal ID: ISSN 1553-7358
- Publisher:
- Public Library of Science
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 59 BASIC BIOLOGICAL SCIENCES; 97 MATHEMATICS AND COMPUTING; data visualization; metabolites; web-based applications; genome analysis; genomic databases; gene mapping; enzymes; protein metabolism
Citation Formats
King, Zachary A., Drager, Andreas, Ebrahim, Ali, Sonnenschein, Nikolaus, Lewis, Nathan E., and Palsson, Bernhard O. Escher: A Web Application for Building, Sharing, and Embedding Data-Rich Visualizations of Biological Pathways. United States: N. p., 2015.
Web. doi:10.1371/journal.pcbi.1004321.
King, Zachary A., Drager, Andreas, Ebrahim, Ali, Sonnenschein, Nikolaus, Lewis, Nathan E., & Palsson, Bernhard O. Escher: A Web Application for Building, Sharing, and Embedding Data-Rich Visualizations of Biological Pathways. United States. https://doi.org/10.1371/journal.pcbi.1004321
King, Zachary A., Drager, Andreas, Ebrahim, Ali, Sonnenschein, Nikolaus, Lewis, Nathan E., and Palsson, Bernhard O. Thu .
"Escher: A Web Application for Building, Sharing, and Embedding Data-Rich Visualizations of Biological Pathways". United States. https://doi.org/10.1371/journal.pcbi.1004321. https://www.osti.gov/servlets/purl/1455068.
@article{osti_1455068,
title = {Escher: A Web Application for Building, Sharing, and Embedding Data-Rich Visualizations of Biological Pathways},
author = {King, Zachary A. and Drager, Andreas and Ebrahim, Ali and Sonnenschein, Nikolaus and Lewis, Nathan E. and Palsson, Bernhard O.},
abstractNote = {Escher is a web application for visualizing data on biological pathways. Three key features make Escher a uniquely effective tool for pathway visualization. First, users can rapidly design new pathway maps. Escher provides pathway suggestions based on user data and genome-scale models, so users can draw pathways in a semi-automated way. Second, users can visualize data related to genes or proteins on the associated reactions and pathways, using rules that define which enzymes catalyze each reaction. Thus, users can identify trends in common genomic data types (e.g. RNA-Seq, proteomics, ChIP)—in conjunction with metabolite- and reaction-oriented data types (e.g. metabolomics, fluxomics). Third, Escher harnesses the strengths of web technologies (SVG, D3, developer tools) so that visualizations can be rapidly adapted, extended, shared, and embedded. This paper provides examples of each of these features and explains how the development approach used for Escher can be used to guide the development of future visualization tools.},
doi = {10.1371/journal.pcbi.1004321},
journal = {PLoS Computational Biology (Online)},
number = 8,
volume = 11,
place = {United States},
year = {Thu Aug 27 00:00:00 EDT 2015},
month = {Thu Aug 27 00:00:00 EDT 2015}
}
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Systems Biology and Multi-Omics Integration: Viewpoints from the Metabolomics Research Community
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Interoperable and scalable data analysis with microservices: Applications in Metabolomics
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libsbmljs—Enabling web-based SBML tools
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Community-driven roadmap for integrated disease maps
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A KBase Case Study on Genome-wide Transcriptomics and Plant Primary Metabolism in Sorghum
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Compartment and hub definitions tune metabolic networks for metabolomic interpretations
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Metabolic Analyses of Nitrogen Fixation in the Soybean Microsymbiont Sinorhizobium fredii Using Constraint-Based Modeling
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Engineering and systems-level analysis of Saccharomyces cerevisiae for production of 3-hydroxypropionic acid via malonyl-CoA reductase-dependent pathway
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Population FBA predicts metabolic phenotypes in yeast
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A diurnal flux balance model of Synechocystis sp. PCC 6803 metabolism
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Rewiring monocyte glucose metabolism via C-type lectin signaling protects against disseminated candidiasis
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Enzyme promiscuity shapes adaptation to novel growth substrates
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Multi-Omics and Genome-Scale Modeling Reveal a Metabolic Shift During C. elegans Aging
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Systems Biology and Multi-Omics Integration: Viewpoints from the Metabolomics Research Community
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Answer Set Programming for Computing Constraints-Based Elementary Flux Modes: Application to Escherichia coli Core Metabolism
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