TY - JOUR
T1 - Escher: A Web Application for Building, Sharing, and Embedding Data-Rich Visualizations of Biological Pathways
AU - King, Zachary A.
AU - Draeger, Andreas
AU - Ebrahim, Ali
AU - Sonnenschein, Nikolaus
AU - Lewis, Nathan
AU - Palsson, Bernhard O.
N1 - 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 credited
PY - 2015
Y1 - 2015
N2 - 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.
AB - 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.
U2 - 10.1371/journal.pcbi.1004321
DO - 10.1371/journal.pcbi.1004321
M3 - Journal article
C2 - 26313928
SN - 1553-7358
VL - 11
JO - PLoS Computational Biology
JF - PLoS Computational Biology
IS - 8
M1 - e1004321
ER -