Escher: A Web Application for Building, Sharing, and Embedding Data-Rich Visualizations of Biological Pathways

By Zachary A. King, Andreas Dräger, Ali Ebrahim, Nikolaus Sonnenschein, Nathan E. Lewis, Bernhard O. Palsson. PLoS Comput. Biol., 2015

369 citations recorded by the source corpus.

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.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/2beb0f80a7936b222bd05916632f3983ed116ec1

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Citations in the corpus

The RCSB protein data bank: integrative view of protein, gene and 3D structural information (2016, methodology): “Our new pathway view (Figure 3) supports browsing through well-characterized metabolic pathways and visualizing 3D structures of enzymes and metabolites comprising such pathways with the Escher visualization tool (23).”
Metabolic Induction of Trained Immunity through the Mevalonate Pathway. (2018, neutral): “…Turro et al., 2011 https://github.com/eturro/mmseq DEseq Anders and Huber 2010 http://bioconductor.org/packages/ release/bioc/html/DESeq.html Escher King et al., 2015 Bwa Li and Durbin 2009 http://bio-bwa.sourceforge.net/ Samtools and Bamtools Barnett et al., 2011, Li et al., 2009…”
Pathview Web: user friendly pathway visualization and data integration (2017, methodology): “Currently, several online tools offer intuitive and useful functions for pathway and data visualization, including MAPMAN (18), VANTED (19), iPath (15), Pathway Pro-jector (12), G-language Pathway Visualization Web Application (20) and Escher (21).”
Glutaminolysis and Fumarate Accumulation Integrate Immunometabolic and Epigenetic Programs in Trained Immunity (2016, methodology): “Cells were restimulated with 200 mL RPMI, Escherichia coli LPS (serotype 055:B5, Sigma-Aldrich, 10 ng/mL), or Pam3Cys (EMC Microcollections, L2000, 10 mg/mL).”
Systems Biology and Multi-Omics Integration: Viewpoints from the Metabolomics Research Community (2019, methodology): “- Rapidly design new pathway maps based on user data and genome-scale models - Visualize data related to genes or proteins on the associated reactions and pathways - Identify trends in common genomic data types Open (MIT license) [116]”
BiGG Models: A platform for integrating, standardizing and sharing genome-scale models (2015, methodology): “The GEMs in BiGG Models can be used for modeling metabolism, interpreting omics data, visualizing metabolic phenotypes and more (9,10,24).”