The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Escher: A Web Application for Building, Sharing, and Embedding Data-Rich Visualizations of Biological Pathways
Open accessAbstract
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Gene Expression Omnibus: NCBI gene expression and hybridization array data repository
Edgar, R. (2002) · Nucleic Acids Research · doi:10.1093/nar/30.1.207 · Cited by 13,288
A comprehensive genome-scale reconstruction of Escherichia coli metabolism—2011
Orth, J. D., Conrad, T. M., Na, J., Lerman, J. A., Nam, H., Feist, A. M., & Palsson, B. Ø. (2011) · Molecular Systems Biology · doi:10.1038/msb.2011.65 · Cited by 1,006
Self-citationThe UCSC Genome Browser database: 2014 update
Karolchik, D., Barber, G. P., Casper, J., Clawson, H., Cline, M. S., Diekhans, M., Dreszer, T. R., Fujita, P. A., Guruvadoo, L., Haeussler, M., et al. (2014) · Nucleic Acids Research · doi:10.1093/nar/gkt1168 · Cited by 670
Using process diagrams for the graphical representation of biological networks
Kitano, H., Funahashi, A., Matsuoka, Y., & Oda, K. (2005) · Nature Biotechnology · doi:10.1038/nbt1111 · Cited by 483
Genome‐scale models of metabolism and gene expression extend and refine growth phenotype prediction
O'Brien, E. J., Lerman, J. A., Chang, R. L., Hyduke, D. R., & Palsson, B. Ø. (2013) · Molecular Systems Biology · doi:10.1038/msb.2013.52 · Cited by 471
Self-citationJSBML 1.0: providing a smorgasbord of options to encode systems biology models
Rodriguez, N., Thomas, A., Watanabe, L., Vazirabad, I. Y., Kofia, V., Gómez, H. F., Mittag, F., Matthes, J., Rudolph, J., Wrzodek, F., et al. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv341 · Cited by 37
Self-citation
Cited by
BiGG Models: A platform for integrating, standardizing and sharing genome-scale models
King, Z. A., Lu, J., Dräger, A., Miller, P., Federowicz, S., Lerman, J. A., Ebrahim, A., Palsson, B. O., & Lewis, N. E. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkv1049 · Cited by 938
Self-citationArts, R. J. W., Novakovic, B., ter Horst, R., Carvalho, A., Bekkering, S., Lachmandas, E., Rodrigues, F., Silvestre, R., Cheng, S.-C., Wang, S.-Y., et al. (2016) · Cell Metabolism · doi:10.1016/j.cmet.2016.10.008 · Cited by 930
Systems biology and multi-omics integration: viewpoints from the metabolomics research community
Pinu, F. R., Beale, D. J., Paten, A. M., Kouremenos, K., Swarup, S., Schirra, H. J., & Wishart, D. (2019) · Metabolites · doi:10.3390/metabo9040076 · Cited by 723
da Silveira, W. A., Fazelinia, H., Rosenthal, S. B., Laiakis, E. C., Kim, M. S., Meydan, C., Kidane, Y., Rathi, K. S., Smith, S. M., Stear, B., et al. (2020) · Cell · doi:10.1016/j.cell.2020.11.002 · Cited by 402
Essential metabolism for a minimal cell
Breuer, M., Earnest, E. E., Merryman, C., Wise, K. S., Sun, L., Lynott, M. R., Hutchison, C. A., Smith, H. O., Lapek, J. D., Gonzalez, D. J., et al. (2019) · eLife · doi:10.7554/elife.36842 · Cited by 190
“Overview of the metabolic reconstruction of JCVI-syn3A, drawn with Escher (King et al., 2015).”
MethodFundamental behaviors emerge from simulations of a living minimal cell
Thornburg, Z. R., Bianchi, D. M., Brier, T. A., Gilbert, B. R., Earnest, E. E., Melo, M. C. R., Safronova, N., Sáenz, J. P., Cook, A. T., Wise, K. S., et al. (2022) · Cell · doi:10.1016/j.cell.2021.12.025 · Cited by 165
COBRAme: A computational framework for genome-scale models of metabolism and gene expression
Lloyd, C. J., Ebrahim, A., Yang, L., King, Z. A., Catoiu, E., O’Brien, E. J., Liu, J. K., & Palsson, B. O. (2018) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1006302 · Cited by 167
Self-citationMulti-Omics Approaches to Define Calcific Aortic Valve Disease Pathogenesis
Blaser, M. C., Kraler, S., Lüscher, T. F., & Aikawa, E. (2021) · Circulation Research · doi:10.1161/circresaha.120.317979 · Cited by 109
Model-driven design allows growth of Mycoplasma pneumoniae on serum-free media
Gaspari, E., Malachowski, A., Garcia-Morales, L., Burgos, R., Serrano, L., Martins dos Santos, V. A. P., & Suarez-Diez, M. (2020) · npj Systems Biology and Applications · doi:10.1038/s41540-020-00153-7 · Cited by 30
Machine learning predicts system-wide metabolic flux control in cyanobacteria
Kugler, A., & Stensjö, K. (2024) · Metabolic Engineering · doi:10.1016/j.ymben.2024.02.013 · Cited by 31
Population FBA predicts metabolic phenotypes in yeast
Labhsetwar, P., Melo, M. C. R., Cole, J. A., & Luthey-Schulten, Z. (2017) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1005728 · Cited by 21
Casini, I., McCubbin, T., Esquivel-Elizondo, S., Luque, G. G., Evseeva, D., Fink, C., Beblawy, S., Youngblut, N. D., Aristilde, L., Huson, D. H., et al. (2023) · iScience · doi:10.1016/j.isci.2023.108016 · Cited by 14
Self-citationDynamic visualization of multi-level molecular data: The Director package in R
Icay, K., Liu, C., & Hautaniemi, S. (2018) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2017.10.013 · Cited by 8
Metadata
- Authors
- King, Z. A., Dräger, A., Ebrahim, A., Sonnenschein, N., Lewis, N. E., & Palsson, B. O.
- Venue
- PLOS Computational Biology
- Publisher
- Public Library of Science (PLoS)
- Published
- 2015-08-27
- Volume
- 11
- Issue
- 8
- Pages
- e1004321
- ISSN
- 1553-734X (ISSN-L)
- 1553-7358
- OpenAlex
- W1665355332
- Cited by
- 385
- References
- 6
- FWCI
- 8.88
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
