Title |
Escher-FBA: a web application for interactive flux balance analysis
|
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Published in |
BMC Systems Biology, September 2018
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DOI | 10.1186/s12918-018-0607-5 |
Pubmed ID | |
Authors |
Elliot Rowe, Bernhard O. Palsson, Zachary A. King |
Abstract |
Flux balance analysis (FBA) is a widely-used method for analyzing metabolic networks. However, most existing tools that implement FBA require downloading software and writing code. Furthermore, FBA generates predictions for metabolic networks with thousands of components, so meaningful changes in FBA solutions can be difficult to identify. These challenges make it difficult for beginners to learn how FBA works. To meet this need, we present Escher-FBA, a web application for interactive FBA simulations within a pathway visualization. Escher-FBA allows users to set flux bounds, knock out reactions, change objective functions, upload metabolic models, and generate high-quality figures without downloading software or writing code. We provide detailed instructions on how to use Escher-FBA to replicate several FBA simulations that generate real scientific hypotheses. We designed Escher-FBA to be as intuitive as possible so that users can quickly and easily understand the core concepts of FBA. The web application can be accessed at https://sbrg.github.io/escher-fba . |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | 33% |
United Kingdom | 2 | 22% |
Colombia | 1 | 11% |
India | 1 | 11% |
Denmark | 1 | 11% |
Unknown | 1 | 11% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 5 | 56% |
Members of the public | 4 | 44% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 172 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 31 | 18% |
Researcher | 31 | 18% |
Student > Master | 20 | 12% |
Student > Bachelor | 16 | 9% |
Student > Doctoral Student | 8 | 5% |
Other | 18 | 10% |
Unknown | 48 | 28% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 48 | 28% |
Agricultural and Biological Sciences | 22 | 13% |
Computer Science | 13 | 8% |
Chemical Engineering | 10 | 6% |
Engineering | 10 | 6% |
Other | 13 | 8% |
Unknown | 56 | 33% |