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Get Free AccessAlthough recent advances in synthetic biology allow us to produce biological designs more efficiently than ever, our ability to predict the end result of these designs is still nascent. Predictive models require large amounts of high-quality data to be parametrized and tested, which are not generally available. Here, we present the Experiment Data Depot (EDD), an online tool designed as a repository of experimental data and metadata. EDD provides a convenient way to upload a variety of data types, visualize these data, and export them in a standardized fashion for use with predictive algorithms. In this paper, we describe EDD and showcase its utility for three different use cases: storage of characterized synthetic biology parts, leveraging proteomics data to improve biofuel yield, and the use of extracellular metabolite concentrations to predict intracellular metabolic fluxes.
William Morrell, Garrett W. Birkel, Mark Forrer, Teresa Díaz-Faes López, Tyler W. H. Backman, Michael Dussault, Christopher J. Petzold, Edward E. K. Baidoo, Zak Costello, David Ando, Jorge Alonso-Gutiérrez, Kevin W. George, Aindrila Mukhopadhyay, Ian Vaino, Jay D Keasling, Paul D. Adams, Nathan J. Hillson, Héctor García Martín (2017). The Experiment Data Depot: A Web-Based Software Tool for Biological Experimental Data Storage, Sharing, and Visualization. , 6(12), DOI: https://doi.org/10.1021/acssynbio.7b00204.
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Type
Article
Year
2017
Authors
18
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.1021/acssynbio.7b00204
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