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Title: The Experiment Data Depot: A Web-Based Software Tool for Biological Experimental Data Storage, Sharing, and Visualization

Abstract

Although 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.

Authors:
 [1];  [2];  [3];  [3];  [2];  [4];  [2];  [2];  [2];  [5];  [5];  [5];  [5];  [4];  [6];  [2];  [7]; ORCiD logo [8]
  1. DOE Joint BioEnergy Institute, Emeryville, CA (United States); Sandia National Lab. (SNL-CA), Livermore, CA (United States)
  2. DOE Joint BioEnergy Institute, Emeryville, CA (United States); DOE Agile BioFoundry, Emeryville, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  3. DOE Joint BioEnergy Institute, Emeryville, CA (United States); Sandia National Lab. (SNL-CA), Livermore, CA (United States); DOE Agile BioFoundry, Emeryville, CA (United States)
  4. DOE Joint BioEnergy Institute, Emeryville, CA (United States)
  5. DOE Joint BioEnergy Institute, Emeryville, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  6. DOE Joint BioEnergy Institute, Emeryville, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Berkeley, CA (United States); DOE Agile BioFoundry, Emeryville, CA (United States); Technical Univ. Denmark, Horsholm (Denmark)
  7. DOE Joint BioEnergy Institute, Emeryville, CA (United States); DOE Agile BioFoundry, Emeryville, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States)
  8. DOE Joint BioEnergy Institute, Emeryville, CA (United States); DOE Agile BioFoundry, Emeryville, CA (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Basque Center for Applied Mathematics, Bilbao (Spain)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
OSTI Identifier:
1400002
Alternate Identifier(s):
OSTI ID: 1436657
Grant/Contract Number:  
AC02-05CH11231
Resource Type:
Journal Article: Published Article
Journal Name:
ACS Synthetic Biology
Additional Journal Information:
Journal Volume: 6; Journal Issue: 12; Journal ID: ISSN 2161-5063
Publisher:
American Chemical Society (ACS)
Country of Publication:
United States
Language:
English
Subject:
96 KNOWLEDGE MANAGEMENT AND PRESERVATION; -omics data; data mining; data standards; database; flux analysis; synthetic biology

Citation Formats

Morrell, William C., Birkel, Garrett W., Forrer, Mark, Lopez, Teresa, Backman, Tyler W. H., Dussault, Michael, Petzold, Christopher J., Baidoo, Edward E. K., Costello, Zak, Ando, David, Alonso-Gutierrez, Jorge, George, Kevin W., Mukhopadhyay, Aindrila, Vaino, Ian, Keasling, Jay D., Adams, Paul D., Hillson, Nathan J., and Martin, Hector Garcia. The Experiment Data Depot: A Web-Based Software Tool for Biological Experimental Data Storage, Sharing, and Visualization. United States: N. p., 2017. Web. doi:10.1021/acssynbio.7b00204.
Morrell, William C., Birkel, Garrett W., Forrer, Mark, Lopez, Teresa, Backman, Tyler W. H., Dussault, Michael, Petzold, Christopher J., Baidoo, Edward E. K., Costello, Zak, Ando, David, Alonso-Gutierrez, Jorge, George, Kevin W., Mukhopadhyay, Aindrila, Vaino, Ian, Keasling, Jay D., Adams, Paul D., Hillson, Nathan J., & Martin, Hector Garcia. The Experiment Data Depot: A Web-Based Software Tool for Biological Experimental Data Storage, Sharing, and Visualization. United States. doi:10.1021/acssynbio.7b00204.
Morrell, William C., Birkel, Garrett W., Forrer, Mark, Lopez, Teresa, Backman, Tyler W. H., Dussault, Michael, Petzold, Christopher J., Baidoo, Edward E. K., Costello, Zak, Ando, David, Alonso-Gutierrez, Jorge, George, Kevin W., Mukhopadhyay, Aindrila, Vaino, Ian, Keasling, Jay D., Adams, Paul D., Hillson, Nathan J., and Martin, Hector Garcia. Mon . "The Experiment Data Depot: A Web-Based Software Tool for Biological Experimental Data Storage, Sharing, and Visualization". United States. doi:10.1021/acssynbio.7b00204.
@article{osti_1400002,
title = {The Experiment Data Depot: A Web-Based Software Tool for Biological Experimental Data Storage, Sharing, and Visualization},
author = {Morrell, William C. and Birkel, Garrett W. and Forrer, Mark and Lopez, Teresa and Backman, Tyler W. H. and Dussault, Michael and Petzold, Christopher J. and Baidoo, Edward E. K. and Costello, Zak and Ando, David and Alonso-Gutierrez, Jorge and George, Kevin W. and Mukhopadhyay, Aindrila and Vaino, Ian and Keasling, Jay D. and Adams, Paul D. and Hillson, Nathan J. and Martin, Hector Garcia},
abstractNote = {Although 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.},
doi = {10.1021/acssynbio.7b00204},
journal = {ACS Synthetic Biology},
number = 12,
volume = 6,
place = {United States},
year = {Mon Aug 21 00:00:00 EDT 2017},
month = {Mon Aug 21 00:00:00 EDT 2017}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record at 10.1021/acssynbio.7b00204

Citation Metrics:
Cited by: 2 works
Citation information provided by
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