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.
journal_name
ACS Synth Bioljournal_title
ACS synthetic biologyauthors
Morrell WC,Birkel GW,Forrer M,Lopez T,Backman TWH,Dussault M,Petzold CJ,Baidoo EEK,Costello Z,Ando D,Alonso-Gutierrez J,George KW,Mukhopadhyay A,Vaino I,Keasling JD,Adams PD,Hillson NJ,Garcia Martin Hdoi
10.1021/acssynbio.7b00204subject
Has Abstractpub_date
2017-12-15 00:00:00pages
2248-2259issue
12issn
2161-5063journal_volume
6pub_type
杂志文章abstract::To facilitate the construction of cell-free genetic devices, we evaluated the ability of 17 different fluorescent proteins to give easily detectable fluorescence signals in real-time from in vitro transcription-translation reactions with a minimal system consisting of T7 RNA polymerase and E. coli translation machiner...
journal_title:ACS synthetic biology
pub_type: 杂志文章
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journal_title:ACS synthetic biology
pub_type: 杂志文章
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journal_title:ACS synthetic biology
pub_type: 信件
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journal_title:ACS synthetic biology
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journal_title:ACS synthetic biology
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journal_title:ACS synthetic biology
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journal_title:ACS synthetic biology
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journal_title:ACS synthetic biology
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journal_title:ACS synthetic biology
pub_type: 杂志文章
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journal_title:ACS synthetic biology
pub_type: 杂志文章
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journal_title:ACS synthetic biology
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