Literature DB >> 28826210

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

William C Morrell1,2, Garrett W Birkel1,3,4, Mark Forrer1,2,3, Teresa Lopez1,2,3, Tyler W H Backman1,3,4, Michael Dussault1, Christopher J Petzold1,3,4, Edward E K Baidoo1,3,4, Zak Costello1,3,4, David Ando1,4, Jorge Alonso-Gutierrez1,4, Kevin W George1,4, Aindrila Mukhopadhyay1,4, Ian Vaino1, Jay D Keasling1,3,4,5,6,7, Paul D Adams1,3,8, Nathan J Hillson1,3,4,9, Hector Garcia Martin1,3,4,10.   

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.

Keywords:  -omics data; data mining; data standards; database; flux analysis; synthetic biology

Mesh:

Year:  2017        PMID: 28826210     DOI: 10.1021/acssynbio.7b00204

Source DB:  PubMed          Journal:  ACS Synth Biol        ISSN: 2161-5063            Impact factor:   5.110


  9 in total

1.  Setting Up an Automated Biomanufacturing Laboratory.

Authors:  Marilene Pavan
Journal:  Methods Mol Biol       Date:  2021

Review 2.  Common principles and best practices for engineering microbiomes.

Authors:  Christopher E Lawson; William R Harcombe; Roland Hatzenpichler; Stephen R Lindemann; Frank E Löffler; Michelle A O'Malley; Héctor García Martín; Brian F Pfleger; Lutgarde Raskin; Ophelia S Venturelli; David G Weissbrodt; Daniel R Noguera; Katherine D McMahon
Journal:  Nat Rev Microbiol       Date:  2019-09-23       Impact factor: 60.633

3.  A machine learning approach to predict metabolic pathway dynamics from time-series multiomics data.

Authors:  Zak Costello; Hector Garcia Martin
Journal:  NPJ Syst Biol Appl       Date:  2018-05-29

4.  Impact framework: A python package for writing data analysis workflows to interpret microbial physiology.

Authors:  Naveen Venayak; Kaushik Raj; Radhakrishnan Mahadevan
Journal:  Metab Eng Commun       Date:  2019-04-04

5.  Better research by efficient sharing: evaluation of free management platforms for synthetic biology designs.

Authors:  Uriel Urquiza-García; Tomasz Zieliński; Andrew J Millar
Journal:  Synth Biol (Oxf)       Date:  2019-06-20

Review 6.  Organizing genome engineering for the gigabase scale.

Authors:  Bryan A Bartley; Jacob Beal; Jonathan R Karr; Elizabeth A Strychalski
Journal:  Nat Commun       Date:  2020-02-04       Impact factor: 14.919

7.  Multiomics Data Collection, Visualization, and Utilization for Guiding Metabolic Engineering.

Authors:  Somtirtha Roy; Tijana Radivojevic; Mark Forrer; Jose Manuel Marti; Vamshi Jonnalagadda; Tyler Backman; William Morrell; Hector Plahar; Joonhoon Kim; Nathan Hillson; Hector Garcia Martin
Journal:  Front Bioeng Biotechnol       Date:  2021-02-09

8.  Machine learning framework for assessment of microbial factory performance.

Authors:  Tolutola Oyetunde; Di Liu; Hector Garcia Martin; Yinjie J Tang
Journal:  PLoS One       Date:  2019-01-15       Impact factor: 3.240

9.  Research data infrastructure for high-throughput experimental materials science.

Authors:  Kevin R Talley; Robert White; Nick Wunder; Matthew Eash; Marcus Schwarting; Dave Evenson; John D Perkins; William Tumas; Kristin Munch; Caleb Phillips; Andriy Zakutayev
Journal:  Patterns (N Y)       Date:  2021-11-11
  9 in total

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