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Automated Planning Enables Complex Protocols on Liquid-Handling Robots.
Journal article

Automated Planning Enables Complex Protocols on Liquid-Handling Robots.

  • Whitehead E Department of Biosystems Science and Engineering , ETH Zurich and SIB Swiss Institute of Bioinformatics , Mattenstrasse 26 , 4058 Basel , Switzerland.
  • Rudolf F Department of Biosystems Science and Engineering , ETH Zurich and SIB Swiss Institute of Bioinformatics , Mattenstrasse 26 , 4058 Basel , Switzerland.
  • Kaltenbach HM Department of Biosystems Science and Engineering , ETH Zurich and SIB Swiss Institute of Bioinformatics , Mattenstrasse 26 , 4058 Basel , Switzerland.
  • Stelling J Department of Biosystems Science and Engineering , ETH Zurich and SIB Swiss Institute of Bioinformatics , Mattenstrasse 26 , 4058 Basel , Switzerland.
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  • 2018-02-28
Published in:
  • ACS synthetic biology. - 2018
automated planning
complex protocols
laboratory automation
robot programming
Automation
Green Fluorescent Proteins
Hydrogen-Ion Concentration
Mutant Proteins
Osmolar Concentration
Protein Folding
Robotics
English Robotic automation in synthetic biology is especially relevant for liquid handling to facilitate complex experiments. However, research tasks that are not highly standardized are still rarely automated in practice. Two main reasons for this are the substantial investments required to translate molecular biological protocols into robot programs, and the fact that the resulting programs are often too specific to be easily reused and shared. Recent developments of standardized protocols and dedicated programming languages for liquid-handling operations addressed some aspects of ease-of-use and portability of protocols. However, either they focus on simplicity, at the expense of enabling complex protocols, or they entail detailed programming, with corresponding skills and efforts required from the users. To reconcile these trade-offs, we developed Roboliq, a software system that uses artificial intelligence (AI) methods to integrate (i) generic formal, yet intuitive, protocol descriptions, (ii) complete, but usually hidden, programming capabilities, and (iii) user-system interactions to automatically generate executable, optimized robot programs. Roboliq also enables high-level specifications of complex tasks with conditional execution. To demonstrate the system's benefits for experiments that are difficult to perform manually because of their complexity, duration, or time-critical nature, we present three proof-of-principle applications for the reproducible, quantitative characterization of GFP variants.
Language
  • English
Open access status
closed
Identifiers
Persistent URL
https://folia.unifr.ch/global/documents/101192
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