Rapid, Reliable and Repeatable Platforms for Cell-Free Prototyping: Difference between revisions
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We are working with [http://synvitrobio.com Synvitrobio, Inc.] to develop and commercialize a cell-free platform that that emulates the in vivo environment and allows for rapid, low-cost, high-throughput, and reproducible prototyping of complex biomolecular networks. Achieving this goal will accelerate predictive and rational engineering of biology by providing an intermediary environment between design and execution. | |||
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Past participants: | |||
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Collaborators: | Collaborators: | ||
* Zachary Sun, Abel Chiao (Synvitrobio, Inc.) | |||
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=== Objectives === | === Objectives === | ||
Work at Caltech is focused on the following areas: | |||
* Reduce variability of output data from the cell-free experts by analyzing sources of variability and developing methods of calibrating cell-free data sets | |||
* Explore the use of lyophilized extracts and buffers for long-term storage. | |||
=== References === | === References === | ||
{{project paper list}} | {{project paper list}} | ||
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|Project ID=Synvitrobio SBIR | |Project ID=Synvitrobio SBIR | ||
|ack=This work is funded by DARPA SBIR contract W911NF-16-P-0003 (Caltech subcontract from Synvitrobio, Inc.). The views and conclusions contained in this document are those of the authors and should not be interpreted as representing officially policies, either expressly or implied, of the Defense Advanced Research Projects Agency or the U.S. Government.. | |||
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Latest revision as of 20:21, 4 September 2021
We are working with Synvitrobio, Inc. to develop and commercialize a cell-free platform that that emulates the in vivo environment and allows for rapid, low-cost, high-throughput, and reproducible prototyping of complex biomolecular networks. Achieving this goal will accelerate predictive and rational engineering of biology by providing an intermediary environment between design and execution.
Past participants:
|
Collaborators:
|
Objectives
Work at Caltech is focused on the following areas:
- Reduce variability of output data from the cell-free experts by analyzing sources of variability and developing methods of calibrating cell-free data sets
- Explore the use of lyophilized extracts and buffers for long-term storage.
References
- A MATLAB toolbox for modeling genetic circuits in cell-free systems. Vipul Singhal, Zoltan A. Tuza, Zachary Z. Sun, Richard M. Murray. Synthetic Biology, 6(1):ysab007, 2021.
- Cell-Free Extract Data Variability Reduction in the Presence of Structural Non-Identifiability. Vipul Singhal and Richard M. Murray. Submitted, 2019 American Control Conference (ACC).
This work is funded by DARPA SBIR contract W911NF-16-P-0003 (Caltech subcontract from Synvitrobio, Inc.). The views and conclusions contained in this document are those of the authors and should not be interpreted as representing officially policies, either expressly or implied, of the Defense Advanced Research Projects Agency or the U.S. Government..
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