Coping with complexity: machine learning optimization of cell-free protein synthesis.
about
Synthetic biology outside the cell: linking computational tools to cell-free systemsProtocols for implementing an Escherichia coli based TX-TL cell-free expression system for synthetic biologyMini-review: In vitro Metabolic Engineering for Biomanufacturing of High-value ProductsBacterial cell-free expression technology to in vitro systems engineering and optimization.A versatile coupled cell-free transcription-translation system based on tobacco BY-2 cell lysates.Compartmentalization of an all-E. coli Cell-Free Expression System for the Construction of a Minimal Cell.Cell-free protein synthesis enabled rapid prototyping for metabolic engineering and synthetic biology.Systems and synthetic biology approaches in understanding biological oscillators.
P2860
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P2860
Coping with complexity: machine learning optimization of cell-free protein synthesis.
description
2011 nî lūn-bûn
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2011年の論文
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name
Coping with complexity: machine learning optimization of cell-free protein synthesis.
@en
Coping with complexity: machine learning optimization of cell-free protein synthesis.
@nl
type
label
Coping with complexity: machine learning optimization of cell-free protein synthesis.
@en
Coping with complexity: machine learning optimization of cell-free protein synthesis.
@nl
prefLabel
Coping with complexity: machine learning optimization of cell-free protein synthesis.
@en
Coping with complexity: machine learning optimization of cell-free protein synthesis.
@nl
P2093
P2860
P50
P356
P1476
Coping with complexity: machine learning optimization of cell-free protein synthesis
@en
P2093
Andrew Buchanan
Gianluca Gazzola
James Cawse
Mark A Bedau
Norman H Packard
P2860
P304
P356
10.1002/BIT.23178
P577
2011-05-24T00:00:00Z