Systems biotechnology for strain improvement
Various high-throughput experimental techniques are routinely used for generating large amounts of omics data. In parallel, in silico modelling and simulation approaches are being developed for quantitatively analyzing cellular metabolism at the systems level. Thus informative high-throughput analys...
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Published in | Trends in biotechnology (Regular ed.) Vol. 23; no. 7; pp. 349 - 358 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Oxford
Elsevier Ltd
01.07.2005
Elsevier Science Elsevier Limited |
Subjects | |
Online Access | Get full text |
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Summary: | Various high-throughput experimental techniques are routinely used for generating large amounts of omics data. In parallel,
in silico modelling and simulation approaches are being developed for quantitatively analyzing cellular metabolism at the systems level. Thus informative high-throughput analysis and predictive computational modelling or simulation can be combined to generate new knowledge through iterative modification of an
in silico model and experimental design. On the basis of such global cellular information we can design cells that have improved metabolic properties for industrial applications. This article highlights the recent developments in these systems approaches, which we call systems biotechnology, and discusses future prospects. |
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Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 ObjectType-Review-3 content type line 23 ObjectType-Article-1 ObjectType-Feature-2 ObjectType-Feature-3 ObjectType-Review-1 |
ISSN: | 0167-7799 1879-3096 |
DOI: | 10.1016/j.tibtech.2005.05.003 |